# AlgorithmicFIRE — Full Quantitative Content & Model Index > Complete text index of research papers, quantitative models, and tool specifications. --- ## The FIRE Movement Curriculum: Learn the Math of Early Retirement URL: https://algorithmicfire.com/post/the-fire-investors-learning-track-from-beginner-to-fire Published: 2026-03-20 Category: Curriculum Review Abstract: A step-by-step curriculum for early retirement. Master Safe Withdrawal Rates, control sequence of returns risk, and optimize taxes to fast-track your FIRE goals. Date: 2026-03-20 Video: true Youtube_ID: https://youtu.be/7Lsj6k-XN_Q Duration: PT8M32S SEO_Title: The FIRE Movement Curriculum: Learn the Math of Early Retirement SEO_Description: A step-by-step curriculum for early retirement. Master Safe Withdrawal Rates, control sequence of returns risk, and optimize taxes to fast-track your FIRE goals. # The AlgorithmicFIRE Curriculum Review ### Our data-driven posts provide comprehensive resources to the math, the risks, and the strategies of Financial Independence/Retire Early (FIRE). In our Curriculum Review, we provide a summary of key posts to quick-start your journey. (Not all topics about which we have written are covered in this review.)
Curriculum At-A-Glance
1. System Math
Foundational mechanics: savings rates, time value of money, and compounding math.
2. Risk Architecture
Engineering for failure: Sequence Risk, Safe Withdrawal Rates, and stagnation.
3. Strategic Alpha
Active defense: tax arbitrage, ACA subsidies, and mechanical trend following.
## Table of Contents
Curriculum Navigation
Introduction: The Engineer's Approach to FIRE
Chapter 1
The Rules of the Game (Foundational Math)
1.1 Sequence of Returns Risk 1.2 Safe Withdrawal Rates (SWR)
Chapter 2
The Accumulation Phase (Getting There)
2.1 The Math of Saving 2.2 Advisor Fees 2.3 Tax Optimization 2.4 Engineering for ACA Subsidies 2.5 Which IRA Wins?
Chapter 3
The Decumulation Phase (Staying There)
3.1 Variable Withdrawal Strategies 3.2 SWR for Different Horizons 3.3 The Surplus Paradox
Chapter 4
Active Defense & Market Realities
4.1 The Myth of Diversification 4.2 The "Worst Case" isn't 2008 4.3 Trend Following & Options
--- ## Introduction: The Engineer's Approach to FIRE Most investment advice is built on "Hope". You hope the stock market returns 10%. You hope inflation stays low. You hope to retire at 65 and die at 90. At AlgorithmicFIRE, we don't do hope. We do math. We believe that Financial Independence Retire Early (FIRE) is an engineering problem. It is a system with: * **Inputs**: Savings rate, Investment Returns. * **Constraints**: Taxes, Inflation, Time Horizon. * **Failure Modes**: Sequence of Returns Risk, Long-term Stagnation. This summary is organized to walk you through that system from the ground up, identifying the points of failure and engineering solutions for them. It synthesizes our research into a cohesive roadmap. --- ## Chapter 1: The Rules of the Game (Foundational Math) Before you save a single dollar, you must understand the environment you are operating in. The market does not care about your plans, and "average" returns are a dangerous myth. ### 1.1 The Most Important Concept: Sequence of Returns Risk If you learn only one thing from this curriculum, let it be this: **The order of your returns matters more than the average.** During your working years (Accumulation), volatility is your friend. If the market crashes, you buy more shares for cheap. But once you retire (Decumulation), volatility is your enemy. Consider two retirees, **Alice** and **Bob**, who both start with **$1,000,000** and withdraw **$100,000/year**. They both invest in an asset that matches the S&P 500's average return, but they experience the returns in reverse order. | Year | Alice's Returns (Early Crash) | Bob's Returns (Early Boom) | | :--- | :--- | :--- | | **Year 1** | **-50%** (Crash) | **+100%** (Boom) | | **Year 2** | **+100%** (Boom) | **-50%** (Crash) | | Common Math (Avg) | **+25%** | **+25%** | | **Real CAGR** | **0%** | **0%** | | **Final Balance** | **$700,000** | **$850,000** | **What happened?** * **Alice**: Her $1M dropped to $500k. Then she withdrew $100k, leaving $400k. To get back to $1M, she needs a **150%** return, but she only got 100%. She makes her second year withdrawal, and ends up with **$700k**. * **Bob**: His $1M grew to $2M. He withdrew $100k, leaving $1.9M. The crash hurt, but he was crashing from a higher height. He makes his second year withdrawal, and ends up with **$850k**. **The Gap**: Despite having the exact same investment returns, Alice has **$150,000 less** than Bob after just 2 years. This gap will widen forever because she now has a smaller base to compound from. > These numbers are exaggerated for effect. But in real life, several down years in a row can compound and cause a permanent loss of purchasing power. This is **Sequence of Returns Risk**. It is the primary reason retirement plans fail. A market crash early in retirement creates a hole that you can never dig out of, because your withdrawals act like a shovel digging the hole deeper. * *Deep Dive: [Understanding Sequence of Returns Risk](/post/understanding-sequence-of-returns-risk)* * *Deep Dive: [Average Return - It’s Not What You Think](/post/average-return-its-not-what-you-think)* ### 1.2 The Yardstick: Safe Withdrawal Rates (SWR) To solve the Sequence of Returns problem, financial planners look for a "Safe Withdrawal Rate". This is the maximum percentage of your portfolio you can spend each year (adjusted for inflation) that would have survived the worst historical scenarios (like the Great Depression of 1929 or the Stagflation of 1966). #### Real vs. Nominal Returns We always speak in **Real** (inflation-adjusted) terms. * If your portfolio grows by **7%** (Nominal Return)... * But inflation is **4%**... * Your Real Return is only **3%**. You cannot eat nominal returns. If bread costs 4% more, your 7% gain only buys you 3% more bread. #### Why "Safe" is Hard The SWR is determined by the **worst** periods in history. Even if the market averages 7% real returns, there are long periods where it averaged at or near 0% real returns. Your plan must survive those. That is why the common recommendation is only **4%**, even though the market returns much more on average. You are paying a "safety tax" for the worst-case scenario. * *Deep Dive: [Understanding Safe Withdrawal Rate](/post/understanding-safe-withdrawal-rate)* * *Deep Dive: [Safe Withdrawal Rate Failure](/post/safe-withdrawal-rate-failure)* --- ## Chapter 2: The Accumulation Phase (Getting There) Now that you know the risks, how do you get the money? ### 2.1 The Math of Saving (Time Value of Money) There is a dangerous myth that you can "catch up" on savings later in life when you earn more money. The math of compound interest disagrees violently. Let's look at the monthly savings required to reach **$2,500,000** by age 65 (assuming 7% real return). | Starting Age | Years to Save | Monthly Savings Required | Total Cash Contributed | | :--- | :--- | :--- | :--- | | **25** | 40 | **$1011** | **$485,527** | | **35** | 30 | **$2,138** | **$769,591** | | **45** | 20 | **$4,926** | **$1,182,181** | | **55** | 10 | **$14,615** | **$1,753,855** | A dollar saved at age 25 is worth ~$15 at retirement. A dollar saved at age 55 is worth ~$2. If you wait until 45 to start, you don't just need to save *double* what the 25-year-old saves... you need to save **5x** as much. **The Strategy**: Save aggressively early. Even if you stop saving later, those early dollars will coast to victory. * *Deep Dive: [It's OK to Put Off Retirement Savings Until You're Older (Myth)](/post/its-ok-to-put-off-retirement-savings-until-youre-older-its-easier-then)* * *Deep Dive: [How Much Retirement Savings Can be Accumulated with 30 Years of Saving $1,000/month](/post/how-much-retirement-savings-can-be-accumulated-with-30-years-of-saving-1000month)* * *Deep Dive: [Hope Is Not a Strategy](/post/hope-is-not-a-strategy-retirement-takes-planning)* ### 2.2 The Headwinds: Advisor Fees You might think paying an investment advisor 1% is a fair trade. You keep 99%, they keep 1%, right? **Wrong.** They take 1% of the *assets*, not the *gains*. Imagine a **$1,000,000** portfolio growing for 30 years. * **Self-Managed (7% Return)**: Grows to **$7,612,000** * **With Advisor (6% Return after 1% fee)**: Grows to **$5,743,000** **The Cost**: Your payments to the advisor cost you **$1,869,000**. > To be clear, this is not saying that you paid the advisor $1,869,000. It is saying that the advisor cost you $1,869,000 in terms of the returns you received. Compound interest is powerful, but you reduced the compounding from 7%/year to 6%/year, which is a significant drag on your returns. In retirement, it's even worse. If your Safe Withdrawal Rate is 4%, and the advisor takes 1%, you effectively give up **25% of your annual income** (1/4th) to the advisor. >Learning to manage your own portfolio (buying simple Index ETFs like VTI or VOO) may be the highest hourly wage you will ever earn. * *Deep Dive: [Can You Afford an Investment Advisor?](/post/can-you-afford-an-investment-advisor)* ### 2.3 Tax Optimization: The Arbitrage Should you do Roth (tax now) or Traditional (tax later)? Most advice ignores the **progressive** nature of US taxes. 1. **Contribution**: You save taxes at your **Marginal Rate** (your highest bracket). If you earn $100k, every dollar you put in a Traditional 401k saves you 22% or 24% in taxes today. 2. **Withdrawal**: When you pull money out in retirement, you fill up the buckets from the bottom. * First $30k (Standard Deduction): **0% Tax** * Next $24k (10% Bracket): **10% Tax** * Next $73k (12% Bracket): **12% Tax** You could withdraw **$127,000** in retirement and pay an **Effective Tax Rate** of roughly **9%**. **The Arbitrage**: You saved 24% tax today to pay 9% tax later. That is a massive guaranteed return. *Note: This math changes if you have other income (pension, inheritance, etc.) that fills up the lower brackets first.* (This example assumes filing status is joint; individual would be lower.) > Given the tax rates and reasonable assumptions regarding Safe Withdrawal Rate, it is unlikely that the Roth IRA will be a better deal than the Traditional IRA, unless you have substantial other income in retirement. * *Deep Dive: [Simplified Roth Versus Traditional IRA Conversations May Be Costly](/post/simplified-roth-versus-traditional-ira-conversations-may-be-costly)* ### 2.4 Engineering Your Income for ACA Subsidies For early retirees, healthcare is a significant and uncertain cost. The Affordable Care Act (ACA) offers subsidies (Premium Tax Credits) that can dramatically lower premiums, but these subsidies are based on your Modified Adjusted Gross Income (MAGI). This creates a "Goldilocks" problem: earn too little, and you might fall into the Medicaid gap; earn too much, and you lose the subsidy entirely. This is where account structure becomes a powerful tool. By holding funds in both Traditional (pre-tax) and Roth (post-tax) accounts, you gain direct control over your taxable income. * **Traditional IRA/401k withdrawals** count as income, raising your MAGI. * **Roth IRA/401k withdrawals** do not count as income. You can strategically withdraw just enough from your Traditional accounts to generate the precise MAGI needed to maximize ACA subsidies, while covering the rest of your spending needs with tax-free Roth withdrawals. This turns healthcare from an uncontrollable risk into a manageable, engineered expense. * *Deep Dive: [Considering retiring early, but worried about healthcare (ACA) costs?](/post/considering-retiring-early-but-worried-about-healthcare-aca-costs)* ### 2.5 The Full Lifecycle: Which IRA Wins? We've established the tax arbitrage of Traditional vs. Roth and the utility of Traditional funds for managing ACA subsidies. But which strategy is truly better over a full lifetime of saving and spending? We ran a comprehensive simulation modeling the entire wealth lifecycle—from a first dollar saved at age 35 to a last dollar spent in retirement—across a range of incomes, savings rates, and retirement ages. The simulation accounts for compounding returns, Social Security, and the complex taxation of withdrawals, including the "tax torpedo" and Medicare (IRMAA) surcharges. The results are clear: **for most people, a Traditional-first approach is optimal.** The penalty for pre-paying taxes on Roth contributions at your high marginal rate during your career is rarely overcome by the benefit of tax-free withdrawals. The analysis introduces the concept of an "optimal tax hurdle rate"—a marginal tax rate above which a Traditional contribution is always superior. For the vast majority of scenarios, this hurdle is low, making the Traditional IRA the clear winner for accumulating wealth. * *Deep Dive: [Roth vs. Traditional IRA: A Full Lifecycle View](/post/roth-vs-traditional-ira-the-full-lifecycle-view)* --- ## Chapter 3: The Decumulation Phase (Staying There) You quit your job. Now the game changes. You are no longer growing; you are harvesting. ### 3.1 Beyond the 4% Rule: Variable Strategies The "4% Rule" assumes you act like a robot. If the market drops 50%, the rule says "Keep spending exactly $40,000 inflation-adjusted," even if that drains your portfolio to zero. No human acts like that. **Variable Withdrawal Strategies (VWS)** inject human logic into the math. * **The Rule**: If the portfolio drops, cut spending slightly. If it grows, give yourself a raise. * **The Guardrails**: * **Ceiling**: Never increase spending by more than 5% a year. * **Floor**: Never cut spending below 90% of your initial target (e.g., if you started at $40k, never spend less than $36k). By agreeing to cut spending by just 10% during a crash, you can often increase your *initial* withdrawal rate to **5% or more**. Flexibility is the most expensive insurance policy you can buy, and it costs you nothing but discipline. * *Deep Dive: [The 4% Rule Is Dead, Here's What's Replaced It](/post/the-4-rule-is-dead-heres-whats-replaced-it)* * *Deep Dive: [Variable Withdrawal Rates Enable Increased Retirement Income](/post/variable-withdrawal-rates-enable-increased-retirement-income)* ### 3.2 SWR for Different Horizons SWR is not a single number. It depends on how long you need the money to last. * **The Gap Year (10 Years)**: If you are 55 and just need to bridge the gap to a pension at 65, your SWR is massive (historically **6-8%**). Even if you deplete the capital, the pension kicks in. * **The Standard (30 Years)**: This is where the **4% Rule** lives. * **The Early Retiree (60 Years)**: If you retire at 30, you need money until 90. You face double the risk of encountering a "Lost Decade" or a Japan-style stagnation. Historical data suggests you might need to be safer, perhaps **3.25% - 3.5%**. * *Deep Dive: [Safe Withdrawal Rate for Shorter Retirements](/post/safe-withdrawal-rate-for-shorter-retirements)* ### 3.3 The Surplus Paradox Here is the irony of SWR planning: To be 100% safe against the worst-case scenario (1929), you must be incredibly conservative. But 95% of the time, 1929 *doesn't* happen. If you withdraw 4.5% and the market booms (like the 1990s or 2010s), your portfolio will explode. * **Failure**: Running out of money (Probability: ~0.2%) * **Success**: Dying with more than you started with (Probability: ~79.2%) * **Large Surplus**: Dying with more than **$2.9 Million** (nearly 3x your starting balance) (Probability: ~15.4%) "Failure" in FIRE planning usually isn't going broke; it's dying with $10 Million that you never enjoyed. You need a plan for this surplus—charity, heirs, or spending more while you are alive. * *Deep Dive: [Does Using a Safe Withdrawal Rate Mean I Likely Die With No Money?](/post/does-using-a-safe-withdrawal-rate-mean-i-likely-die-with-no-money)* --- ## Chapter 4: Active Defense & Market Realities "Buy and Hold" works... until it doesn't. ### 4.1 The Myth of Diversification You think you are diversified because you own an S&P 500 fund. But: 1. **Concentration**: Today, the top 10 stocks (Tech giants) make up **40%+** of the index. You are not buying the US economy; you are buying a Tech ETF with a side of other stuff. 2. **Correlation**: In a calm market, stocks and bonds might move differently. In a crash, **correlations go to 1**. Panic sellers sell *everything* to raise cash. True diversification requires looking beyond market-cap weighted indices (e.g., Equal Weight funds like RSP) or asset classes that structurally behave differently. * *Deep Dive: [Your Index Investments Likely Aren't as Diversified as You Think](/post/your-index-investments-likely-arent-as-diversified-as-you-think)* ### 4.2 The "Worst Case" isn't 2008 US Investors suffer from Recency Bias. We assume stocks always recover in 5 years because that's what happened in 2000, 2008, and 2020. **But look what happened in Japan.** * **1989**: The Nikkei 225 peaks. * **2009**: 20 years later, it is down **80%**. * **2024**: It finally recovers its nominal high (34 years later). A "Buy and Hold" investor retiring in Japan in 1989 went bankrupt. It didn't matter if they had a 3% withdrawal rate. The math didn't work. Valuations matter. Buying at the peak of a historic bubble can lead to decades of stagnation. * *Deep Dive: [U.S.-Based Investors Think the Worst-Case Scenario is the Great Depression or GFC. Other Countries Disagree](/post/us-based-investors-think-the-worst-case-scenario-is-the-great-depression-or-gfc-other-countries-disagree)* ### 4.3 Active Defense: Trend Following & Options If "Buy and Hold" can fail for 30 years, you need an alternative. We call this **Active Defense**. #### Strategy A: Trend Following Use simple, mechanical rules to exit the market when it is falling. * **The Rule**: If the price is below the 200-Day Moving Average, sell and go to Cash/Bonds. If it is above, buy. (We also describe a strategy that uses "excess returns" to determine when to sell. That method is generally better, but harder to describe in a single bullet point.) * **The Result**: You avoid the deep drawdowns. In 2008, you would have sold in early 2008 and sat out the crash, buying back in 2009. * **The Trade-off**: Whipsaws. In a choppy market, you will buy and sell frequently, losing small amounts. You trade small papercuts to avoid the amputation. * *Deep Dive: [Defending Your Savings Against Significant Downturns](/post/defending-your-savings-against-significant-downturns)* #### Strategy B: Put Options (Insurance) Think of this like homeowner's insurance. You pay a premium (~1% of your portfolio per year) to buy **Put Options**. These contracts guarantee that you can sell your portfolio at a set floor price (the "Strike Price"), no matter how far the market crashes. * **Pros**: Mathematical Certainty. You sleep well knowing you cannot lose more than X%. * **Cons**: Cost. That 1% drag is real, and you pay it every year, even if the market goes up. * *Deep Dive: [Buying Insurance for Your Portfolio: Put Options vs. Trend Following](/post/buying-insurance-with-put-options)* --- ## 4% Rule Bond Sensitivity: Duration, Credit Quality & Allocation | AlgorithmicFIRE URL: https://algorithmicfire.com/post/why-your-bond-choice-can-break-the-4-percent-rule Published: 2026-07-22 Category: General Investing Abstract: A data-driven analysis of how deviating from Bengen's original 5-year Treasury bond prescription affects safe withdrawal rate (SWR) survival. Covers bond duration, credit quality, allocation sweeps, and dynamic trend-following under a behavioral capital floor. Date: 2026-07-22 Video: false SEO_Title: 4% Rule Bond Sensitivity: Duration, Credit Quality & Allocation | AlgorithmicFIRE SEO_Description: A data-driven analysis of how deviating from Bengen's original 5-year Treasury bond prescription affects safe withdrawal rate (SWR) survival. Covers bond duration, credit quality, allocation sweeps, and dynamic trend-following under a behavioral capital floor. # Why Your Bond Choice Can Break the 4% Rule ### Bengen specified 5-year U.S. Treasuries for a reason. This analysis shows what happens historically when investors substitute other bond types — and how much it matters which bonds you hold. In our [prior post](/post/can-you-safely-retire-on-a-100-percent-stock-portfolio), we replicated Bill Bengen's classic 4% rule. Bengen was specific about the bond component: intermediate-term U.S. Treasuries with roughly a 5-year maturity. In practice, however, many investors following the 4% rule hold something different — bond index funds with longer effective durations, corporate bond exchange-traded funds (ETFs), target-date funds, or high-yield bond sleeves — often without considering how that choice changes the underlying risk profile. During the replication work for that post, we found that Safe Withdrawal Rate (SWR) outcomes are remarkably sensitive to which bonds you hold. The difference between 5-year Treasuries and 20-year Treasuries, or between Treasuries and BAA corporates, is not a rounding error — it has historically been the difference between a retirement that survives comfortably and one that collapses in 15 years. All simulations sweep monthly cohorts from January 1930 through the present at a **4.0% SWR**, capped at a **40-year horizon** to prevent timeline truncation bias. Bengen's original analysis used a 30-year horizon; we extend to 40 years to stress-test longer retirements, which matters particularly for early retirees. --- ## 1. A Better Definition of Retirement Failure Bengen's original 4% rule framework relies on two core assumptions: * **Solvency Criterion ($0 Balance)**: A portfolio "passes" as long as account value stays strictly above $0 through the end of the timeline. * **30-Year Horizon**: Bengen validated his 4% rule across a 30-year retirement window. We extend this to **40 years** throughout this post, as longer horizons are critical for early retirees (FIRE). ### Why a "Wealth Reaches $0" Definition is Inadequate The standard zero-balance definition is inadequate for a behavioral analysis. In practice, a retiree who has lost 40% of their real purchasing power in the first few years of retirement is not going to continue following the plan. The psychological and behavioral reality is that most people would capitulate, sell, cut spending, or seek work long before their account reaches zero. The $0 failure threshold measures mathematical solvency, not behavioral viability. To capture this, we use a **Behavioral Capital Floor**. A cohort is marked as a behavioral failure the moment its real purchasing power breaches a time-scaled floor: $$\text{Floor}(t) = \text{Initial Principal} \times \max\left(0.05,\ 0.60 \times \frac{\text{Years Remaining}}{\text{Total Horizon}}\right)$$ At the start of a 40-year retirement, a cohort fails if real wealth ever drops below **60% of initial principal**. The floor decays linearly to 5% by year 40, relaxing the constraint as the horizon shortens — reflecting that a small balance late in retirement is less alarming than the same balance in year two. The chart below shows what this means for the classic Bengen scenario: a passive 50/50 portfolio of S&P 500 and 5-Year U.S. Treasuries at 4.0% SWR. ![Ruin Definition Comparison](survival_ruin_definition.png) The contrast between the two panels makes the point clearly: * **1960s cohorts**: Under Bengen's original 30-year criterion, nearly all 1960s cohorts passed — consistent with his published findings, and confirming our replication is accurate. Extending the horizon to **40 years** under the same $0 solvency definition, only **53% of cohorts** completed the full window. Under our Capital Floor, that falls further to **36% passed** — and the median portfolio survival collapsed to **15.46 years**. Each step reveals failure that the prior step concealed. * **1970s cohorts**: Bengen's metric shows **100% pass** — not a single portfolio went to zero. Yet the Capital Floor reveals that **25% of these cohorts breached the behavioral threshold**, with the interquartile range (IQR) of survival spanning roughly 33 to 40 years. Mathematically solvent; behaviorally vulnerable. * **1930s**: Both methods show a pass rate near 90%, and no bar is visible in either panel because the small number of failures occur very late in the simulation — cohorts that failed did so around years 38–39, well beyond Bengen's original 30-year window. Every single 1930s cohort would have passed under Bengen's original criterion. * **1940s, 1950s, 1980s**: 100% pass under both definitions. > Every simulation in the remainder of this post uses a 40 year horizon and the Behavioral Capital Floor as the failure criterion. --- ## 2. Defining the Portfolios & Simulation Methodology To evaluate the impact of bond maturity, credit quality, and active management, we compare two primary portfolio architectures built from the S&P 500, various bond indices, and 3-Month Treasury Bills (the cash exit destination): 1. **Passive Stock-Bond Mix (Buy & Hold)**: The classic static asset allocation benchmark. It holds a fixed ratio of equities (S&P 500 total return index, dividends reinvested) and bonds (either U.S. Treasuries or Moody's Corporate bonds, depending on the simulation), rebalanced **annually** back to target weights. 2. **Dynamic Stock-Bond Mix (ER_MMA Overlay)**: The active risk-managed alternative. It holds the same asset ratio, but applies our Excess Return Multiple Moving Average ([ER_MMA](/post/defending-your-savings-against-significant-downturns#examination-of-trend-following-methods)) trend-following model independently to both the equity and bond sleeves. Rather than relying on a single moving average, ER_MMA uses an ensemble of multiple moving average lookback windows to dynamically scale allocation (0%, 33.3%, 66.7%, or 100%) in the target asset based on excess return over cash (3-Month Treasury Bills), sweeping uninvested capital into T-bills to defend against capital losses. *Note: All trend-following simulations incorporate a conservative 0.05% trading fee (slippage) on transacted volumes when a sleeve shifts allocation. Withdrawal amounts are adjusted annually for CPI inflation, matching Bengen's original methodology, but portfolio survival is capped at **40 years** under our Behavioral Capital Floor metric.* --- ## 3. Does Your Bond Choice Matter? (Duration & Credit Sensitivity) Given the Capital Floor as our metric, how much does the choice of bond affect outcomes? We simulated a balanced **50/50 stock-bond portfolio** across two dimensions: * **Duration**: Intermediate 5-Year constant maturity vs. Long 20-Year constant maturity * **Credit tier**: U.S. Treasuries (rate risk only), Moody's AAA Corporates, and Moody's BAA Corporates (lowest investment-grade tier) * **Management style**: Passive buy-and-hold vs. Dynamic ER_MMA (Excess Return Multi-Sleeve Moving Average) trend-following applied to both sleeves ![Bond Duration & Credit Sensitivity](survival_duration_type_combined.png) > **How to Read This Chart**: Each boxplot summarizes the distribution of portfolio survival years across all monthly cohorts starting in that decade. The colored box covers the middle 50% of outcomes (25th to 75th percentile) with the center line marking the median, while the whiskers show the full range of survival times. A green **"100% PASS"** badge indicates that every cohort in that decade completed the full 40-year retirement without breaching the capital floor. ### Key Observations #### Passive Portfolios (Buy & Hold) * **The 1960s Stagflation Collapse**: * A portfolio with a **Passive 5Y Treasury** bond sleeve survived a median of only **15.46 years** in the 1960s, with just 36% of cohorts completing the full horizon. High inflation eroded real purchasing power while rising interest rates generated capital losses in the bond sleeve — simultaneously destroying both sides of the 50/50 portfolio. * Switching the bond sleeve to **Passive 5Y AAA Corporates** slightly improved median survival to **17.50 years** (48% full pass), but did not change the overall failure regime. * Utilizing **Passive 5Y BAA Corporates** in the bond sleeve improved the portfolio to a **40-year median** (62% full pass). The higher credit spread provided a yield buffer against inflation, though over one-third of these cohorts still failed behaviorally. * **Passive 20Y Bonds Failed Catastrophically Across Both the 1960s and 1970s**: * **1960s Cohorts**: Suffered rapid early ruin as 20Y Treasury portfolios collapsed to a **10.46-year median survival** (only 2% completed 40 years). AAA Corporates fell to **10.62 years** (8% pass) and BAA Corporates to **11.79 years** (16% pass). Rising interest rates destroyed bond capital value right as inflation eroded real purchasing power. * **1970s Cohorts**: Long duration remained severely vulnerable. Under Bengen's original $0 rule, **10.8% of 1970s cohorts with 20Y Treasuries suffered complete zero-balance bankruptcy**. Under our Capital Floor metric, **45.0% of 20Y Treasury cohorts failed**, breaching the 60% real wealth threshold within a mean of **just 6.54 years** of retirement due to early-1970s stagflation and late-70s Volcker rate hikes. #### Dynamic Portfolios (ER_MMA Overlay) * **1960s Rate-Hike Failures Eliminated Entirely**: * Applying the ER_MMA trend filter to both sleeves achieved **100% pass in the 1960s across all bond types and both durations**. The trend signal rotated the bond sleeve into cash (T-bills) during rising-rate periods, preventing the capital losses that destroyed passive portfolios. * **The 1930s Trend Whipsaw Cost & Credit Compensation**: * The Great Depression created a choppy, mean-reverting environment for trend signals. A dynamic portfolio holding a **5Y Treasury** bond sleeve dropped to a **33.12-year median** in the 1930s (31% full pass) due to whipsaw drag. * Adding credit spread compensated significantly for this whipsaw cost: a **Dynamic 5Y AAA** sleeve achieved 56% pass, while a **Dynamic 5Y BAA** sleeve reached **90% full pass** (40-year median) in the 1930s. > **Behavioral Capitulation vs. Mathematical Recovery**: Some of the passive cohorts that failed the Capital Floor test in the 1930s and 1960s actually finished the 40-year horizon with an account balance above $0 (thus passing Bengen's rule). However, because they suffered early drawdowns exceeding 40% of their real purchasing power, they are categorized here as behavioral failures. In the real world, a retiree is highly unlikely to stay the course through a 40%+ drop in their real net worth; they would capitulate and lock in losses, making eventual mathematical recovery irrelevant. --- ## 4. Does the Stock-Bond Split Matter? (Allocation Sweep) To isolate the effect of the stock-bond ratio, we swept five allocations from 70/30 down to 30/70. Since Chart 2 identified the best bond for each style, the comparison is designed as a fair contest: * **Passive panel**: 5-Year U.S. Treasuries (the standard Bengen bond) * **Dynamic panel**: 5-Year BAA Corporates with ER_MMA trend-following (the strongest bond from Chart 2) ![Allocation Sweep](survival_allocation_sweep.png) ### Key Observations * **Passive stock-bond allocations all fail the same way in the 1960s**: * Across all five stock-bond allocations, the 1960s produced 15–16 year median survivals under the Capital Floor. Whether a retiree held 70% stocks or 30% stocks, the bond sleeve dragged outcomes into failure territory. Diversification did not help because both equities and bonds underperformed inflation-adjusted real returns simultaneously. While some equity-heavy passive portfolios eventually recovered mathematically by year 40, they suffered devastating real-value drawdowns early on that breached the behavioral threshold. * Conservative passive allocations (30% stocks / 70% bonds) show additional weakness in the 1930s (32.50-year median SWR survival, 31% pass) and 1940s (36.08-year median, 35% pass), where low Treasury yields were insufficient to sustain 40 years of real withdrawals. * **Dynamic BAA eliminated decade-level failures at and above 50/50 stock weight**: * The **Dynamic 70/30**, **60/40**, and **50/50** portfolios achieved 90–100% full pass in every decade including the 1930s and 1960s. The BAA credit spread combined with trend-following provided enough yield and downside protection to prevent the portfolio from ever breaching the behavioral floor. * **Dynamic 40/60** (40% stocks) shows some degradation in the 1930s (76% pass) and 1940s (87% pass) — where the relatively modest equity weight limited the portfolio's ability to recover from early drawdowns. * **Dynamic 30/70** (30% stocks) shows the most vulnerability: 60% full pass in the 1930s and 68% in the 1940s. With the stock sleeve reduced to 30%, the portfolio lacks sufficient compounding power to consistently sustain 40 years of 4% real withdrawals under a behavioral floor constraint, even with BAA corporate trend bonds protecting the downside. --- ## Summary Four practical conclusions emerge from this sensitivity analysis: 1. **Risk-managed trend-following restores 40-year viability to the 4% rule**: Under a realistic Behavioral Capital Floor, a passive 50/50 portfolio collapses to a 15.46-year median survival in the 1960s. Applying the ER_MMA trend overlay with BAA corporate bonds restores 40-year survival rates to **90%–100% across all historical stress decades** (1930s, 1960s, and 1970s). 2. **Avoid long bond durations in passive portfolios**: 20-Year bonds are an SWR catastrophe in inflationary or rate-hiking regimes. If holding bonds passively, intermediate maturities (5Y or shorter) substantially reduce duration risk. 3. **Credit quality matters, but is not a silver bullet passively**: In the 1960s, 5Y BAA corporates outperformed Treasuries and AAA bonds in passive portfolios — but 38% of cohorts still breached the behavioral floor. The credit spread helped, but did not prevent failure across the board. 4. **Trend-following on the bond sleeve rescues passive failure modes**: Applying the ER_MMA trend filter to both sleeves eliminated the 1960s failure entirely, converting a decade of near-universal behavioral failure into 100% pass regardless of bond type or duration. The combination of BAA corporate credit spread and trend signal also largely resolved the 1930s whipsaw problem present in Treasury-only dynamic portfolios. ### Bonus Benchmark: 100% Historical Pass Max SWR Comparison To provide a direct reference for readers evaluating traditional SWR rules versus our Behavioral Capital Floor, the table below shows the **Maximum Safe Withdrawal Rate (Max SWR)** that achieved **100% survival across all historical monthly cohorts (1930–present)** under both Bengen's original $0 solvency metric and our 40-year Behavioral Capital Floor: | Portfolio Architecture | 30-Year Horizon
(Bengen $0 Solvency) | 40-Year Horizon
(Bengen $0 Solvency) | 40-Year Horizon
(Behavioral Capital Floor) | | :--- | :---: | :---: | :---: | | **Passive 50/50 (5Y Treasuries)** | **3.95%** | **3.65%** | **3.05%** | | **Dynamic 50/50 (5Y BAA Trend)** | **4.20%** | **3.70%** | **3.65%** | | **Dynamic 60/40 (5Y BAA Trend)** | **4.15%** | **3.75%** | **3.40%** | | **Dynamic 70/30 (5Y BAA Trend)** | **4.10%** | **3.70%** | **2.00%** | *Key Takeaway*: In Bengen's original 30-year window, active trend management boosts the 100% safe withdrawal rate from **3.95% to 4.20%** (+25 bps). Over a 40-year early-retirement horizon under the Behavioral Capital Floor, active trend management increases the 100% safe withdrawal floor from **3.05% to 3.65%** (+60 bps). --- ## Data Sources, Provenance & Model Limitations To ensure absolute mathematical reproducibility and academic transparency, the underlying datasets, conjoining boundaries, and historical modeling assumptions are documented below: ### 1. Primary Data Registry | Asset / Metric | Source Agency | Series ID / Endpoint | Splicing & Conjoining Boundary | Modeling Details | | :--- | :--- | :--- | :--- | :--- | | **S&P 500 Daily OHLC** | Yahoo Finance | `^GSPC` | Continuous (1927–Present) | Daily resolution; adjusted close includes dividends. | | **Consumer Price Index** | Bureau of Labor Statistics | FRED `CPIAUCNS` | Continuous (1927–Present) | Monthly resolution; forward-filled to daily. Used for real-wealth SWR adjustments. | | **3-Month Treasury Yield** | Federal Reserve (FRED) & NBER | `M1329AUSM193NNBR` / `TB3MS` | Spliced on **January 1, 1934** | Pre-1934 utilizes NBER daily average short-term security notes; post-1934 utilizes standard FRED 3-Month T-Bill yields. | | **5-Year Treasury Yield** | Federal Reserve (FRED) & Shiller | `GS5` / `Long Interest Rate` | Spliced on **April 1, 1953** | Pre-1953 utilizes Robert Shiller's 10-Year Government Yield curve minus a fixed 0.60% term premium adjustment; post-1953 uses FRED GS5. | | **Moody's AAA Corporate Yield** | Federal Reserve (FRED) | `AAA` | Continuous (1919–Present) | Used for high-grade corporate bond SWR calculations; forward-filled to daily. | | **Moody's BAA Corporate Yield** | Federal Reserve (FRED) | `BAA` | Continuous (1919–Present) | Used for lower-tier investment-grade corporate bond SWR calculations; forward-filled to daily. | | **S&P 500 Dividend Yield** | Robert Shiller Database | multpl.com monthly S&P yield | Continuous (1871–Present) | Linearly resampled and accrued daily: $\text{Yield}_{\text{daily}} = \text{Yield}_{\text{annual}} / 252$. | ### 2. Splicing Proxy Disclosures & Term Premium Sensitivity * **Pre-1953 5-Year Treasury Proxy**: Because constant-maturity 5-Year Treasury Yield data (`GS5`) is not published before April 1953, the yields for 1927–1953 are estimated using Robert Shiller's 10-Year Long Interest Rate minus a fixed 0.60% (60 bps) term premium proxy. This represents the average term premium during the Federal Reserve's World War II interest rate peg era (1942–1951). Actual historical spreads between the 5-Year and 10-Year yield varied between 0.45% and 0.75%. Modeling sensitivity sweeps indicate that a ±15 bps shift in this yield proxy does not materially affect the final Safe Withdrawal Rate (SWR) survival percentages or Bengen's 4.0% SWR benchmark. * **Dividend Yield Accrual Smoothing**: S&P 500 dividends are modeled as a smooth daily linear accrual (Yield / 252) rather than lumpy quarterly distributions. This is standard in 90-year historical backtests to avoid dependency on specific dividend declaration dates, introducing negligible variance to long-term SWR survival math. * **Execution lag & slippage**: All systematic trend-following allocations incorporate a next-day open execution lag (signals calculated at Close T, executed at Open T+1) and a fixed 0.05% (5 bps) transaction slippage fee. --- ## Can You Safely Retire on a 100% Stock Portfolio? | AlgorithmicFIRE URL: https://algorithmicfire.com/post/can-you-safely-retire-on-a-100-percent-stock-portfolio Published: 2026-07-20 Category: General Investing Abstract: A data-driven replication of Bengen's 4% rule using 5-Year U.S. Treasuries showing that systematic trend-following matches bonds for SWR safety, generates crash alpha, and is not simply a higher-risk strategy. Date: 2026-07-20 Video: false SEO_Title: Can You Safely Retire on a 100% Stock Portfolio? | AlgorithmicFIRE SEO_Description: A data-driven replication of Bengen's 4% rule using 5-Year U.S. Treasuries showing that systematic trend-following matches bonds for SWR safety, generates crash alpha, and is not simply a higher-risk strategy. # Can You Safely Retire on a 100% Stock Portfolio? Trend-Following, SWRs, and the Sequence Risk Trade-Off ### Replicating Bengen's 4% rule with historically accurate intermediate-term Treasuries shows that trend-following allows retirees to hold 100% equity portfolios nearly as safely as a passive 50/50 allocation—but combining the two introduces a costly double drag in growth regimes. The standard "4% rule" is the most widely cited benchmark in retirement planning. Originating from Bill Bengen's landmark 1994 study, it demonstrated that historically, a 4% initial withdrawal rate—adjusted annually for inflation—was the worst-case floor (what Bengen termed "SAFEMIN") that survived every rolling 30-year cohort in modern U.S. history. Bengen's result rested on two specific implementation choices that are routinely misunderstood: 1. **He used 5-Year intermediate-term U.S. Treasuries**, not long-duration bonds or corporate credit. Longer bonds suffer severe capital losses during inflation spikes; shorter-duration Treasuries cushion that blow. 2. **He adjusted withdrawals annually**, not monthly. Monthly CPI adjustments continuously compound withdrawals upward during high-inflation years, dramatically worsening simulated outcomes. Many modern retirees are reluctant to hold static bonds because of low yields and high inflation drag. In this case study, we test an alternative thesis: **can a retiree hold a 100% equity portfolio to maximize compounding, but use systematic trend-following instead of a static bond allocation to defend against sequence risk?** To answer this, we use daily S&P 500 data from 1927 to 2026, a reconstructed continuous 5-Year U.S. Treasury yield curve (FRED GS5 from 1953, Shiller 10Y minus 60 bps for 1930–1952), and 3-Month T-Bill yields as the cash alternative. We test three distinct retirement portfolios across 799 rolling 30-year windows and four major crisis case studies. > The intention of this research is **NOT** an endorsement of any of the portfolios presented, but instead to show how trend-following impacts Safe Withdrawal Rate (SWR) relative to the historical standard. > **Note: Data Constraints & Modern ETFs** > > Modern financial markets offer thousands of specialized ETFs (covering corporate credit, commodities, liquid alternatives, etc.). However, running a mathematically rigorous **30-year rolling SWR analysis** requires at least 80 to 90 years of daily historical data to capture multiple independent 30-year cycles. If we used assets with data starting in the 1990s (when ETFs were first introduced) or corporate credit indices (many of which only have reliable daily data since 2008), we would have only *one* completed 30-year window to analyze. This would completely omit the Great Depression (1930s) and the stagflation era (1970s)—the exact macroeconomic shocks that define the boundaries of safe retirement withdrawals. To preserve historical integrity, we restrict our analysis to fundamental indices (broad equities, Treasuries, and cash) with continuous data reaching back to 1927. --- ## Defining the Three Portfolios To evaluate this strategy, we compare three realistic portfolios built from the S&P 500, 5-Year U.S. Treasury bonds, Moody's AAA Corporate bonds, and 3-month Treasury Bills (the cash exit destination during trend-following downtrends): 1. **Passive 50/50 (5Y Treasuries)**: The traditional balanced baseline, closely matching Bengen's original allocation. It holds a static 50% S&P 500 and 50% 5-Year U.S. Treasury bonds, rebalanced **annually** to target weights. 2. **Dynamic 100% Equity (ER_MMA)**: The aggressive trend-following alternative. It starts 100% invested in the S&P 500, but uses our [Excess Return Multiple Moving Average (ER_MMA)](/post/defending-your-savings-against-significant-downturns#examination-of-trend-following-methods) ensemble model to dynamically scale allocation and exit to cash (T-bills) during downtrends. 3. **Dynamic 50/50 (AAA Corporates)**: The hybrid overlay. Both the S&P 500 stock sleeve (50%) and the 5-Year Moody's AAA Corporate bond sleeve (50%) are managed dynamically using the [ER_MMA](/post/defending-your-savings-against-significant-downturns#examination-of-trend-following-methods) trend-following signal ensemble. When either stocks or bonds enter a downtrend, their respective sleeve rotates to cash (3-Month T-Bills) to defend against capital losses. *Note: All trend-following simulations incorporate a conservative 0.05% trading fee (slippage) on days when the portfolio shifts allocation. Withdrawal amounts are adjusted annually for CPI inflation, matching Bengen's original methodology.* --- ## Replicating Bengen's Benchmark: SWR Success Rates (1930 - 1996) By running rolling 30-year simulations starting monthly from January 1930 through May 1996 (representing 799 completed historical retirement windows), we calculated the success rate for each portfolio across a range of initial Safe Withdrawal Rates (SWR). * **Initial SWR**: The percentage withdrawn from the starting portfolio value in Year 1 (e.g., $40,000 on a $1,000,000 portfolio for a 4.0% SWR). This baseline dollar amount is adjusted annually for CPI inflation in all subsequent years. * **Max Sustainable SWR**: The highest initial withdrawal percentage at which a portfolio survived the full 30-year window without reaching zero. ![SWR Success Rate Comparison](swr_success_comparison.png) ### SWR Success Rates across 799 Historical 30-Year Windows: | SWR (%) | Passive 50/50 (5Y Treasuries) | Dynamic 100% MMA | Dynamic 50/50 (AAA Corporates) | | :---: | :---: | :---: | :---: | | **3.50%** | **100.00% (0 fails)** | **100.00% (0 fails)** | **100.00% (0 fails)** | | **3.75%** | **100.00% (0 fails)** | **100.00% (0 fails)** | **100.00% (0 fails)** | | **4.00%** | **99.75% (2 fails)** | 99.37% (5 fails) | 96.87% (25 fails) | | **4.25%** | 94.24% (46 fails) | **98.75% (10 fails)** | 92.62% (59 fails) | | **4.50%** | 89.36% (85 fails) | **93.12% (55 fails)** | 78.22% (174 fails) | | **5.00%** | 74.47% (204 fails) | **84.11% (127 fails)** | 61.83% (305 fails) | ### Key Findings from the Rolling Analysis: * **Bengen's 4% Rule Is Verified**: The Passive 50/50 (5Y Treasuries) portfolio achieves a **99.75% success rate** at the classic 4.0% SWR—only 2 failures across 799 historical windows. This generally replicates Bengen's original finding using his actual bond duration and annual rebalancing methodology. * **Dynamic 100% MMA Is Highly Competitive at 4%**: At 4.0% SWR, the Dynamic 100% MMA achieves a **99.37% success rate** (5 failures)—statistically equivalent to the passive balanced portfolio. Systematic trend-following allows retirees to hold a 100% equity allocation with almost the same survival probability as a traditional 50/50 portfolio, while preserving full compounding during bull markets. * **Above 4.25% SWR, Dynamic 100% MMA Decisively Dominates**: At every withdrawal rate above 4.25%, trend-following's crash avoidance significantly outperforms the passive bond cushion. At 5.0% SWR, Dynamic 100% MMA succeeds **84.11%** of the time versus **74.47%** for Passive 50/50—nearly 10 percentage points better. * **The "Dynamic 50/50" Whipsaw Drag (in Growth Regimes)**: The hybrid Dynamic 50/50 portfolio (using dynamic S&P 500 and dynamic Corporate AAA sleeves) underperforms both alternatives in standard U.S. history at all SWR levels above 3.50% due to whipsaw drag on both sleeves. At 4.0% SWR its failure rate is 12× higher than Passive 50/50 (25 failures vs. 2), and at 4.25% SWR it achieves **92.62%** success, underperforming both pure alternatives. ### The Math Behind the Dynamic 50/50 Trade-off (The Diluted Base Drag in Growth Regimes) Why does overlaying trend-following on a 50/50 stock sleeve perform so poorly compared to applying it to a 100% equity portfolio? 1. **The Whipsaw Drag (Insurance Premium)**: Trend-following is a reactive system that pays a cost in false exits and delayed re-entries at market turning points. On a portfolio level, this drag is proportional to the size of the equity sleeve—halved in a 50/50 portfolio compared to a 100% equity portfolio. 2. **The Diluted Compounding Base**: During market recoveries, the dynamic equity sleeve only compounds on a 50% base, making it much harder for the portfolio to overcome even its halved whipsaw drag. In a 100% MMA portfolio, the entire base participates in recoveries, easily overcoming whipsaw drag. In a static 50/50 portfolio, there is zero entry lag and zero whipsaw, capturing the recovery on a 50% base from day one. The hybrid Dynamic 50/50 pays a whipsaw premium on the stock sleeve, and has its recovery upside severely diluted—the worst of both worlds in growth regimes. --- ## When Did Failures Occur? A Decade-by-Decade Breakdown The following heatmap visualizes the success rate for the Passive 50/50 (5Y Treasuries) and Dynamic 100% MMA portfolios by the decade when retirement began. Red cells represent high failure rates; green cells represent perfect survival. ![SWR Failure Heatmap by Decade](swr_failure_heatmap.png) At standard withdrawal rates (at or below 4.0% SWR), both portfolios are highly resilient. The primary differences emerge at 4.5% SWR and above: * **The 1960s Stagflation Trap**: The 1966–1969 cohorts are the hardest windows for the Passive 50/50 portfolio. Triple-digit CPI inflation combined with stagnant equity markets slowly eroded the bond cushion as rates surged, driving severe capital losses in the 5-Year Treasury sleeve. The Dynamic 100% MMA portfolio navigates this window significantly better at higher SWRs by maintaining 100% equity exposure during recoveries without a bond sleeve to damage. * **The 1940s & 1950s Bond Drag**: During the high-growth post-WWII era, interest rates were low and the equity market compounded strongly. The Dynamic 100% MMA portfolio, fully invested in equities, achieved significantly higher success rates at SWRs of 4.5% and 5.0%. * **Tail Protection**: Trend-following's main advantage is not raising average returns, but protecting retirees who start exactly at valuation peaks (like 1929 and 2000), preventing sequence risk from turning into permanent ruin. --- ## Case Study 1: The Great Depression (Retiring in September 1929) The most catastrophic sequence-of-returns event in American financial history began in September 1929. Within three years, the S&P 500 collapsed **89%**. ![1929 Wealth Curves and ER_MMA Equity Exposure](wealth_curve_1929_with_exposure.png) ### Sept 1929 Retirement Outcomes ($1M Start, 30-Year Horizon): | Portfolio | Max Sustainable SWR | Terminal Wealth (4.0% SWR) | Terminal Wealth (4.5% SWR) | Survival Status (4.5% SWR) | | :--- | :---: | :---: | :---: | :---: | | Passive 50/50 (5Y Treasuries) | 4.20% | $178,961 | $0 | Failed | | **Dynamic 100% Equity (ER_MMA)** | **5.80%** | **$2,195,927** | **$1,611,648** | **Succeeded** | | Dynamic 50/50 (AAA Corporates) | **6.30%** | **$1,395,395** | **$1,095,191** | **Succeeded** | The Passive 50/50 portfolio—despite holding 50% in intermediate Treasuries—achieved only a 4.20% Max SWR. At a 4.5% SWR it failed entirely. The 1929 deflation briefly helped by reducing the real size of withdrawals, but the high inflation of the 1940s and 1950s reversed that benefit and eroded the bond cushion's purchasing power over the full 30-year horizon. By rotating to cash as the trend broke down in late 1929, the **Dynamic 100% MMA** portfolio preserved its capital base, then captured the explosive recoveries of 1933 and 1935. At a 4.0% SWR, it ended with **$2.20M**—nearly 12× the terminal wealth of the Passive 50/50 portfolio. --- ## Case Study 2: Sideways Chop and Inflation (Retiring in 1966) A retiree starting in January 1966 faced a perfect storm: high inflation (CPI tripled between 1966 and 1982) and stagnant nominal equity markets. ![1966 Wealth Curves and ER_MMA Equity Exposure](wealth_curve_1966_with_exposure.png) ### Jan 1966 Retirement Outcomes ($1M Start, 30-Year Horizon): | Portfolio | Max Sustainable SWR | Terminal Wealth (4.0% SWR) | Survival Status (4.0% SWR) | | :--- | :---: | :---: | :---: | | Passive 50/50 (5Y Treasuries) | 4.00% | $62,577 | **Succeeded** | | **Dynamic 100% Equity (ER_MMA)** | **4.20%** | **$186,685** | **Succeeded** | | Dynamic 50/50 (AAA Corporates) | 3.90% | $0 | Failed | The 1966 cohort is Bengen's "worst case" window—the one that originally defined the 4% rule's lower bound. Both the Passive 50/50 and Dynamic 100% MMA portfolios survive at 4.0% SWR, confirming Bengen's original result. However, the hybrid Dynamic 50/50 (AAA Corporates) fails at 4.0% SWR (max SWR of 3.90%) because the double trend filter sat in cash/T-bills during the rapid inflation spikes of the 1970s and was eaten away by inflation drag. Crucially, the **Dynamic 100% MMA** portfolio is the **outright winner**, finishing with **$186,685** in real terminal wealth—3× the $62,577 left in the Passive 50/50 portfolio. Despite the choppy 1970s trend environment, the ER_MMA model significantly reduced sequence-of-returns damage during the 1973–1974 bear market (-48%) and the 1977–1982 rate-shock downturn, leaving more capital to compound during recoveries. The Passive 50/50 portfolio survived, but barely. When yields surged from 8% to 16% in 1979–1981, the 5-Year Treasury sleeve suffered severe capital losses. The bond cushion that was supposed to protect the portfolio instead became a source of real-wealth destruction during the worst years—a cautionary reminder that intermediate-duration bonds are not immune to inflationary regimes. --- ## Case Study 3: Dot-Com and Global Financial Crisis (GFC) Crashes (Retiring in 2000) A retiree starting in January 2000 immediately faced consecutive crashes: the 2000–2002 Dot-Com crash (-49%) and the 2007–2009 Global Financial Crisis (-56%), followed by a roaring bull market. ![2000 Wealth Curves and ER_MMA Equity Exposure](wealth_curve_2000_with_exposure.png) ### Jan 2000 Retirement Outcomes ($1M Start, 26-Year Horizon): | Portfolio | Max Sustainable SWR | Terminal Wealth (4.0% SWR) | Terminal Wealth (4.5% SWR) | | :--- | :---: | :---: | :---: | | Passive 50/50 (5Y Treasuries) | 5.00% | $495,422 | $249,735 | | **Dynamic 100% Equity (ER_MMA)** | **5.80%** | **$1,641,788** | **$1,203,469** | | Dynamic 50/50 (AAA Corporates) | **6.90%** | **$1,749,517** | **$1,451,739** | ### Drawdown Profile from Peak (2000 Retirement at 4.0% SWR) The chart below visualizes the path risk of the Passive 50/50 portfolio vs. the Dynamic 100% MMA portfolio during this window: ![2000 Portfolio Drawdown from Peak](drawdown_profile_2000.png) By exiting equities during both major crashes, both dynamic portfolios protected their core capital. **Dynamic 100% MMA** ended the 26-year period with **$1.64M**, outperforming the Passive 50/50 portfolio by more than $1.1M. During the GFC, the **Dynamic 100% MMA** portfolio significantly cushioned the downside while the Passive 50/50 suffered a deeper drawdown. This risk protection kept the capital base intact early, allowing the portfolio to compound more aggressively during the subsequent bull market. Dynamic 100% MMA achieved a Max Sustainable SWR of **5.80%**, outperforming the Passive 50/50 portfolio (5.00%) by a full 80 basis points. --- ## Beyond the U.S.: The True Purpose of Trend-Following It is easy to look at U.S. history and assume that a passive 50/50 portfolio is "good enough" because the U.S. has always recovered from its worst depressions and stagflation cycles. But this exhibits a strong home-country bias. Retirees in other developed nations have faced sequence-of-returns risks that standard U.S. models simply cannot benchmark. To see why benchmarking against U.S. history alone is a dangerous assumption, see our detailed breakdown on [how other countries' worst-case scenarios dwarf the Great Depression](/post/us-based-investors-think-the-worst-case-scenario-is-the-great-depression-or-gfc-other-countries-disagree). > Trend-following's ultimate value is not just shielding you from temporary V-shaped drops; it is an insurance policy against **permanent capital destruction** in the event of multi-decade secular declines. To illustrate this, we model the Japanese asset bubble collapse. ### Case Study 4: The Nikkei Nightmare (Retiring in December 1989) We model a retiree who retired in December 1989 at the absolute peak of the Japanese asset bubble, holding the Nikkei 225 index. This case study assumes a U.S.-based retiree who invested their equity sleeve in the Nikkei, using U.S. CPI for inflation adjustments, and U.S. 3-Month T-bills (cash) and U.S. 5-Year Treasury bonds for their defensive allocations. ![1989 Wealth Curves and ER_MMA Equity Exposure](wealth_curve_1989_with_exposure.png) #### Dec 1989 Retirement Outcomes ($1M Start, 30-Year Horizon): | Portfolio | Max Sustainable SWR | Terminal Wealth (3.0% SWR) | Survival Status (3.0% SWR) | | :--- | :---: | :---: | :---: | | **Buy & Hold 100% Equity** | 0.80% | $0 | Failed | | **Passive 50/50 (5Y Treasuries)** | **2.50%** | $0 | Failed | | **Dynamic 100% Equity (ER_MMA)** | 2.10% | $0 | Failed | | Dynamic 50/50 (5Y Treasuries) | **3.55%** | $239,611 | **Succeeded** | *Note: Buy & Hold 100% Equity failed at 4.0% SWR in just 7.8 years. All portfolios failed at 4.0% SWR.* #### Re-evaluating the Whipsaw Trade-off in Secular Declines: In our analysis of S&P 500 history, we showed that the hybrid **Dynamic 50/50** portfolio is sub-optimal in growth regimes because equity whipsaw drag on a diluted base outweighs the modest downside protection. However, the Nikkei 1989 scenario reveals the limit of that rule: **in a permanent, multi-decade market decline, the hybrid Dynamic 50/50 portfolio is the single most resilient strategy.** Why did the Dynamic 50/50 dominate here? 1. **Prolonged Defensive Sweeps**: Because the Nikkei went into a secular bear market for 30 years, the ER_MMA trend filter spent the majority of the time in cash (0% equity exposure), bypassing the massive drawdowns entirely. 2. **The High-Yielding Bond Cushion**: The 5-Year Treasury bond sleeve yielded 5% to 8% in the 1990s and 3% to 5% in the 2000s, providing a compounding yield and cash engine that funded withdrawals throughout the 30-year horizon. 3. **Halving the Whipsaw Drag**: Because the equity allocation was halved, the whipsaw losses on false stock entries were cut in half, while the bond sleeve continued to grow. The **Dynamic 100% MMA** portfolio failed here because even intermittent re-entries into the Nikkei during bear market rallies caused severe drawdowns compounding over 30 years of stagnation. The passive bond cushion of the Dynamic 50/50 prevented this re-entry trap. --- ## The Risk-Adjusted Reality: Choose Your Trade-off Trend-following is not a magic sauce that guarantees outperformance in all markets. Its benefits are highly regime-dependent, and a retiree's optimal portfolio choice depends entirely on the **worst-case scenario they want to defend against**: 1. **If defending against standard U.S.-style sequence risk (V- or U-shaped recoveries):** * **The Dynamic 100% MMA** is the optimal choice. At 4.0% SWR it matches the Passive 50/50 in survival probability (99.37% vs. 99.75%), while providing dramatically higher terminal wealth across all case studies. At higher withdrawal rates (4.25%+), it decisively outperforms the passive alternative. Retirees get full equity compounding during bull markets plus crash protection during bear markets. * **The Passive 50/50** remains a valid choice for retirees who want to completely avoid the behavioral challenge of trend-following exits and re-entries. Its 5-Year Treasury cushion provides reliable, low-volatility income during equity drawdowns—validating Bengen's original research. * The hybrid **Dynamic 50/50** is sub-optimal in this regime at all withdrawal rates above 3.75%. The equity whipsaw drag on a diluted compounding base produces worse outcomes than either pure alternative. 2. **If defending against multi-decade secular stagnation (like Japan in 1989):** * The hybrid **Dynamic 50/50** is the undisputed winner. In a market that does not recover for 30 years, there is no "rebound upside" to dilute. Survival requires avoiding the equity market during downturns (via the trend filter) while relying on a stable Treasury yield cushion to fund withdrawals. A 100% equity allocation (even with trend-following) or a passive 50/50 allocation both lead to bankruptcy in this scenario. Ultimately, there is no single "winner." The choice comes down to a trade-off: do you want to maximize long-term wealth in a growing economy by accepting some whipsaw cost, or do you want to pay an insurance premium in growth regimes to ensure survival in a worst-case secular collapse? --- ## Addendum: Does Trend-Following Just Take More Risk? ### The most common objection to systematic strategies is that higher returns are simply compensation for higher risk. The data tells a different story. In classical finance theory (CAPM), there is no free lunch: higher returns must reflect higher risk. If trend-following produces better outcomes, the skeptic argues, it must be because it carries hidden systematic risk that eventually manifests as larger losses. This is a reasonable prior assumption—but when you measure the actual risk profile of trend-following, the objection collapses. ![Risk-Adjusted Performance Metrics](risk_metrics_summary.png) ### Full-History Risk-Adjusted Metrics (1930–Present): *Computed from monthly total returns (S&P 500 inc. dividends, 5-Year U.S. Treasury index inc. coupon). Sharpe ratio uses 3-Month T-Bill as risk-free rate. Exact figures are labeled directly on the chart above.* Three findings stand out immediately: * **Volatility is lower, not higher**: Dynamic 100% MMA produces meaningfully lower annualized volatility than Buy & Hold S&P 500. By exiting to cash during downtrends, it truncates the right side of the loss distribution—the months that cause the worst permanent damage. * **Maximum drawdown is dramatically lower**: The worst peak-to-trough loss for Dynamic 100% MMA is a fraction of the Buy & Hold figure. This is the exact opposite of what a "more risk = more return" story would predict. * **Sharpe ratio is higher**: Dynamic 100% MMA achieves a higher risk-adjusted return than both Buy & Hold equity and Passive 50/50. If the excess return were simply compensation for more risk, the Sharpe ratio would be equal or lower—not higher. --- ### Crash Alpha: Trend-Following Performs Best When Risk Is Highest The CAPM risk-premium story says: *assets that carry a risk premium should underperform in bad markets*—that is what you are being paid to endure. Value stocks underperform in recessions. Small-cap stocks underperform during liquidity crises. If trend-following were simply a risk premium, it should underperform during crashes. Instead, the opposite is true. ![Average Monthly Return by Market Regime](bear_market_returns.png) When we classify every month in the full 95-year history as either a **bear market month** (S&P 500 total return < −2%) or a **bull market month** (> +2%), the results are unambiguous: * **During bear months**: Dynamic 100% MMA has a near-zero or positive average monthly return. Buy & Hold S&P 500 has deeply negative average returns. This is the defining feature of *crisis alpha*—a strategy that provides protection precisely when traditional asset classes are most dangerous. * **During bull months**: Dynamic 100% MMA slightly lags Buy & Hold (this is the whipsaw drag—the cost of the insurance). The gap is the "insurance premium" paid in exchange for bear-market protection. This payoff profile—paying a small cost in good times to avoid large losses in bad times—is the hallmark of a **hedge**. In standard financial theory, hedges should command *negative* expected returns (investors expect to pay a premium for insurance, not receive one). The fact that trend-following generates substantial long-term excess returns *despite* providing this defensive tail-risk protection is the core empirical anomaly that standard risk-factor models struggle to explain. --- ### So What Is Trend-Following Actually Compensating? If it is not traditional market risk, what explains the premium? The most widely accepted explanation in academic literature (Moskowitz, Ooi, and Pedersen, "Time Series Momentum," *Journal of Financial Economics*, 2012) is **behavioral**: 1. **Underreaction**: Investors are slow to price new information, anchoring to recent prices and trends. This creates price momentum that persists for months before fully correcting. 2. **Herding**: Once a trend is established, institutional capital piles in, amplifying the move beyond what fundamentals warrant. 3. **Overreaction and reversal**: Eventually sentiment overcorrects—but a reactive trend-following system has already exited before the reversal is complete. These behavioral inefficiencies are not "risk factors." They are exploitable mispricings that persist because: - Trend-following requires accepting extended periods of underperformance relative to a rising market (career risk and tracking error deters most institutional investors from holding it). - Positions can be "right but early"—markets can remain in a trend longer than most investors can sustain patience or employment. This means the premium is likely to persist. But it also means trend-following has a specific and real cost: **whipsaw drag in directionless, choppy, mean-reverting markets**. This is the price of the strategy, and it shows up clearly in the bull-market bar of the chart above—Dynamic 100% MMA gives back a small portion of bull-market gains in exchange for dramatically better bear-market behavior. --- ## Data Sources, Provenance & Model Limitations To ensure absolute mathematical reproducibility and academic transparency, the underlying datasets, conjoining boundaries, and historical modeling assumptions are documented below: ### 1. Primary Data Registry | Asset / Metric | Source Agency | Series ID / Endpoint | Splicing & Conjoining Boundary | Modeling Details | | :--- | :--- | :--- | :--- | :--- | | **S&P 500 Daily OHLC** | Yahoo Finance | `^GSPC` | Continuous (1927–Present) | Daily resolution; adjusted close includes dividends. | | **Consumer Price Index** | Bureau of Labor Statistics | FRED `CPIAUCNS` | Continuous (1927–Present) | Monthly resolution; forward-filled to daily. Used for real-wealth SWR adjustments. | | **3-Month Treasury Yield** | Federal Reserve (FRED) & NBER | `M1329AUSM193NNBR` / `TB3MS` | Spliced on **January 1, 1934** | Pre-1934 utilizes NBER daily average short-term security notes; post-1934 utilizes standard FRED 3-Month T-Bill yields. | | **5-Year Treasury Yield** | Federal Reserve (FRED) & Shiller | `GS5` / `Long Interest Rate` | Spliced on **April 1, 1953** | Pre-1953 utilizes Robert Shiller's 10-Year Government Yield curve minus a fixed 0.60% term premium adjustment; post-1953 uses FRED GS5. | | **Moody's AAA Corporate Yield** | Federal Reserve (FRED) | `AAA` | Continuous (1919–Present) | Used for corporate bond addendum SWR comparison; forward-filled to daily. | | **S&P 500 Dividend Yield** | Robert Shiller Database | multpl.com monthly S&P yield | Continuous (1871–Present) | Linearly resampled and accrued daily: \\(\\text{Yield}\_{\\text{daily}} = \\text{Yield}\_{\\text{annual}} / 252\\). | ### 2. Splicing Proxy Disclosures & Term Premium Sensitivity * **Pre-1953 5-Year Treasury Proxy**: Because constant-maturity 5-Year Treasury Yield data (`GS5`) is not published before April 1953, the yields for 1927–1953 are estimated using Robert Shiller's 10-Year Long Interest Rate minus a fixed 0.60% (60 bps) term premium proxy. This represents the average term premium during the Federal Reserve's World War II interest rate peg era (1942–1951). Actual historical spreads between the 5-Year and 10-Year yield varied between 0.45% and 0.75%. Modeling sensitivity sweeps indicate that a ±15 bps shift in this yield proxy does not materially affect the final Safe Withdrawal Rate (SWR) survival percentages or Bengen's 4.0% SWR benchmark. * **Dividend Yield Accrual Smoothing**: S&P 500 dividends are modeled as a smooth daily linear accrual (Yield / 252) rather than lumpy quarterly distributions. This is standard in 90-year historical backtests to avoid dependency on specific dividend declaration dates, introducing negligible variance to long-term cumulative SWR survival math. * **Execution lag & slippage**: All systematic trend-following allocations incorporate a next-day open execution lag (signals calculated at Close T, executed at Open T+1) and a fixed 0.05% (5 bps) transaction slippage fee. --- --- ## Tactical Leverage: S&P 500 Leveraged ETF Strategy URL: https://algorithmicfire.com/post/tactical-leverage-with-the-macro-stress-index Published: 2026-06-15 Category: General Investing Abstract: Learn how to use a macro stress filter (AF-MSI™) to safely hold leveraged ETFs (SSO/UPRO) in a Three-Fund portfolio and avoid leverage decay. Date: 2026-06-15 Video: false SEO_Title: Tactical Leverage: S&P 500 Leveraged ETF Strategy SEO_Description: Learn how to use a macro stress filter (AF-MSI™) to safely hold leveraged ETFs (SSO/UPRO) in a Three-Fund portfolio and avoid leverage decay. # Tactical Leverage with the AlgorithmicFIRE Macro Stress Indicator ### A systematic case study: boosting S&P 500 returns by adding leverage only when macro indicators indicate a low-stress market regime. Leveraged exchange-traded funds (ETFs) like [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (2x S&P 500) can dramatically boost returns during bull markets, but they are highly dangerous in market downturns. The combination of daily rebalancing and market volatility leads to a phenomenon known as **volatility drag** (or leverage decay), which can cause permanent capital loss during a crash. Rather than holding leverage permanently, this case study evaluates a tactical approach: starting with a standard, conservative portfolio—like a **60/20/20 Three-Fund Portfolio**—and *tactically leveraging up* by substituting [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (2x) for [VTI](/report/VTI_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x) only during periods of extremely low macroeconomic stress. We use the **[AlgorithmicFIRE Macro Stress Indicator (AF-MSI)™](/market#af-msi)** to systematically identify these low-stress windows. ## The Mechanics of Volatility Drag and Leverage Decay Leveraged ETFs reset their exposure daily. If the S&P 500 rises 1% today, a 2x S&P 500 ETF is designed to rise 2%. However, over a multi-day holding period, the compounding of daily returns causes performance to drift from a simple multiple of the index. Consider this two-day example of daily compounding: * **Day 1**: The S&P 500 drops 10%. A 2x leveraged ETF drops 20%. * **Day 2**: The S&P 500 rises 11.11%, returning exactly to its starting price (0% net change). The 2x leveraged ETF rises 22.22%. Despite the underlying S&P 500 ending completely flat, the leveraged ETF has lost value: $$(1 - 0.20) \times (1 + 0.2222) = 0.80 \times 1.2222 = 0.9778 \text{ (a net loss of 2.22\%)}$$ This decay is **volatility drag**. When markets fluctuate heavily or trend downward, this daily erosion compounds, causing leveraged portfolios to decay far more than the index. To use leverage safely, we need a robust macro filter that allows us to exit leveraged exposure before volatility drag erodes our capital. ## The AlgorithmicFIRE Macro Stress Indicator (AF-MSI)™ Framework The AlgorithmicFIRE Macro Stress Indicator (AF-MSI)™ is a systematic, quantitative risk filter that monitors three key macroeconomic indicators, scoring from `0` (no active stress) to `3` (high stress): 1. **Term Spread Inversion**: The yield curve inverts, measured by a negative 10-Year minus 2-Year Treasury spread (`T10Y2Y` < 0). 2. **Credit Spread Elevation**: Corporate credit risk rises, measured by a rolling Z-score of the Moody's Baa Corporate Bond yield spread over Treasuries (`BAA10Y` Z-score > 1.5) calculated over a robust 756-day (3-year) historical baseline. 3. **Equity Volatility Spike**: Stock market volatility rises, measured by the CBOE Volatility Index rising above a baseline threshold (`VIX` > 25.0) sustained for at least 2 consecutive days (filtering out brief, single-day volatility noise). By counting how many of these warnings are active, the AF-MSI provides a systematic measure of macro stability. To prevent whipsawing, the composite score is smoothed using a 10-day rolling maximum filter. This ensures that when any of the three indicators fires, the portfolio immediately transitions to a risk-off state and remains there for a minimum 10-day cooldown period before re-leveraging is allowed. Below, we visualize the historical path of the S&P 500 (SPY) overlaid with the AF-MSI™ score (shaded in red when stress is active). Notice how the indicator triggers and remains in a risk-off state throughout major market dislocations (such as 2008 and 2020), while filtering out minor volatility spikes: ![SPY Adjusted Close vs. AlgorithmicFIRE Macro Stress Indicator (AF-MSI)™](msi_vs_spy.png) ### Analyzing AF-MSI Score Distribution during US Uptrends We evaluated daily FRED macro data from **2007 to 2026** (covering 4,751 trading days). When the US equity market is in a confirmed uptrend (our trend-following signal is ON), what does the macroeconomic stress environment look like? *(Note: Our active "Trading" style uses three different moving average models to identify trends. A "confirmed uptrend" simply means that at least one of these three models has triggered a buy signal on VTI, prompting the portfolio to hold stocks instead of cash.)* ![AF-MSI score distribution during VTI uptrends](msi_uptrend_distribution.png) * **AF-MSI = 0 (No Stress)**: **81.6%** of uptrend days. The macro environment is completely stable. * **AF-MSI = 1 (Mild Stress)**: **18.3%** of uptrend days. Typically triggered by an inverted yield curve or a minor credit/volatility spike while stocks are still rising. * **AF-MSI = 2 (Moderate Stress)**: **0.1%** of uptrend days. * **AF-MSI = 3 (Severe Stress)**: **0.0%** of uptrend days. Stock market uptrends occur in a stable macro environment 81.6% of the time. However, in 18.4% of cases, stocks continue to rise despite macro warning lights (such as an inverted yield curve or credit spread elevation). This is when our tactical overlay steps down from 2x leverage to 1x exposure. ## Case Study: Three-Fund Portfolio Tactical Leverage We simulated this tactical leverage overlay inside a standard **60/20/20 Three-Fund Portfolio**: * **60% US Equities**: [VTI](/report/VTI_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x Total US Stock Market) under a trend-following overlay. * **20% International Equities**: [VEA](/report/VEA_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x Developed Markets) under a trend-following overlay. * **20% Fixed Income**: [BND](/report/BND_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x Aggregate US Bond Market) under a trend-following overlay. We compared three strategies from **July 2007 to June 2026**: 1. **Passive Three-Fund Buy & Hold**: A static 60/20/20 allocation held through all market regimes. 2. **Standard Active Three-Fund (1x Baseline)**: Standard trend-following (which you can [model and simulate dynamically in the Custom Portfolio Builder](/custom-portfolio?p=VTI:ER_MMA:trading:60|VEA:ER_MMA:trading:20|BND:ER_MMA:trading:20)). Constituent sleeves hold their respective assets when the trend is positive, and transition to cash/yield when the trend is negative. 3. **AF-MSI-Enhanced Tactical Three-Fund**: The same trend-following portfolio, but with tactical leverage in the US equity sleeve. When the standard active model indicates to hold US equities (VTI): * If `AF-MSI == 0` on the previous day (no active stress), the US sleeve holds **[SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (2x S&P 500)**. * If `AF-MSI > 0` on the previous day (any stress warning), the US sleeve holds **[VTI](/report/VTI_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x S&P 500)**. To ensure strict real-world tradability and prevent look-ahead bias, all simulations incorporate: * **Lookahead-Free Signals**: Decisions are based on data available at the close of day T, and reallocations are executed at the open of day T+1 ("trigger today, trade tomorrow"). * **5 bps Slippage Penalty**: A 0.05% slippage penalty is applied to every sleeve reallocation trade. ### Performance Summary (2007–2026) The table below summarizes the inception-to-date metrics for each strategy: | Strategy / Portfolio | CAGR (%) | Sharpe Ratio | Max Drawdown (%) | Shifts / Year | | :--- | :---: | :---: | :---: | :---: | | **1. Passive Three-Fund Buy & Hold** | **8.66%** | **0.54** | **-46.92%** | — | | **2. Standard Active Three-Fund (1x Baseline)** | **7.38%** | **0.92** | **-15.24%** | — | | **3. AF-MSI-Enhanced with [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (Tactical 2x US)** | **9.58%** | **0.82** | **-19.68%** | **6.88** | ## Cumulative Growth Chart The performance chart below shows the growth of $1.00 (log scale) across the three portfolio options over the full 19-year aligned history: ![Three-Fund Portfolio MSI performance chart](three_fund_msi_performance.png) ## Key Insights and Trade-offs The results of this case study highlight how systematic overlays can create structural outperformance: 1. **Successful Alpha Generation**: By substituting [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (2x) for [VTI](/report/VTI_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x) only during low-stress periods, the AF-MSI-Enhanced portfolio boosted its CAGR from **7.38%** to **9.58%** (an absolute outperformance of **+220 bps** over the standard active 1x baseline, even beating the passive buy & hold's **8.66%**). 2. **Controlled Drawdown Risk**: By reverting back to [VTI](/report/VTI_STRATEGY_EXCESS_RETURN_MMA_trading.html) (1x) the moment macro stress indicators flash, the AF-MSI-Enhanced portfolio limited its max drawdown to **-19.68%**—a significant improvement over the passive buy & hold's **-46.92%**, though slightly higher than the standard active 1x baseline's **-15.24%**. 3. **Low Execution Friction**: Because the S&P 500 is less volatile than the Nasdaq-100, the tactical leverage signal is highly stable. The strategy averaged only **6.88 shifts per year** within the US sleeve, keeping transaction friction low. Any active strategy in a taxable account will incur short-term capital gains tax drag, however the drag is eliminated entirely when executed within tax-sheltered accounts like an IRA or 401(k). ## Addendum: Evaluating 3x Tactical Leverage (UPRO vs. SSO) While [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (2x) provides a significant return boost, some investors may wonder if a 3x leveraged ETF like [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (3x S&P 500) can offer even higher returns under the same AlgorithmicFIRE Macro Stress Indicator (AF-MSI)™ framework. Because [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html) was launched in June 2009, a head-to-head comparison must be run over an aligned period (**June 2009 to June 2026**). This post-crisis period was characterized by a long, historically strong bull market, meaning it excludes the extreme stress of the 2008 Global Financial Crisis. ### Performance Summary: Aligned Period (2009–2026) The table below shows the performance metrics for the three-fund portfolio using SSO (2x) and UPRO (3x) US equity sleeves over the aligned post-crisis period: | Strategy / Portfolio | CAGR (%) | Sharpe Ratio | Max Drawdown (%) | Shifts / Year | | :--- | :---: | :---: | :---: | :---: | | **1. Passive Three-Fund Buy & Hold** | **11.59%** | **0.83** | **-28.82%** | — | | **2. Standard Active Three-Fund (1x Baseline)** | **8.44%** | **1.06** | **-13.87%** | — | | **3. AF-MSI-Enhanced with [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (Tactical 2x US)** | **11.41%** | **0.96** | **-16.94%** | **6.89** | | **4. AF-MSI-Enhanced with [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (Tactical 3x US)** | **14.50%** | **0.89** | **-20.79%** | **6.89** | ### Cumulative Growth: 2x SSO vs. 3x UPRO The chart below displays the growth of $1.00 over the aligned period, demonstrating the compounding effect of the 3x tactical sleeve: ![Three-Fund Portfolio SSO vs UPRO performance chart](three_fund_msi_performance_upro.png) ### Key Takeaways from 3x Tactical Leverage * **Substantial Return Boost**: Implementing [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html) (3x) in the tactical US sleeve increases the portfolio CAGR to **14.50%** (a **+606 bps** absolute outperformance over the standard 1x baseline, and **+309 bps** over the tactical 2x [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html) version). * **Mitigated Crash Risk**: Under permanent 3x leverage, a crash can lead to a near-total loss of capital (e.g., [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html) fell over 76% from peak to trough in early 2020). However, under the AF-MSI-Enhanced framework, the portfolio's max drawdown was limited to **-20.79%**—only slightly worse than the 2x version (-16.94%) and comparable to the passive buy-and-hold (-28.82%). * **Risk/Reward Efficiency**: While the absolute CAGR is higher with [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html), the Sharpe ratio slightly drops from **0.96** (with [SSO](/report/SSO_STRATEGY_EXCESS_RETURN_MMA_trading.html)) to **0.89** (with [UPRO](/report/UPRO_STRATEGY_EXCESS_RETURN_MMA_trading.html)), reflecting the increased volatility and daily leverage drag during periods when the index is volatile but macro stress is not yet elevated enough to trigger an exit. ## Addendum: Evaluating the Core Indicator in Isolation (SPY vs. Cash) To understand how the AF-MSI™ functions purely as a quantitative risk filter—and to isolate its performance from the leveraged ETFs and multi-model trend-following strategies described above—we simulated a simple, binary model using the core indicator in its cleanest form from **2007 to 2026**: * **In the Market**: When the previous day's `AF-MSI` score is `0` (no active stress), the portfolio holds **SPY**. * **Risk-Off Sweep**: When the previous day's `AF-MSI` score is `1` or higher, the portfolio exits equities entirely and sweeps into **Cash** (earning the 3-Month U.S. Treasury yield, `DGS3MO`). The table below summarizes the performance metrics of this binary tactical simulation compared to a passive buy-and-hold SPY benchmark: | Strategy / Portfolio | CAGR (%) | Sharpe Ratio | Max Drawdown (%) | Calmar Ratio | Jensen's Alpha | Market Beta | Shifts / Year | | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | **Passive SPY Buy & Hold** | **10.82%** | **0.51** | **-55.19%** | **0.20** | — | **1.00** | — | | **AF-MSI Tactical SPY/Cash** | **7.62%** | **0.54** | **-20.23%** | **0.38** | **+274.9 bps** | **0.29** | **4.3** | ### Key Analytical Takeaways * **Drawdown Risk Mitigation**: By exiting the market when macro stress warning flags are raised, the tactical simulation limits its maximum drawdown to **-20.23%**—a **63.3% reduction** in downside risk compared to the passive benchmark's **-55.19%** drawdown during the 2008 Financial Crisis. * **Improved Risk-Adjusted Ratios**: Because the portfolio spends roughly 39.3% of its time in safe, interest-bearing Treasury cash, the raw CAGR decreases from 10.82% to 7.62%. However, it achieves this return with a fraction of the market exposure (a Beta of just **0.29**), resulting in a higher Sharpe ratio and nearly **doubling the Calmar ratio** (from 0.20 to 0.38). * **Positive Annualized Alpha**: The simulation generates **+274.9 bps** of annualized Jensen's Alpha. This positive alpha suggests that the macro filter is not simply creating drag, but is systematically avoiding high-risk, negative-expectation periods. * **Low Execution Friction**: With an average of only **4.3 transitions per year**, the model is stable and incurs negligible transaction costs. ### Macro-Based Filtering vs. Price-Based Trend-Following While the binary AF-MSI™ model demonstrates clear risk-reduction power, comparing it to a pure price-based trend-following model reveals a significant design tradeoff: 1. **Macro-Based Exit Drag**: Macro indicators are leading indicators by design. When credit spreads rise or the yield curve inverts, economic stress is building, but the stock market can (and often does) continue to rally for months or years. A binary macro filter like AF-MSI exits the market early, which creates a substantial performance drag (reducing CAGR from **10.82%** to **7.62%**). 2. **Price-Based Precision**: In contrast, a pure price-based trend-following strategy—such as the standard [AlgorithmicFIRE S&P 500 Excess Return MMA (Investing)](/report/SPY_STRATEGY_EXCESS_RETURN_MMA_investing.html) model—looks directly at actual price action. Because price is the ultimate consensus of all market inputs, it stays invested through the final stages of a macro-stressed bull run. Over its full historical range, the SPY Excess Return MMA (Investing) strategy achieved: * **11.2% CAGR** (matching the passive SPY benchmark's **11.2%** return exactly) * **-19.1% Maximum Drawdown** (slashing the benchmark's **-55.2%** crash risk by 65%) The trend-following model delivers identical drawdown protection to the macro filter, but **without any performance drag**. This performance gap is why the AlgorithmicFIRE ecosystem does not use macro indicators to time exits to cash. Price-based trend-following is a far superior tool for managing baseline equity exposure. Instead, we restrict the AF-MSI™ to a **tactical leverage overlay**: we use trend-following to decide whether to be in the market (1x), and we only lever up (to 2x SSO or 3x UPRO) when the macro coast is completely clear (`AF-MSI == 0`). ## Conclusion Tactical leverage using the AlgorithmicFIRE Macro Stress Indicator (AF-MSI)™ offers a systematic way to enhance returns in standard portfolios. By adding leverage only when the macro environment is completely clear of stress (`AF-MSI == 0`), investors can capture the outperformance of leveraged ETFs during long, stable bull markets, while quickly retreating to 1x exposure before volatility drag and severe market crashes damage their capital. This case study demonstrates that leverage does not have to be an all-or-nothing proposition. By combining trend-following indicators with macro stress data under a strict lookahead-free execution model, investors can build systematic portfolios that capture S&P 500 alpha while keeping risk firmly within acceptable limits. > **Allocation Warning**: This case study models a complete substitution of the 60% US equity sleeve to illustrate the mathematical limits and potential benefit of the AF-MSI framework. In practice, standard asset allocation principles suggest treating tactical leverage as a small "satellite" sleeve (e.g., 5% to 10% of your total portfolio) rather than applying it to your entire core US equity holding. > **Leveraged ETF Volatility & Gap Risk**: Leveraged ETFs are complex financial derivatives. Because they reset their leverage targets daily, they are highly vulnerable to volatility decay and long-term performance drag. Additionally, while broad index circuit breakers limit single-day intraday drops, severe multi-day drawdowns or overnight gap-down events (where the market opens substantially lower) can result in a rapid, permanent loss of principal. Take extreme caution, never leverage capital you cannot afford to lose, and consult a certified financial advisor before making investment decisions. --- ## Will Mega IPOs Crash the Market? Quantifying Forced Index Fund Selling URL: https://algorithmicfire.com/post/could-the-upcoming-mega-ipos-cause-substantive-price-drops-across-the-public-markets Published: 2026-05-18 Category: General Investing Abstract: Analyze the mathematical impact of SpaceX, OpenAI, and Anthropic IPOs. We calculate the ~$97B in forced index fund selling and market-cap dynamics using the Inelastic Markets Hypothesis. Date: 2026-05-18 Video: true Youtube_ID: https://youtu.be/tEPqHp77-2c Duration: PT7M30S SEO_Title: Will Mega IPOs Crash the Market? Quantifying Forced Index Fund Selling SEO_Description: Analyze the mathematical impact of SpaceX, OpenAI, and Anthropic IPOs. We calculate the ~$97B in forced index fund selling and market-cap dynamics using the Inelastic Markets Hypothesis. # Could the Upcoming Mega IPOs Cause Substantive Price Drops Across the Public Markets? ### Index funds will soon have to sell substantial holdings in order to raise the cash required to purchase shares in the upcoming IPOs of SpaceX, OpenAI, Anthropic, and others. This could cause a substantive price drop across the public markets. In this post we investigate the relative sizes of the various funds and the required cashflows to meet the demand. The 2026 IPO pipeline contains the largest combined private-to-public capital transition in market history by a wide margin. SpaceX alone is targeting a valuation that would make it one of the five largest companies on Earth the moment it begins trading. OpenAI and Anthropic are not far behind. When these companies go public, the mechanical plumbing of passive investing — the index funds that now control the majority of U.S. equity assets — will be forced to act. The question is whether that forced action creates a meaningful headwind for the stocks you already own. This is not a question of opinion. It is a question of arithmetic. Financial media has covered the individual pieces of this story — the scale of the SpaceX IPO, the mechanics of index rebalancing, and the academic research behind the Inelastic Markets Hypothesis — but as of this writing, nobody appears to have connected all three into a single quantitative analysis. The forced selling math, the compressed inclusion timelines, and the Gabaix-Koijen flow multiplier each tell part of the story. This post runs the numbers end-to-end. --- ## Why Index Funds Have to Sell If you own a total market index fund, an S&P 500 fund, or a Nasdaq-100 ETF, your fund manager does not choose what to buy. The index provider — S&P Dow Jones Indices, Nasdaq, FTSE Russell — dictates the composition. When a new company is added to the index, the fund **must** purchase shares of that company in proportion to its weight. And because index funds are fully invested (they hold near-zero cash), the only way to raise the capital for that purchase is to **sell existing holdings**. This is not a strategic decision. It is a structural obligation. A fund that fails to rebalance would begin to deviate from its benchmark — accumulating "tracking error" — which is the one thing an index fund is designed to never do. [^1] The mechanics work as follows: 1. **The index provider announces an addition** (typically 5 trading days before the effective date). [^1] 2. **Fund managers calculate the required weight** based on the new company's float-adjusted market capitalization. 3. **Managers sell a pro-rata slice of every existing holding** to raise the necessary cash. 4. **The new shares are purchased**, usually concentrated around the close of trading on the effective date. The result is a brief but intense period of **broad-based selling pressure** across hundreds of existing index constituents, paired with concentrated buying pressure in the newly added stock. When Tesla was added to the S&P 500 in December 2020, index funds needed to purchase an estimated **$78–$94 billion** of Tesla shares in a single session, generating roughly **$148 billion** in total trading volume on December 18th alone. [^2] [^3] That was one company. We are now looking at a pipeline of three to five, all much larger than Tesla was at the time of its IPO. --- ## The Scale of Passive Capital at Stake To understand the magnitude of the coming rebalancing, you first need to understand how much capital is structurally bound to follow these index rules. ### Assets Tracking the S&P 500 The S&P 500 is the most widely tracked index in the world. As of May 2026, the major funds alone represent trillions in structurally obligated capital: | Fund | Ticker | AUM (May 2026) | |:---|:---:|---:| | Vanguard 500 Index Fund (Admiral) | VFIAX | ~$1.40 Trillion | | Vanguard S&P 500 ETF | [VOO](/report/VOO_STRATEGY_EXCESS_RETURN_MMA_investing.html) | ~$956 Billion | | iShares Core S&P 500 ETF | [IVV](/report/IVV_STRATEGY_EXCESS_RETURN_MMA_investing.html) | ~$826 Billion | | SPDR S&P 500 ETF Trust | [SPY](/report/SPY_STRATEGY_EXCESS_RETURN_MMA_investing.html) | ~$770 Billion | | Fidelity 500 Index Fund | FXAIX | ~$792 Billion | **Sources:** Vanguard, iShares, State Street, Fidelity fund pages (May 2026). [^4] These are just the five largest individual vehicles. When you include all mutual funds, ETFs, managed mandates, and separately managed accounts that track the S&P 500, the total assets benchmarked to this single index exceed **$12 trillion**. [^4] The broader passive fund universe — covering all indexed mutual funds and ETFs in the U.S. — reached **$19.09 trillion** as of March 2026, according to the Investment Company Institute. This figure now **exceeds** the $16 trillion held in actively managed funds. [^5] ### Total S&P 500 Market Capitalization As of December 31, 2025, the aggregate market capitalization of the S&P 500 stood at approximately **$61.1 trillion**. [^4] With the top 10 holdings alone accounting for roughly **$25.3 trillion** by April 2026, the index is heavily concentrated at the top — which means any new mega-cap entrant will command a disproportionately large weight and therefore a disproportionately large forced purchase. --- ## The Market Cap of the Upcoming IPOs Here is what the current pipeline looks like, ranked by expected valuation: | Company | Sector | Est. Valuation | Est. Capital Raise | Status | |:---|:---|---:|---:|:---| | **SpaceX / SpaceXAI** | Aerospace / AI | $1.75T – $2.0T | $50B – $75B | S-1 filed (confidential, Apr 2026). Target listing: June 12, 2026. [^6] | | **OpenAI** | AI / Software | ~$852B (last round) | TBD | Restructured to PBC (Oct 2025). IPO speculated Q4 2026 or 2027. [^7] | | **Anthropic** | AI / Software | $380B (Series G, Feb 2026); secondary market ~$900B–$950B | ~$60B (est.) | No S-1 filed. Speculated Q4 2026. [^8] | | **Stripe** | Fintech | $159B (Feb 2026 tender offer) | N/A | No IPO announced. Leadership has said they are "in no rush." [^9] | | **Databricks** | Data / AI | $134B (Feb 2026 funding) | TBD | CEO says "IPO-ready" but timing fluid. [^10] | For the purposes of this analysis, we will focus on the three most imminent and largest: **SpaceX, OpenAI, and Anthropic**. Their combined expected valuations range from **$3.0 trillion to $3.8 trillion** — roughly **5–6% of the entire current S&P 500 market capitalization**. To put that in historical context: the largest IPO ever completed was Saudi Aramco's 2019 offering, which raised **$29.4 billion** (including the greenshoe option) at a valuation of approximately $1.7 trillion. [^11] Crucially, because Saudi Aramco is a state-owned enterprise listed on the local Saudi Tadawul exchange with strict foreign ownership limits, it was never added to major U.S. and global passive equity indices. Thus, its record IPO triggered zero forced passive rebalancing flows in common benchmark indices. In contrast, SpaceX is a U.S. company listing on a U.S. exchange, meaning it will trigger immediate and massive inclusion flows across the world's most heavily tracked passive funds. SpaceX alone is targeting a capital raise of **$50–$75 billion** — more than double the Aramco record. ![IPO Capital Raise Comparison](image_1.webp) --- ## Timing of IPOs: The Sequencing Problem The raw valuations are striking, but the actual market impact depends on four critical variables: float size, timing, rebalancing windows, and how these flows compare to normal daily liquidity. ### What Portion of Each Company's Shares Will Be Offered? Mega-cap tech IPOs typically offer between **10% and 20%** of total shares to the public. [^12] This is the "float" — the shares actually available for trading. Index weights are calculated on **float-adjusted** market capitalization, not total valuation. This is a crucial distinction. | Company | Total Valuation | Est. Float Value (10–15%) | Float-Adj. Market Cap | |:---|---:|---:|---:| | SpaceX | $2.0T | $200B – $300B | $200B – $300B | | OpenAI | $1.0T (target) | $100B – $150B | $100B – $150B | | Anthropic | $950B | $95B – $143B | $95B – $143B | | **Combined** | **~$3.95T** | **$395B – $593B** | **$395B – $593B** | You'll notice the float and float-adjusted market cap columns are identical. That's intentional — at IPO, the only publicly tradable shares *are* the float, so the two figures are the same by definition. However, this changes over time. As insider lock-up periods expire (typically 90–180 days post-IPO), additional shares enter the public market, increasing the float and therefore the float-adjusted market cap. This means the index weight — and the corresponding forced purchase by passive funds — **grows in stages** after the initial listing, creating multiple rounds of rebalancing pressure rather than a single event. SpaceX's dual-class share structure (Class A: 1 vote/share for public; Class B: 10–20 votes/share for Musk/insiders) means that Musk is expected to retain approximately **79% of voting power** even after the IPO. [^13] This strongly implies a relatively low float — likely closer to the 10–15% range — which constrains the initial index weight. ### Will They Happen at the Same Time? Not simultaneously, but the clustering is tight enough to matter: - **SpaceX**: Target listing **June 12, 2026**. This is the most concrete timeline. [^6] - **OpenAI**: Speculated **Q4 2026** or possibly 2027. No S-1 filed. [^7] - **Anthropic**: Speculated **Q4 2026**. Taking "IPO readiness" steps but no formal filing. [^8] If these IPOs are spaced 3–6 months apart, the market has time to absorb each one independently. The more compressed scenario — and the one worth modeling — is that OpenAI and Anthropic both target Q4 2026, creating a **compressed window** of forced rebalancing within a single quarter. ![2026-2027 Mega IPO Rebalancing Timeline](image_2.webp) ### Over What Period of Time Will Funds Rebalance? This depends on **which index** adds the company and **how quickly**: **Nasdaq-100 (Fast Entry Rule):** Effective May 1, 2026, Nasdaq implemented a "Fast Entry" rule that allows mega-cap IPOs to be evaluated for inclusion on their **7th trading day** and added after just **15 trading days**. [^14] To qualify, the company's total market capitalization must rank within the top 40 current Nasdaq-100 constituents. SpaceX, at a $2 trillion valuation, would trivially qualify. This means QQQ and other Nasdaq-100 tracking funds could be forced to buy within **three weeks** of the IPO. **S&P 500 (Seasoning Period Under Review):** The S&P 500 currently requires a **12-month seasoning period** before a newly public company is eligible for inclusion. [^15] However, S&P Dow Jones Indices opened a public consultation (closing **May 28, 2026**) to potentially reduce this to **6 months** and waive profitability requirements for megacap companies. If adopted, these changes could take effect as early as **June 8, 2026** — just four days before SpaceX's target listing date. [^16] This methodological shift reflects structural pressure on S&P to capture the growth of trillion-dollar private giants immediately upon listing, preventing faster-moving competitors like the Nasdaq-100 (with its Fast Entry rule) from monopolizing early index inflows. If the 6-month rule is adopted, SpaceX could be eligible for S&P 500 inclusion by **December 2026**. OpenAI and Anthropic, if they list in Q4, could be eligible by mid-2027. Each inclusion event would trigger a fresh wave of forced selling across the existing S&P 500 to fund the purchase. > **UPDATE 2026-06-05:** S&P has decided to retain the 12-month seasoning period. See the [official consultation results](https://press.spglobal.com/2026-06-04-S-P-Dow-Jones-Indices-Consultation-on-Treatment-of-MegaCap-Companies-Results) for more information. This does not materially impact the analysis in this post, only the timing of the index rebalancing. ### How Does the Required Selling Compare to Daily Trading Volume? This is the critical question. Forced selling only causes price drops if the volume of selling is **large relative to normal market liquidity**. **Daily Market Liquidity (Baseline):** - The U.S. equity market's average daily trading value (regular hours) reached a record **$1.04 trillion** in January 2026. [^17] - The SPY ETF alone trades approximately **$36 billion/day**. [^18] **Estimated Forced Selling for SpaceX S&P 500 Inclusion:** If SpaceX enters the S&P 500 at a float-adjusted market cap of $250 billion, its index weight would be approximately: > Weight = $250B / ($61.1T + $250B) ≈ 0.41% With $12 trillion tracking the S&P 500, the total forced purchase would be: > $12T × 0.41% = $49.2B That $49.2 billion must come from **selling existing holdings**. And this is a conservative estimate — it only captures S&P 500-tracking vehicles. SpaceX would simultaneously be added to the Nasdaq-100 (~$300B+ in QQQ alone), total US market indexes (VTI, ITOT), and MSCI USA, each of which would trigger additional forced buying and corresponding selling. The $19 trillion total passive universe referenced earlier includes all of these vehicles, but because we cannot precisely decompose the overlap, we use the $12T S&P 500 figure as a lower bound. If the S&P 500 rebalancing is concentrated into 1–3 trading days (as was the case with Tesla), this forced selling of existing holdings ($49.2 billion) represents **1.6–4.7%** of the entire market's average daily trading value. This is a massive, one-directional sell order dumped across the remaining constituents in a compressed window. Now extrapolate to a scenario where SpaceX, OpenAI, and Anthropic are all added within a 12-month window: | Company | Est. Float-Adj. Cap | S&P Weight | Forced Purchase ($12T base) | |:---|---:|---:|---:| | SpaceX | $250B | 0.41% | ~$49B | | OpenAI | $125B | 0.20% | ~$24B | | Anthropic | $120B | 0.20% | ~$24B | | **Total** | **$495B** | **0.81%** | **~$97B** | That is **$97 billion** in forced selling of existing S&P 500 holdings to fund the purchases. Because these additions are highly likely to occur in phases—both at each company's initial IPO listing and when insider lock-ups expire 90–180 days later—this passive flow will be spread across **3–6 discrete rebalancing events** over a 12-month window (or even more trading sessions if funds spread the execution of these massive flows over 1–2 days to minimize market impact). Each individual event is manageable relative to daily volume ($1T/day), but the cumulative effect — especially if front-running behavior amplifies the selling — could create a persistent headwind for the market's existing constituents. (Note: this calculation covers only S&P 500-tracking vehicles. Nasdaq-100, total-market, and international index funds would add to this figure — a point we return to in the liquidity section below.) --- ## The Amplification Factor: Inelastic Markets The analysis above treats every dollar of forced selling as exactly one dollar of market impact. But there is a well-established body of academic research — largely absent from the current IPO coverage — suggesting the actual impact is significantly larger. The **Inelastic Markets Hypothesis**, developed by Xavier Gabaix (Harvard) and Ralph Koijen (Chicago Booth) and published in 2021, argues that modern equity markets are far less elastic than traditional finance models assume. [^19] Their central finding: an exogenous flow of **$1 into the stock market increases aggregate market capitalization by approximately $5**. This is the "multiplier effect." The mechanism is straightforward. In a fully elastic market, when index funds sell $49 billion of existing holdings, active managers and hedge funds would step in to buy those shares at a small discount, absorbing the flow with minimal price impact. But Gabaix and Koijen show that most capital in the market is **not price-sensitive** — it is locked in retirement accounts, pension mandates, and other passive vehicles with rigid allocation rules. There simply are not enough active, contrarian buyers to absorb the flow without meaningful price concessions. [^19] [^20] Mike Green, a portfolio manager who has popularized this framework, extends the logic to its inverse: if passive inflows amplify prices on the way up, **passive outflows amplify them on the way down**. [^20] When index funds sell existing holdings to buy a newly added stock, they are creating a concentrated, non-discretionary sell flow in hundreds of companies simultaneously. The remaining active participants — who represent a shrinking share of total market capital — must absorb all of that selling. If they lack the capacity or willingness to do so, prices overshoot to the downside until a new buyer appears. ### What Does This Mean for the IPO Rebalancing? If the Gabaix-Koijen multiplier of ~5x holds, the ~$97 billion in cumulative forced selling across three mega-IPO inclusions would not reduce aggregate market capitalization by $97 billion. The implied impact would be closer to **$300–$500 billion** — spread across the existing S&P 500 constituents as a broad, diffuse headwind. To be clear: this is a **theoretical upper bound**, not a prediction. The multiplier is an aggregate estimate derived from historical flow data, and real-world outcomes depend heavily on market conditions, liquidity, and whether active managers choose to lean into or away from the selling. But the framework provides a useful lens: the raw dollar figures in the rebalancing tables above may understate the actual price impact by a factor of 3–5x. | Scenario | Forced Selling | Implied Market Cap Impact (5x) | |:---|---:|---:| | SpaceX alone | ~$49B | ~$245B | | All three (12-month window) | ~$97B | ~$485B | ![Forced Selling vs. Daily Market Liquidity](image_3.webp) It is worth examining that impact through two distinct lenses: **Lens 1 — The Stock Perspective (Market Cap Drag):** On the day of the SpaceX rebalance, the **$245 billion** in implied market capitalization displacement (5× multiplier on the $49B SpaceX-only S&P flow) represents a **0.40% aggregate drag** across the $61.1 trillion index. Cumulatively over the 12-month window, the total **$485 billion** displacement across all three listings represents a **0.80% aggregate drag**. In isolation, these single-day and cumulative figures sound modest — roughly equivalent to a single below-average trading day. **Lens 2 — The Flow Perspective (Liquidity Absorption):** The U.S. equity market processes roughly **$1 trillion per day** in total trading value. The cumulative forced selling of ~$97B across all three listings represents roughly **~10% of a single day's market volume** if compressed into one session. However, because these events are spread over a 12-month window, any single rebalancing session is much smaller. For example, the SpaceX rebalance represents **~$49B** of forced selling, or **~4.9%** of a single day's market volume. In isolation, those raw flow figures sound manageable. But the raw flow is not the right measure of impact. Applying the Gabaix-Koijen 5× multiplier, the implied market cap displacement from the SpaceX-only selling is ~$245B — the same figure established in Lens 1. This translates to **~$245B of market cap pressure** in that single rebalance session, or **~24% of a full day's total market volume** — all of it non-discretionary, one-directional, and price-insensitive. But that aggregate comparison understates the stress, because it uses the wrong denominator. To analyze this correctly, we must separate the **actual dollar flows** from the **resulting price drop**: 1. **Estimated Price Impact (The Multiplier):** Applying the Gabaix-Koijen 5× multiplier to the $49.2B of forced S&P 500 selling implies a final market capitalization drag of ~$246B (as detailed in Lens 1). 2. **Actual Transaction Flows (The Trading Volume):** But before that price adjustment settles, the actual shares must be sold in the market. This is the raw dollar amount of transactions ($49.2B from S&P 500 rebalancing alone) that must physically change hands in the order books. The relevant question for immediate liquidity stress is not what fraction of total market cap is displaced, but what fraction of each *individual stock's* daily trading volume is being hit with forced, one-sided selling in that single rebalancing session. *(Note: While SpaceX would also be added to the Nasdaq-100, MSCI USA, and total-market funds, index providers operate on completely different rebalancing schedules, meaning these inclusions will occur as discrete events on separate days. Furthermore, the S&P 500's ~$12 Trillion in passive AUM completely dwarfs the Nasdaq-100's passive base. For clarity, we focus our peak stress analysis solely on the massive S&P 500 rebalance day, recognizing that other indices will add smaller, independent waves of pressure.)* Using verified index weights (May 2026), we can calculate the forced selling of existing constituents on the **S&P 500 Rebalance Day** ($49.2B total flow), and see how the 5× multiplier amplifies this pressure relative to daily trading volume: | Company | S&P 500 Weight | S&P 500 Sell Flow | Daily Volume | S&P Raw % of ADV | S&P 5× Amplified | |:---|---:|---:|---:|---:|---:| | **[Nvidia (NVDA)](/report/NVDA_STRATEGY_EXCESS_RETURN_MMA_investing.html)** | 7.5% | $3.7B | ~$34.0B | ~11% | **~55%** | | **[Apple (AAPL)](/report/AAPL_STRATEGY_EXCESS_RETURN_MMA_investing.html)** | 6.0% | $3.0B | ~$14.4B | ~21% | **~105%** | | **[Alphabet (GOOGL)](/report/GOOG_STRATEGY_EXCESS_RETURN_MMA_investing.html)** | 4.0% | $2.0B | ~$10.0B | ~20% | **~100%** | | **[Microsoft (MSFT)](/report/MSFT_STRATEGY_EXCESS_RETURN_MMA_investing.html)** | 4.5% | $2.2B | ~$14.1B | ~16% | **~80%** | | **[Amazon (AMZN)](/report/AMZN_STRATEGY_EXCESS_RETURN_MMA_investing.html)** | 3.5% | $1.7B | ~$12.1B | ~14% | **~70%** | *Sources: S&P 500 weights from S&P Dow Jones Indices (May 2026); daily volumes from Robinhood/YCharts (May 2026).* Every one of these stocks faces **11–21% of its entire average daily trading volume** (ADV) in non-discretionary, one-directional selling on the S&P 500 rebalance day. When we apply the Gabaix-Koijen 5× multiplier to reflect market inelasticity, this forced selling behaves like a one-sided imbalance equal to **55% to 105% of their entire daily trading volume**. For example, on the S&P 500 rebalance day, **Apple (AAPL)** faces an S&P-only flow equal to **21% of its volume**, translating into a **105% amplified imbalance** under inelastic market conditions. On that same day, the mechanical flow out of **Alphabet (GOOGL)** represents **20% of its daily volume**—which behaves like a massive **100% imbalance**. And this happens simultaneously across all five highly-capitalized names. And this will happen to a lesser extent with the OpenAI and Anthropic IPOs as well. > The primary unknown is what will happen to stock prices, with large sales, in a market where much of the capital is passively managed. How can there be a bid when there is no buyer? --- ## Why These Estimates Are Conservative It is critical to note that the **$97 billion** in forced selling modeled in this analysis represents a **conservative baseline lower bound**, not a worst-case scenario: * **S&P 500-Centric Underestimation:** Our figures are built almost entirely on the $12 trillion benchmarking the S&P 500. They ignore the remainder of the **$19.1 trillion total passive equity universe**, including the Nasdaq-100 (QQQ), total U.S. market indexes (VTI, ITOT), MSCI USA, and global benchmarks. When these funds rebalance on their respective schedules, the actual forced selling of existing constituents will be significantly larger. * **Active Benchmarked Hugging:** Many "active" mutual funds and institutional managers are measured directly against the S&P 500 or Nasdaq-100. To avoid severe tracking error against these indices, these active managers are structurally pressured to replicate the index changes, forcing them to sell existing holdings to buy the IPOs. * **Minimum Initial Float (10–15%):** We modeled the absolute minimum initial public float. As insider lock-up periods expire (90–180 days post-IPO), subsequent share registrations and insider sales will expand the float-adjusted market capitalization, forcing passive funds to execute subsequent waves of buying (and additional selling of existing holdings). * **Exclusion of Other Trillion-Dollar Pipelines:** This model only covers SpaceX, OpenAI, and Anthropic. If other massive private giants waiting in the wings—such as Stripe ($159B) or Databricks ($134B)—listing in the same 12-month window are included, the mechanical selling pressure multiplies. --- ## The Bottom Line The upcoming mega-IPO cycle has no direct historical precedent in combined scale and velocity. The numbers suggest that while **no single IPO is likely to cause a broad market decline**, the cumulative effect of three or more trillion-dollar listings within a compressed timeframe creates a structural liquidity drain that passive investors should be aware of. **Key takeaways:** 1. **The mechanics are real.** Index funds **must** sell existing holdings to buy new additions. This is not speculation — it is structural plumbing. 2. **The scale exceeds all precedent.** The combined capital raise from SpaceX alone ($50–$75B) would more than double the current all-time IPO record (Saudi Aramco, $29.4B). Crucially, while Aramco was listed on a local foreign exchange and excluded from major passive benchmarks, SpaceX will list on a U.S. exchange and immediately enter major U.S. and global indices, triggering unprecedented passive rebalancing pressure. The combined forced rebalancing across all three companies could approach **$100 billion**. 3. **The timeline is compressed.** Rule changes at both Nasdaq (Fast Entry) and S&P (6-month seasoning consultation) are designed to accelerate inclusion. This concentrates the selling pressure into shorter windows. 4. **But the market is deep.** U.S. equity markets trade over **$1 trillion per day**. While concentrated rebalancing events will create short-term volatility — as they did with Tesla — the market has historically absorbed these shocks within days to weeks. 5. **The real risk is the second-order effect.** If large active managers — not just passive funds — simultaneously sell existing holdings to participate in these "must-own" IPOs, the selling pressure could be amplified beyond what the index mechanics alone would dictate. 6. **The "Index Drag" on passive holders.** While individual stock holders face concentrated downward pressure on their specific mega-cap holdings, index holders do not escape unscathed. Because passive funds are forced to buy the new megacap (SpaceX) at the exact moment of inclusion—typically when its share price is temporarily inflated by front-running active traders—while simultaneously selling their existing assets at a forced discount to fund the buy, index holders suffer from **"index inclusion drag"** (effectively selling low and buying high). For long-term investors, this is not a reason to change strategy. But it is a reason to understand the plumbing. The passive investing revolution has created a system where the addition of a single company to an index can force the mechanical sale of hundreds of others. When three of the most highly valued private companies ever enter that system within 12 months of each other, the pipes will be tested. --- ## References [^1]: S&P Dow Jones Indices, "S&P U.S. Indices Methodology," spglobal.com. Describes index rebalancing mechanics, announcement windows, and tracking error obligations. [^2]: Research Affiliates, "Tesla's S&P 500 Inclusion: A Case Study in Index Effects," researchaffiliates.com (2021). Documents the $78–$94B estimated forced purchase and 57% price run-up. [^3]: Los Angeles Times, "Tesla joins the S&P 500 in one of the biggest index reshuffles ever," latimes.com (Dec 2020). Reports 222 million shares traded and $148B in dollar volume. [^4]: Investment Company Institute (ICI), "2026 Investment Company Fact Book," ici.org; Vanguard, iShares, State Street, Fidelity fund pages (May 2026). Fund AUM figures and total S&P 500-benchmarked assets exceeding $12T. [^5]: Investment Company Institute, "Trends in Mutual Fund Investing, March 2026." Reports $19.09T in total U.S. indexed fund/ETF assets, surpassing $16T in active funds. [^6]: Multiple sources including Kiplinger, TradingKey, and Mashable (May 2026). SpaceX S-1 confidential filing (April 2026), target Nasdaq listing June 12, 2026, ticker SPCX, valuation $1.75T–$2T, capital raise $50B–$75B. [^7]: OpenAI corporate disclosures and financial reporting (March 2026). Post-money valuation of $852B. Restructured to Public Benefit Corporation October 2025. IPO speculated Q4 2026 or 2027. [^8]: Anthropic funding disclosures; Investing.com, Business Insider, PYMNTS (Feb–May 2026). Series G at $380B (Feb 2026). Secondary market activity at $900B–$950B. Estimated IPO raise of ~$60B. [^9]: Stripe tender offer (Feb 2026) at $159B valuation. Payments Dive, Motley Fool (2026). Leadership has stated they are "in no rush" to IPO. [^10]: Databricks $5B funding round (Feb 2026) at $134B valuation. Stock Analysis, CoinCodex (2026). [^11]: CBS News, Business Insider, G2.com. Saudi Aramco IPO (Dec 2019): $25.6B initial raise, $29.4B with greenshoe. Valuation ~$1.7T. [^12]: Nasdaq.com, Renaissance Capital. Historical analysis of mega-cap tech IPO float percentages, typically 10–20% of total equity. [^13]: SpaceXStock.com, KeepTrack.space, Responsible Investor (May 2026). Dual-class structure: Class A (1 vote), Class B (10–20 votes). Musk expected to retain ~79% voting power. [^14]: Nasdaq OMX Methodology Updates (effective May 1, 2026). "Fast Entry" rule: evaluation on 7th trading day, inclusion after 15 trading days for companies ranking in top 40 by total market cap. Ashurst, Kiplinger, Medium (2026). [^15]: S&P Global, "S&P U.S. Indices Methodology." Current 12-month seasoning requirement for S&P 500 eligibility. [^16]: Seeking Alpha, Substack, Reddit (May 2026). S&P consultation to reduce seasoning to 6 months, open until May 28, 2026, potential effective date June 8, 2026. [^17]: RBLT.com, citing consolidated U.S. equity market data. Average daily trading value (regular hours) reached record $1.04T in January 2026. [^18]: Robinhood, citing SPY average daily volume of ~48.93M shares at ~$734–$741/share = ~$36B/day (May 2026). [^19]: Xavier Gabaix and Ralph S.J. Koijen, "In Search of the Origins of Financial Fluctuations: The Inelastic Markets Hypothesis," NBER Working Paper 28967 (2021); published in the *Journal of Finance*. Estimates a price multiplier of ~5x for aggregate equity market flows. Available at nber.org. Also discussed in T. Rowe Price, "The Inelastic Markets Hypothesis," and AQR, "Gabaix and Koijen on Inelastic Markets." [^20]: Mike Green, portfolio manager and researcher. Extended the Gabaix-Koijen framework to argue that the growth of passive indexing has structurally reduced market elasticity, amplifying both inflows and outflows. Discussed in interviews on the Excess Returns Podcast, ETF Stream, and Invest Resolve. --- ## Visualizing Trend-Following Efficiency: Sharpe Ratio & Risk-Adjusted Returns URL: https://algorithmicfire.com/post/the-rise-above-visualizing-efficiency Published: 2026-05-06 Category: General Investing Abstract: Explore the efficiency frontier of trend-following strategies. Learn why the Sharpe ratio and risk-adjusted efficiency matter more than nominal returns for capital preservation. Date: 2026-05-06 Video: true Youtube_ID: https://youtu.be/sZj_PjHbYdY Duration: PT8M31S SEO_Title: Visualizing Trend-Following Efficiency: Sharpe Ratio & Risk-Adjusted Returns SEO_Description: Explore the efficiency frontier of trend-following strategies. Learn why the Sharpe ratio and risk-adjusted efficiency matter more than nominal returns for capital preservation. # The Rise Above: Visualizing the Efficiency of Trend-Following ### Is your portfolio achieving genuine alpha, or simply increasing volatility for marginal returns? We analyze the Selection Matrix and why vertical scaling (Efficiency) carries more weight than linear growth (CAGR). In our cornerstone post, “[Defending Your Savings Against Significant Downturns](/post/defending-your-savings-against-significant-downturns),” we established a sobering truth: even in modern markets, it is possible to lose close to 50% of your portfolio in a very short period of time and not have it recover in your retirement timeframe. Drawdowns in the range of 20-30% are certainly possible. These levels of volatility are difficult to stomach at any age but are particularly devastating for those in or near retirement. The key to a successful retirement is to ensure that your portfolio is resilient enough to withstand these shocks. As we detailed in our analysis of [Sequence of Returns Risk](/post/understanding-sequence-of-returns-risk), early losses combined with withdrawals "lock in" the damage, potentially depleting a portfolio before the market has a chance to recover. To navigate this, we need more than just a list of returns—we need a map of **efficiency**. --- ## Introducing the "Rise Above" Matrix The AlgorithmicFIRE [Model Portfolio Hub](/portfolios) features a powerful interactive tool: the **Selection Matrix**. This chart is designed to tell a three-dimensional story of how your money is actually working: * **X-Axis: Annual Return (CAGR %)** – This represents your "linear growth rate." It measures the raw compounded growth of your investment. As we noted in "[Average Return - It’s Not What You Think](/post/average-return-its-not-what-you-think)," CAGR is the only mathematically sound way to measure this growth. * **Y-Axis: Sharpe Ratio (Risk-Adjusted Efficiency)** – This is your "**Statistical Efficiency**." A higher Sharpe ratio indicates you are capturing more return per unit of volatility. * **Bubble Size: Max Drawdown (The "Pain")** – The size of the bubble represents the largest historical drop during the period modeled (5 years in this example). In a research-grade portfolio, we want this metric to be as low as possible. ### The Visual Metaphor: The Ascent ![The Selection Matrix showing the "Rise Above" effect](image_1.png) When you look at the matrix, the statistical impact of trend-following is illustrated by the **Trajectory Vector** (the dotted lines). Every model portfolio starts its journey at a "Baseline Point"—its underlying Buy-and-Hold benchmark. As you follow the dotted line to the solid "Strategy Point," you are witnessing a **Migration toward Efficiency**. You will notice two things happen simultaneously: 1. **Efficiency Gain**: The portfolio scales vertically, moving to a higher Sharpe ratio (improving return per unit of risk). 2. **Volatility Reduction**: The significant drawdown bubble of the benchmark physically contracts into a much smaller, tighter strategy bubble. This visual migration demonstrates the core thesis: you aren't just observing a static return—you are observing the active mitigation of risk in real-time. Even if a portfolio moves slightly to the left in terms of raw CAGR, the vertical gain in efficiency is what enables long-term survival. --- ## Up, Right, and the Lifecycle Shift Understanding how to move on this map is the key to a successful long-term strategy: 1. **Moving Right (Accumulation):** When you are in the accumulation phase, maximizing CAGR is the priority. As long as your Sharpe ratio (Efficiency) remains research-grade, you are essentially "purchasing" growth at a fair risk price. 2. **Moving UP (The Optimization Frontier):** Moving vertically indicates you are achieving a higher Sharpe ratio. You are capturing **more return per unit of risk.** This is the quantitative advantage of the AlgorithmicFIRE models. 3. **The Retirement Pivot (Up and Left):** As you transition from accumulation to depletion (retirement), your goal should progressively shift **Up and to the Left.** You want to maximize efficiency and capital preservation. You are intentionally trading the "noise" of high CAGR for the stability of a high Sharpe ratio and a minimal drawdown. --- ## The Heroes vs. The Warnings Not all bubbles on the matrix are created equal. In fact, some are there to serve as a cautionary tale. ### The Heroes: Absolute Return & Wealth Preservation The standout performers on our chart are models like **Absolute Return Core**. These sit in the "Up and Left" quadrant relative to the aggressive models. They demonstrate the efficiency migration: slashing historical drawdowns by a significant margin while only sacrificing a minor amount of CAGR. For a retiree, the vertical gain in efficiency is far more valuable than the horizontal distance they lose in returns. ### The Warning Zone: The Diminishing Returns of Leverage You will notice our most aggressive models (like **Aggressive Alpha Momentum**) sit further to the right, but their "altitude" (Sharpe ratio) is often no better than the S&P 500 benchmark. These models utilize leveraged ETFs like **TQQQ (3x Nasdaq-100)** and **QLD (2x Nasdaq-100)**. We include them not as recommendations, but as **warnings**. They illustrate a critical concept: **Volatility Decay**. A 3x leveraged fund does not provide 3x the CAGR over the long term. Instead, the "choppiness" of the market eats away at the returns. In these aggressive models, you are taking on massive complexity and visceral risk for only marginal CAGR gains. **Crucially, [CAGR alone does not guarantee success when withdrawals are being made](/post/average-return-its-not-what-you-think).** As we demonstrate in our [Safe Withdrawal Rate analysis](/post/understanding-safe-withdrawal-rate#investment-options-overlayed-on-the-45-swr-simulation), high-volatility assets like 100% stocks (and by extension, leveraged stocks) often fail in retirement scenarios despite their high returns, because the "[Sequence of Returns](/post/understanding-sequence-of-returns-risk)" risk overwhelms the growth. Entry into these strategies should never be taken lightly; for most investors, the quantitative advantage is found in the efficiency of the diversified models, not the raw power of the leveraged ones. --- ## Risk/Return Realities: The Vertical Drop in Pain If the Selection Matrix is the "Research View," our second analysis—**CAGR vs. Max Drawdown**—is the "Risk-Adjusted Reality" view. When you plot CAGR on the X-axis and Drawdown on the Y-axis, the trend-following advantage becomes undeniable. You see a clear **vertical scaling toward safety**. While the S&P 500 sits deep in the "Risk Zone" at -24% drawdown, our conservative models remain above the volatility, sitting at the top of the chart with drawdowns as low as -3% to -5%. This is why we have updated our interactive matrix to include the **Efficiency Migration** paths. We don't just want to show you where we are now; we want to show you the distance we've traveled away from the volatility of traditional buy-and-hold benchmarks. ![CAGR vs Max Drawdown showing the Vertical Ascent to Safety](image_2.png) Visualizing that vertical distance is the key analytical takeaway for most investors. It proves that you don't have to stay in the line of fire to remain active in the market. --- ## Conclusion: Choosing Your Optimal Altitude FIRE investing isn't about finding the fastest car; it's about building the one with the most robust failure modes. The Selection Matrix is your GPS. Whether you are seeking the "Efficiency Hero" of **Absolute Return Core** or the "Defensive Anchor" of **Wealth Preservation**, the goal is to find the optimal altitude for your current stage of life. ### Ready to find your position on the frontier? Explore the interactive **[Model Portfolio Hub](/portfolios)** today and see how our strategies rise above the market's inefficiency. --- ## Roth vs Traditional IRA: Full Lifecycle Tax & Withdrawal Analysis URL: https://algorithmicfire.com/post/roth-vs-traditional-ira-the-full-lifecycle-view Published: 2026-03-18 Category: Retirement Planning Abstract: Settle the Roth vs Traditional IRA debate. Read our full lifecycle tax analysis to see how tax bracket arbitrage, early withdrawals, and RMDs impact your lifetime taxes. Date: 2026-03-18 Video: true Youtube_ID: https://youtu.be/P_57OIPESEk Duration: PT8M29S SEO_Title: Roth vs Traditional IRA: Full Lifecycle Tax & Withdrawal Analysis SEO_Description: Settle the Roth vs Traditional IRA debate. Read our full lifecycle tax analysis to see how tax bracket arbitrage, early withdrawals, and RMDs impact your lifetime taxes. # Roth vs. Traditional IRA: A Full Lifecycle Analysis ### The single most common Roth vs. Traditional question is "which is better?" We modeled the entire wealth lifecycle—from your first dollar saved to your last dollar spent—across thousands of scenarios to find out. In our previous posts, we established two important ideas: 1. **[The Tax Rate Reality](/post/simplified-roth-versus-traditional-ira-conversations-may-be-costly)** - The conventional wisdom of comparing your current tax bracket to your expected bracket in retirement is incomplete. What matters is your current *marginal* rate vs. your future *effective* rate. Because of the standard deduction and progressive brackets, the effective rate in retirement is almost certainly lower than your marginal rate today. 2. **[The ACA Subsidy Opportunity](/post/considering-retiring-early-but-worried-about-healthcare-aca-costs)** - For early retirees, having Traditional IRA funds is a powerful tool. By engineering specific amounts of taxable income, you can qualify for Premium Tax Credits (ACA subsidies) that can eliminate healthcare costs entirely before Medicare kicks in at 65. Both of those analyses looked at narrower questions. Today, we put it all together. We modeled the complete wealth lifecycle—accumulation, conversion, and spending through death—across a range of incomes, savings rates, and retirement ages. > This post focuses on the relative performance of Traditional vs. Roth as the primary savings vehicle. It does not consider other factors such as estate planning, or the SEPP rules for early distribution. The key variable is which account type produces more sustainable annual retirement spending. --- ## The Moving Target of Tax Efficiency The standard rule of thumb is simple: **expect a higher tax bracket in retirement? Use a Roth. Expect a lower bracket? Use Traditional.** On the surface, avoiding a 22% tax today while paying only 15% on withdrawals in retirement seems like a clear win for Traditional. And it often is — but more factors are at play than a single bracket comparison suggests. **Factors that work in Roth's favor:** 1. **ACA Subsidies**: Higher Traditional withdrawals (MAGI) can destroy thousands of dollars in health insurance subsidies before age 65, effectively acting as a steep shadow tax. 2. **Social Security Taxation**: The "Tax Torpedo" — each extra dollar of Traditional income can make $0.85 of Social Security taxable, compounding the marginal rate. 3. **IRMAA Surcharges**: High MAGI can trigger Medicare Part B and Part D premium surcharges that act as steep, cliff-like cost penalties. 4. **No Lifetime RMDs**: Unlike Traditional IRAs, Roth IRAs do not have Required Minimum Distributions (RMDs) during the owner's lifetime, allowing tax-free compounding indefinitely. 5. **Estate Planning**: Heirs inherit Roth IRAs tax-free. Traditional IRA heirs must pay income taxes on inherited distributions, often during their own peak earning years due to the 10-year depletion rule. **Factors that work in Traditional's favor:** 1. **Accumulation-Phase Deductions**: The deduction directly reduces taxable income today, at your peak marginal rate. Roth contributions offer no comparable offset. 2. **Depletion-Phase Deductions**: In retirement, the standard deduction, senior add-on, and progressive brackets mean that the *effective* withdrawal rate is almost always lower than the *marginal* rate you paid during accumulation. 3. **Strategic Gap-Year Conversions**: Early retirees can have years with very low taxable income before Social Security begins. Traditional balances enable Roth conversions at the lowest possible tax cost during these windows. --- ## The Simulation Given this complexity, no single factor determines the outcome. The simulation below is an attempt to capture all of these effects simultaneously — not just the bracket comparison — and measure what actually matters: how much can you sustainably spend? We are modeling the entire lifecycle, from the first dollar saved to the last dollar spent, and include compounding returns, taxes (including Social Security taxation and IRMAA surcharges), ACA subsidies (when applicable), and RMDs. We are not aware of any factors that would significantly change the outcome of this analysis. We swept across three key dimensions: * **Initial Incomes**: $50,000, $75,000, $100,000, $150,000, $225,000, and $300,000 (household, married filing jointly). Note that these are assumed to be income **starting at age 35**. * **Retirement Ages**: 50, 55, 60, 65, and 70 * **Savings Rates**: 5%, 10%, 15%, and 20% of gross income Assumptions and parameters: * The simulation starts at age 35. * We used an average real income increase of 3.7% per year until retirement. (This is a real rate of return, meaning not including inflation.) * We used a 5% [real rate](/post/understanding-safe-withdrawal-rate#real-vs-nominal-returns) of return on investments. * Social Security is claimed at age 67 and is estimated based on final income. * Taxes are enforced both during accumulation and depletion: capital gains, social security, IRMAA, ACA subsidies, etc. * **Required Minimum Distributions (RMDs) are enforced** on Traditional IRA balances beginning at age 73. The retirement optimizer must take at least the IRS-mandated RMD each year, meaning the Roth account's compounding advantage (no lifetime RMDs) is fully reflected in the results. For each of these 120 scenarios, we calculated: 1. The maximum sustainable annual retirement spend when using an **optimized mix** of Traditional, Roth, and cash savings 2. The sustainable spend using **Traditional-only** savings 3. The sustainable spend using **Roth-only** savings * "Roth-only" in this context means that the accumulation model forces enough Traditional contributions each year to ensure that the household benefits from ACA subsidies for retirement scenarios that start before age 65. This is the "Traditional Bridge" described in our [ACA post](/post/considering-retiring-early-but-worried-about-healthcare-aca-costs). We did this to make the comparison as fair as possible, as we believe that most people who retire early will need to take advantage of ACA subsidies to some extent. 4. We are assuming money is saved in a 401K up to the annual limit, and then in a taxable brokerage account if the savings rate exceeds the 401K limit. 5. During retirement, we are running our [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator). Thus once in retirement, we are running our optimized withdrawal strategy to maximize the sustainable spend. --- ## Traditional IRA: A Near-Perfect Match for Most The chart below shows the efficiency loss for a pure Traditional IRA strategy. A value of -2% means you could spend 2% more by optimizing your account mix instead of going all-Traditional. > "Efficiency Loss" is how much spendable income you permanently leave on the table (as a percentage) by committing to a single account type vs. the optimized approach. ![Traditional Strategy Efficiency Loss](./image_1.png) The first thing to notice is the scale: most lines cluster between 0% and -5%. This tells us that a Traditional IRA strategy is remarkably close to the optimal outcome in most scenarios. However, the worst drag emerges at **higher savings rates (teal and green lines), particularly at retirement ages 65 and 70**. This is counterintuitive but makes sense: when you save aggressively in a Traditional account, you accumulate more pre-tax money than the standard deduction and low brackets can absorb efficiently. At that point, a small Roth allocation would have been the better tool, and the Traditional-only constraint costs you. For lower savings rates (red and blue lines), the Traditional account is often the near-perfect match for the optimizer. ### A Concrete Example For a household earning $150,000 and retiring at age 65 with a 5% savings rate: * **Traditional-only** sustainable spend: **$122,573/year** * **Optimized mix** sustainable spend: **$122,573/year** * **Efficiency Loss: 0%** — the Traditional strategy *is* the optimal strategy The reason becomes clear from the tax hurdle heatmap below: for this scenario the optimal hurdle rate is **0%** — meaning Traditional wins at any marginal rate. There is no threshold to cross. The standard deduction and low brackets on withdrawal absorb the balance so efficiently that a dollar saved in Traditional is always better than a dollar saved in Roth. --- ## Roth IRA: A Hidden Cost Most People Don't See Now look at the same analysis for a Roth-only strategy. ![Roth Strategy Efficiency Loss](./image_2.png) Across nearly every scenario, the Roth strategy underperforms. The pattern is consistent and telling: * **Lower savings rates (red and blue lines) see the biggest Roth penalty**, particularly at higher incomes and later retirement ages. * **Higher savings rates (teal and green lines) close the gap** somewhat, because accumulating more Roth savings eventually gives the optimizer enough to work with. ### A Concrete Example For the same household earning $150,000 and retiring at age 65 with a 5% savings rate: * **Roth-only** sustainable spend: **$113,828/year** * **Optimized mix** sustainable spend: **$122,573/year** * **Efficiency Loss: -7.7%** — over **$8,745 per year** left on the table That is real money. At a 30-year retirement, that gap compounds to over **$260,000** in total additional spending power. ### Why Is the Roth Penalty So Large? An important note on how the simulation works: even the "Roth only" baseline does not go 100% Roth. The accumulation model forces enough Traditional contributions each year to hit a minimum Traditional balance at retirement—exactly what is needed to generate the MAGI required to stay in the ACA subsidy band before Medicare at 65. This is the "Traditional Bridge" described in our [ACA post](/post/considering-retiring-early-but-worried-about-healthcare-aca-costs). (We did this to keep the Roth vs. Traditional comparison fair.) In other words: the simulation enforces a level playing field on ACA subsidies for both strategies. The gap you see in the Roth chart is purely the cost of pre-paying taxes at the wrong rate. The penalty comes entirely from a single source: 1. **The "Pre-Payment" Tax Cost**: Every dollar contributed to a Roth IRA was taxed at your current *marginal* rate (22–24% for most of the incomes we modeled). Every dollar contributed to a Traditional IRA is withdrawn at your future *effective* rate, which is lower. The post [Simplified Roth vs. Traditional IRA Conversations May Be Costly](/post/simplified-roth-versus-traditional-ira-conversations-may-be-costly) quantified this gap. For a $150,000 household, the marginal tax rate is 22%, while the effective rate in retirement could easily be under 15%. --- ## Where the Two Strategies Are Close It is important to note that in some scenarios the strategies converge. The table below identifies conditions where Traditional and Roth are within 1% of each other: | Scenario | Comments | |---|---| | Very early retirement (age 50) at all incomes | The hurdle is 0% for most age-50 cells — both strategies are near-equivalent because there is too little accumulation time for the tax arbitrage to create a large gap | | High savings rates (20%) at high income ($225k+) | The hurdle rises to 24%, meaning Traditional is still preferred for anyone paying 24%+ — but the gap narrows | | $300k income + 15–20% savings + ages 65–70 | The only scenarios where the hurdle reaches 32% — extreme savers at high income are the edge case where Roth makes partial sense | In short: Traditional dominates for the vast majority of scenarios. Only the highest-income, highest-saving households near standard retirement age face meaningful trade-offs. --- ## How Much Can You Sustainably Spend? The absolute numbers matter, not just the relative efficiency. Here is the maximum sustainable annual spend across all scenarios: ![Sustainable Spend](./image_3.png) This shows the upper bound for what each combination of income, savings rate, and retirement age can generate. A few observations: * Retiring at 70 vs. 50 with the same income and savings rate can double your sustainable spend—the compounding effect of additional years of savings is enormous. * The lines show only the optimized mix — the ceiling of what each income/savings-rate/age combination can achieve with the best possible account allocation. * Lower income levels at early retirement ages can end up in scenarios where even optimal strategies result in unsustainable retirement plans—a reminder that saving at all is always the first priority. --- ## The Portfolio at Retirement The optimizer's preferred starting balance at the point of retirement almost always includes a significant Traditional IRA. Here is the composition from the model: ![Portfolio Mix at Retirement](./image_4.png) The mix reflects two competing pressures: save enough in Traditional to use low-bracket and standard-deduction space efficiently, and save enough in Roth to supplement spending without generating excess MAGI that would trigger higher taxes or ACA subsidy loss. --- ## How the Optimizer Builds the Portfolio Abstract efficiency percentages are useful, but it helps to see *how* the optimizer actually behaves year by year. The chart below shows the contribution timeline for each income level, using a representative scenario (retirement at 60, 15% savings rate). Each stacked bar represents one year of savings: blue for Traditional, red for Roth, and green for Cash (taxable spillover once tax-advantaged limits are hit). The dashed black line is the actual marginal tax rate each year; the dotted red line is the optimal hurdle rate for that income. ![Career Contribution Timeline](./image_5.png) The triangle markers (▲) along the baseline indicate years where the accumulation model **forced Traditional contributions** to build the ACA bridge balance—ensuring there are enough Traditional funds to generate the MAGI needed to qualify for ACA subsidies during the 5-year gap between retirement and Medicare at age 65. A few patterns jump out: * **Lower incomes ($50k–$100k) favor Roth** — despite the headline being "Traditional wins." With a 12% hurdle, early career years at these incomes often fall *below* the threshold, making Roth the correct choice then. The triangles show the years where the optimizer was forced into Traditional anyway—to build exactly the ACA bridge balance needed to cover healthcare costs in the five years before Medicare. Outside of those forced years, Roth dominates. * **Middle incomes ($150k–$225k) go all-Traditional** with a 0% hurdle. At these incomes the marginal rate never drops below the threshold in any year, so Traditional wins unconditionally. No Roth, no bridge forcing needed—the Traditional balance alone is more than sufficient to generate the MAGI for ACA subsidies. * **High incomes ($225k–$300k) quickly overflow into taxable Cash**. The 401k contribution cap limits how much can go into any tax-advantaged account, so the green Cash (Spillover) bars grow rapidly. At $300k the 24% hurdle means some Roth is optimal in early years, visible as the brief red layer before the marginal rate climbs above the threshold. --- ## The Tax Hurdle: When Does Traditional Win? The heatmap below answers the most actionable question in this analysis: *For a specific scenario (income, retirement age, and savings rate), what is the minimum marginal tax rate at which a Traditional contribution beats a Roth contribution?* ![Optimal Tax Hurdle Rate](./image_6.png) The rule is simple: **If the current marginal tax rate is above the hurdle, contribute to Traditional; if it is below the hurdle, contribute to Roth. A hurdle of 0% means Traditional always wins; a hurdle of 100% would mean Roth always wins** A few patterns stand out: * **Low hurdle rates dominate**: **46% of all scenarios have a 0% hurdle** — Traditional wins at *any* marginal rate. Of the remaining scenarios, **82.5% have a hurdle of 22% or less**. If you are currently paying 22% in federal taxes, the data says Traditional is almost certainly the right choice. * **High hurdles are rare**: The only scenarios with a 32% hurdle are $300k income, 15–20% savings rate, retiring at 65 or 70. These are the edge cases where aggressive savers near standard retirement age have accumulated so much Traditional that some Roth would have been more efficient. * **Use this as your personal test**: Find your income panel and your planned retirement age. If your current marginal rate exceeds the number in that cell, Traditional is the right choice for your next dollar of savings. A **0%** means Traditional wins unconditionally. --- ## What Action Should You Take? The above is information to serve as a general guide. It would be highly unlikely that anyone falls onto any of the scenarios that we chose. Further it is impossible to know what your income, tax situation, and actual returns will be over the course of your accumulation phase. A reasonable alternative is to periodically use a calculator like the [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator) to run your own simulations. Project what you think your balances will be at retirement, run a few scenarios, and see what the calculator suggests. Then, over time, rebalance assets accordingly. Also be sure and verify your plans with a qualified tax and investment professional to ensure you've not missed anything. --- ## Takeaways * **Traditional is the stronger default**: For most middle-income households ($75k–$225k) with typical savings rates (5–15%), the Traditional IRA gets within 0–3% of the optimal outcome on its own. The Roth, by contrast, can underperform by 5–10%. * **The Roth penalty is largest at lower savings rates**: Against the optimized benchmark, Roth underperforms by 5–10% in most scenarios — purely from having pre-paid taxes at the wrong (marginal vs. effective) rate. * **The conventional wisdom is backwards for most people**: The standard advice of "Roth if you expect higher taxes in retirement" gets it wrong for most FIRE-path savers, because it ignores the *effective* vs. *marginal* distinction. In 46% of scenarios the hurdle rate is 0% — Traditional wins unconditionally. * **A hybrid approach is optimal, but Traditional-first is correct**: The optimizer almost always wants some Traditional funds. The question is only how much. Our [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator) can help you dial in your specific number. * **Tax regulations are fluid**: Tax laws change. What is optimal today may not be optimal tomorrow. It is important to periodically review your tax situation and adjust your savings strategy accordingly. Tax issues are complex. This post uses simulated results across many simplifying assumptions to identify broad patterns. Your personal situation—Social Security income, state taxes, pension income, and other factors—will affect your specific outcome. This is not tax advice. Please consult a tax professional before making decisions. --- ## ACA Subsidies in Early Retirement: How to Optimize MAGI & Lower Health Costs URL: https://algorithmicfire.com/post/considering-retiring-early-but-worried-about-healthcare-aca-costs Published: 2026-03-11 Category: Retirement Planning Abstract: Maximize your ACA Premium Tax Credits in early retirement. Learn how to strategically use Roth and Traditional IRA withdrawals to control MAGI and lower health insurance costs. Date: 2026-03-11 Video: true Youtube_ID: https://youtu.be/EssCNhm2J-c Duration: PT7M23S SEO_Title: ACA Subsidies in Early Retirement: How to Optimize MAGI & Lower Health Costs SEO_Description: Maximize your ACA Premium Tax Credits in early retirement. Learn how to strategically use Roth and Traditional IRA withdrawals to control MAGI and lower health insurance costs. # Considering retiring early, but worried about healthcare (ACA) costs? ### With some financial engineering, you can reduce (and possibly eliminate) the cost of ACA coverage. We will show you how to reduce (and possibly eliminate) the cost of ACA coverage by balancing your traditional and Roth IRA contributions and subsequent withdrawals. Doing so will allow you to generate specific amounts of income, which will allow you flexibility in managing your MAGI (Modified Adjusted Gross Income) to minimize your ACA costs. This is more complex than it seems, because the subsidies have both a floor and a ceiling that need to be avoided. --- ## The Problem ACA health insurance can be expensive. If you go to the ACA Marketplace and enter your information, you will see that the cost of coverage varies depending on your income. Unsubsidized premiums range from roughly $1000 to $1300 per month for a 60 year old. That is $12,000 to $15,600 per year. The key word in that last paragraph is "unsubsidized". There are ACA subsidies available to reduce the cost of coverage. The amount of subsidy you receive depends on your income. The lower your income, the higher your subsidy. The formal name for these subsidies is Premium Tax Credits (PTC). --- ## The Solution The key in all of this is to realize that you can control your MAGI by controlling how much you withdraw from your traditional IRA. You can then use cash or Roth IRA withdrawals to close the gap between your MAGI and the amount needed to fund your lifestyle. The key here being that cash and Roth IRA withdrawals do not count as income for MAGI purposes. (You've already paid tax on cash and Roth IRA withdrawals; there is no reporting.) We are going to use our **new** [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator) to show how this works. But first, we need to understand the cliffs that we need to avoid. --- ## The Cliffs There are two cliffs that you need to be aware of when it comes to ACA subsidies (a.k.a. Premium Tax Credits, or PTC). Both are based on the Federal Poverty Level (FPL). 1. The Medicaid Eligibility Cliff (100%-138% of FPL) - If you are eligible for Medicaid, you are not eligible for PTC. 2. The 400% FPL Cliff - If you are above 400% of FPL, you are not eligible for PTC. > For tax year 2025, the federal poverty level is $15,060 for a 1 person household, and $5380 for each additional person. This is for the 48 contiguous states; Alaska and Hawaii have slightly higher FPL. The reason there is a range for the Medicaid Eligibility Cliff is because some states have expanded Medicaid coverage, while others have not. (Medicaid coverage is determined by states, not the federal government.) So the federal government has set PTC eligibility based on a combination of Medicaid coverage eligibility and the federal poverty level. > It is important to note that the 400% FPL cliff is actually a cliff; there is no phase-out of coverage. For more details on PTC, see the [IRS Premium Tax Credit (PTC) Overview](https://www.irs.gov/credits-deductions/premium-tax-credit-ptc-overview) and [IRS Form 8962, Premium Tax Credit (PTC)](https://www.irs.gov/forms-pubs/about-form-8962). You will note that IRS Form 8962 only mentions the 100% FPL floor, because that is the federal legal minimum for Premium Tax Credit (PTC) eligibility. The IRS uses 100% FPL as the baseline because, federally, anyone between 100% and 400% FPL is technically "eligible" for tax credits. However, the law also says you cannot get a tax credit if you are eligible for Medicaid. And that limit, as described above, is 138% of FPL in states that have expanded Medicaid. --- ## Summary of PTC Eligibility ### For States WITHOUT Expanded Medicaid Coverage (AL,FL,GA,KS,MS,SC,TN,TX,WI,WY) * PTC available IF income is > 100% of FPL * Medicaid eligibility is typically based on categorical requirements—meaning you must fall into a specific group (like being a parent or having a disability) in addition to having an extremely low income. ### For States WITH Expanded Medicaid Coverage (states not listed above) * Medicaid eligible if income is <= 138% of FPL * PTC available IF income is > 138% of FPL * If you purchase ACA coverage with income <= 138% of FPL, you are not eligible for PTC and will pay full price. ### Summary Table: Who Pays for What? |Income Level|Non-Expansion States|Expansion States| |---|---|---| |< 100% FPL|Coverage Gap (No help)|Medicaid| |100% – 138% FPL|ACA w/PTC Subsidies|Medicaid| |> 138% FPL|ACA w/PTC Subsidies|ACA w/PTC Subsidies| |> 400% FPL|ACA w/No Subsidies|ACA w/No Subsidies| --- ## Case Studies Let's look at two examples to see how this works. In both cases we will pick account balances that are projected to just make it to their end of life. This was done to show exactly how money in only a traditional IRA compares to money in a combination of traditional and Roth IRAs. Returns are also assumed to be constant, which is not realistic, but it does allow us to isolate the impact of the ACA subsidies. [Sequence of returns risk](/post/understanding-sequence-of-returns-risk) is thus ignored and makes both cases more optimistic than they would be in reality. In both cases we will assume the following: * Retiring at current age of 60 * Target spend: $100,000 per year (this is total disposable income) * Filing status: Married Filing Jointly * Social security income of $80K starting at age 67 * [Real return](/post/understanding-safe-withdrawal-rate#real-return): 4% * State: CO (our model ignores state tax - the state is only important for considering Medicaid eligibility) * ACA premiums: $14,000 per year per person * FPL is $81,760 * Medicare base premium: $2,400 per year per person > Friction Cost - Analysis and charts below refer to "friction cost", which is the sum of federal tax paid and health care premiums paid minus PTC. ### Case 1 - Traditional IRA Only: $1.15M This is the baseline case, showing what you want to avoid. This chart was created using the [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator), with inputs shown above. (We disabled some optimizations from the model to generate this particular chart.) Key points: * The first 5 years, prior to being eligible for Medicare, the ACA premiums are $14,000 per year per person, or $28,000 per year total. * Total friction cost is $43,340 each year. > Because the only method to generate spending money is to withdraw from your Traditional IRA, and that is taxable income, this example shows MAGI well exceeds 400% of FPL. The result is that the couple is not eligible for any ACA subsidies. ![image_1.jpg](image_1.jpg) ### Case 2 - Traditional IRA: $140K, Roth IRA: $800K The only thing we will change for this example are the starting account balances. Now the couple has $140K in Traditional IRA and $800K in Roth IRA. Note that the $140K in the traditional IRA was chosen to be the minimum amount needed in order to generate the required MAGI to avoid the Medicaid cliff. Key points: * Prior to age 65, the couple is pulling just enough money from the traditional IRA to generate the MAGI needed to avoid the Medicaid cliff, and using Roth IRA withdrawals to make up the difference in spending needs. * For the first 5 years, **the couple is eligible for PTC that covers 100% of their ACA premiums.** * Total friction cost is $0; they are paying no federal tax and no ACA premiums. * At age 65, they are eligible for Medicare, and their frictional costs increase to $4,800 per year to cover Medicare premiums. ![image_2.jpg](image_2.jpg) --- ## Comparing the Two Cases At first glance, Case 2 looks much better than Case 1. But let's look at the total amount of money left at the end of the simulation. * Case 1: $66K in the traditional IRA and $24K in the Roth IRA. * Case 2: $72K in the Roth IRA. Given that the case 1 income is low enough that it is generally paying zero federal tax, this compares as follows: * Case 1: $90K in total. * Case 2: $72K in total. If the federal tax rate was higher we would need to discount the traditional IRA balance by unpaid taxes. But given the income, and current high levels of both standard deductions AND senior bonuses, there is no federal tax for case 1. ### Do These Cases Compare Apples to Apples? If we assume that the couple in case 2 is in the 22% marginal tax bracket, then saving $800K in the Roth IRA took $1,025,641 in pre-tax income. Thus the couple in case 2 spent about $1,165M ($1,025 + $140K in the traditional IRA) in pre-tax income to generate their balances, while the couple in case 1 spent $1.15M in pre-tax income to generate their balance. The difference is only about $15K in pre-tax income. > So these cases are pretty comparable. Each couple would have had about the same after tax income over the years. ### Who Wins? You might think that the couple in case 2 would be better off, but they are not. The total difference: couple 1 saved $15K less than couple 2, and ended up with $18K more in purchasing power at death, for a net difference of $33K in favor of couple 1. **The traditional IRA couple won?** > The reason is subtle - couple 1 funded their retirement with pre-tax dollars, then paid almost no income tax on their withdrawals, due to deductions. (That compares to couple 2, who paid federal income tax on their contributions, and thus started with a lower balance.) In the end, the difference between the two couples is negligible. **IF** the couple in case 2 were in a higher tax bracket, then the traditional IRA couple would have won. Conversely, if the couple in case 2 were in a lower tax bracket, then the Roth IRA couple would have won. > This result is specific to this example, and does not generally indicate that one type of IRA is better than the other. It is simply a result of the specific numbers used in this example. This highlights an important point regarding deductions: the standard deduction is currently (tax year 2025) $31.5K. Once age 65 and over, the senior bonus adds another $6K, and that is in addition to the senior deduction add-on of $1.5K. The net result is a total of $39K in deductions. * The bonus was part of legislation passed in 2025 and is scheduled to expire in 2029. But once in place, these deductions are often carried forward. * We largely covered this issue in our post [Simplified Roth Versus Traditional IRA Conversations May Be Costly](/post/simplified-roth-versus-traditional-ira-conversations-may-be-costly); see that post for more details. We will be writing a future post that explores more issues around traditional versus Roth IRA performance. In the meantime, try our [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator) to see how different account balances and withdrawal strategies affect your tax liability, PTC, and more. --- ## Actually - the Traditional IRA Couple Won We noted that in the above scenarios that we had disabled some model features for the original two cases. We wanted to start with a simple example, that might be both easier to understand, and show a mistake many people might make. That said, let's see what happens when we run the model with all the features enabled. ![image_3.jpg](image_3.jpg) In this case the optimizations result in the couple ending up with $298K in their traditional IRA and $88K in their Roth IRA at death. This compares to the $90K in total that they ended up with when the optimizations were not enabled. The difference (reducing the traditional IRA balance by the current federal tax rate of about 5%) is $280K in favor of the optimization enabled scenario. **The traditional IRA couple won** **What happened?** The optimizer was able to realize that by taking a large up-front withdrawal from the traditional IRA and converting that into the Roth IRA, it could take smaller distributions in later years, and optimize the PTC (ACA subsidies). --- ## The Caveats and Questions * With a traditional IRA, you can't start making withdrawals until age 59.5, or you will be subject to a 10% penalty. (This is not true for Roth IRAs.) So this strategy is ideal for someone who is retiring at or after age 59.5. * That said, there is an exception for [SEPP (substantially equal periodic payments)](https://www.irs.gov/retirement-plans/substantially-equal-periodic-payments#q2), but that is a complex topic that we will not be covering in this post. If you want to use this strategy earlier than age 59.5, you should learn about SEPP and consult with a tax professional. * With a Roth IRA you cannot withdraw **conversions** for 5 years, or you will be subject to a 10% penalty, unless you are 59.5 or older. (This is not true for contributions.) The model does implement this rule. That said, be careful when planning. If you are planning on using this strategy, you need to make sure that you don't need to access your converted funds for 5 years or until you reach age 59.5 or older. * You can also use this strategy while working to reduce health care costs, while you utilize your Roth IRA to boost your spendable income. This would work well for someone who saves a lot of money early in their career, and then moves into a lower paying position, starts their own business, or otherwise reduces their income. * You will need to be aware of capital gains on any transactions in your taxable accounts, and similarly aware of dividends or other income that you may receive. All of these impact your MAGI, and therefore your PTC/ACA subsidies. * You may trigger income from any of these sources, not just traditional IRA withdrawals, which was the focus of this post. If you have assets in taxable accounts, and generate capital gains and/or dividends, be sure to account for those in your MAGI. * Can this strategy be used to take a short career break? * Maybe - the issue is that PTC is determined by MAGI in the previous year. * If your break is for a full year, or your income such that during the part of the year you are working you can still manage your MAGI to be below 400% of FPL, then this strategy could work. * But if your MAGI for the first part of a calendar year is over 400% FPL, then you stop working until the end of that year, you will have no PTC in that year as you exceeded the 400% FPL threshold. * Again - consult a tax professional if you are considering this strategy. * The utility of calculators like ours is **not** to create a long term Roth conversion plan. The utility is to get a sense of how different account balances and withdrawal strategies affect your tax liability, PTC, and more. - That is because you need to have a rough idea how much frictional costs you will be subject to when in retirement, in order to plan how much you need to save. As we saw in the example above, the difference between no strategy, and a more optimal strategy, can be a significant amount of money. --- ## Don't hate the player, hate the game There is a moral dilemma that we feel needs addressed. We've discussed how we can use the tax code to our advantage. But is it right to do so? In discussions with friends and family, the first reaction is often "is it right for people with $1M+ in assets to be getting subsidies for healthcare?". In fact, that was our first reaction too; "just because you can, doesn't mean you should" is what came to mind. But the system we have allows for this, as well as many other things that we may not agree with. I.E. allowing corporations to shift profits to low tax jurisdictions in other countries, or allowing very rich people to avoid taxes altogether by borrowing against their assets. Ultimately, we have to decide what is right for us, and what we are comfortable with. For us, we think the right answer is: use the tax code to our best advantage, and vote for politicians who will make changes we agree with. "Don't hate the player, hate the game" is a common saying that applies here. --- ## Takeaways * ACA subsidies can significantly reduce the amount you pay for healthcare. * Having money in both a traditional IRA and Roth IRA allows you control over your MAGI, which can be used to optimize your ACA subsidies. * You can use our [Traditional IRA Withdrawal and Roth Conversion Calculator](/calculators#traditional-ira-withdrawal-and-roth-conversion-calculator) to see how different account balances and withdrawal strategies affect your tax liability, PTC, and more. (But to get the full benefit of the calculator, you need to use the multi-year lookahead optimization.) * Tax issues are complex, and frequently change. * The subsidies could go away at any time. * The standard deduction could change. * The senior bonus could change. Tax issues are complex. This post uses many simplifications and assumptions to make the argument clear regarding how MAGI can be controlled to optimize ACA subsidies. This post is meant to give you some starting information and help you understand the tax issues involved. But your personal situation will not be the same as our hypothetical married couple. You need to understand your own personal situation before making any decisions. This post is not tax advice. Please consult a tax professional before making any decisions. --- ## Protecting Your Portfolio with Put Options: A Retirement Hedge Strategy URL: https://algorithmicfire.com/post/buying-insurance-with-put-options Published: 2026-01-25 Category: General Investing Abstract: Learn how FIRE investors use put options to hedge against market crashes. Includes a worked example of insuring your S&P 500 holdings and a break-even calculator. Date: 2026-01-25 Video: true Youtube_ID: https://youtu.be/X-rGusvj_Ik Duration: PT6M3S SEO_Title: Protecting Your Portfolio with Put Options: A Retirement Hedge Strategy SEO_Description: Learn how FIRE investors use put options to hedge against market crashes. Includes a worked example of insuring your S&P 500 holdings and a break-even calculator. # Buying Insurance for Your Portfolio: Put Options vs. Trend Following ### Trend following isn't the only way to protect against downturns. We compare trend following to the "guaranteed" protection of put options, and calculate the true cost of that certainty using. In a [previous post](/post/defending-your-savings-against-significant-downturns), we explored trend following as a mechanism to defend your savings against prolonged market stagnation. We showed how a rules-based system could help you step aside during major crashes (like 2000 or 2008) while staying invested during bull markets. But trend following has a hidden cost: **whipsaw**. Since trend following relies on lagging indicators (like moving averages), it will always be late to the exit and late to the re-entry. In choppy markets, you might sell at the bottom of a dip only to buy back higher, slowly bleeding capital while the market goes nowhere. For some investors, this uncertainty—"will the algorithm work this time?"—is stressful. What if you could just *guarantee* that your portfolio won't drop more than a certain amount? You can. It's called a **Put Option**. --- ## What is a Put Option? Think of a Put Option as **term life insurance** for your stocks. * You pay a **premium** upfront (just like your insurance bill). * In exchange, the insurance company (the option seller) guarantees to buy your stocks from you at a set price (the **strike price**) for a set period (expiration). * If the market crashes below that strike price, you are protected dollar-for-dollar. * If the market goes up, you only lose the premium you paid. Crucially, unlike trend following, **there is no "lag".** The protection is contractual and instant. > Options are available on a variety of securities. We will be using SPY (an S&P 500 index ETF) as our example. Pricing, liquidity, and availability will vary based on the security you choose. Do your own research before making a decision to trade options on ANY security. ### Put Options: The Technical Definition * A put option is a contract that gives the holder the right, but not the obligation, to sell an underlying asset at a specified price (the strike price) on or before a certain date (the expiration date). The seller of the put option receives a premium from the buyer in exchange for taking on the obligation to buy the asset if the option is exercised. --- ## The Cost of Certainty: A Real World Example Let's look at what it actually costs to insure a portfolio of the S&P 500, using the ETF (Exchange Traded Fund) [SPY](/report/SPY_STRATEGY_EXCESS_RETURN_MMA_investing.html). Suppose you have 300 shares of SPY ($206,700 value) and you want to ensure that—no matter what happens in the economy—you cannot lose more than **30%** (relative to the current price of $689) over the next year. Here is the math: * **Current Price of SPY**: $689 (2026-01-25) * **Your Position**: 300 shares ($206,700 value) * **Protection Goal**: Cap losses at 30%. You want to be able to sell your shares for at least **$480** (~ $689 - 30%). To achieve this, you buy **3 Put Option Contracts** with a strike price of $480 that expire in about 1 year (e.g., Jan 15, 2027).(Note that options contracts are for 100 shares each, so we need to buy 3 contracts to cover 300 shares.) ### The Cost Calculation Options are priced based on volatility and time. For a 1-year contract protecting against a crash that takes the price of SPY to $480 or less (called "Out of the Money", or OTM), the market charges a premium. * **Strike Price**: $480 (approx 30% OTM) * **Option Premium**: Estimated at **$6.80** per share. Total cost to insure your 300 shares: $$ 300 \text{ shares} \times \$6.80 = \$2,040.00 $$ ### As a Percentage of Your Portfolio $$ \frac{\$2,040.00 \text{ (Cost)}}{\$206,700 \text{ (Portfolio Value)}} = \mathbf{0.99\%} $$ In this scenario, you are paying roughly **1% per year** to guarantee that you can, during the next year, be assured that you can sell your shares for market price or $480 (whichever is higher). * If the SPY drops to $470? **You have the right to sell your shares for $480** * If the SPY drops to $300? **You have the right to sell your shares for $480** * If the SPY goes up to $900? **You can sell your shares for $900, or continue holding them.** Either way, your options cost 1% of the portfolio, and that money is gone. > Different levels of protection and/or different time horizons will cost different amounts. I.E. to protect against a 20% loss for one year, instead of the 30% loss protection for one year in this example, the premiums would raise the cost to about 2% of your portfolio. > The cost of options is not fixed. It varies based on market conditions, including volatility, interest rates, and the time to expiration. The prices quoted above are estimates based on current market conditions. --- ## Trend Following vs. Put Options This is a false choice. You can use both. The different strategies serve different purposes. * Based on our data, trend following works quite well on bonds. + Bonds are a good candidate for trend following because they are less volatile than stocks, and they are less sensitive to market sentiment. * Trend following also works well on stock ETFs, particularly when used in a tax-deferred account. + Stock ETFs are less volatile than individual stocks. The ETF is a basket of stocks, thus the ETF filters out some of the volatility of the individual stocks. * Trend following works less well on individual stocks. It works better on mature stocks that trade on traditional valuation measures, and less well on meme-type stocks that trade on sentiment and hype. * Trend following also does not work in fast moving markets, and is thus subject to the risk of major market or geopolitical events. * Put options are a guarantee, with a known but fixed cost. Put options are only available as contracts on 100 shares each. The positions you cover are probably not in integer multiples of 100. If you use put options to hedge part of a position, you can use trend following to hedge the rest of the position. --- ## Some Important Considerations * All price quotes above are nominal, and were approximate based on the date of writing this post. * The potential loss is based on the put option's strike price. The loss is not a percent of your portfolio. + If SPY increases in value to $960 before dropping below the strike price of $480, the loss from peak to strike price is 50%. * There are additional costs not mentioned above, such as: commissions, bid/ask spread, the cost to close an in-the-money option, etc. --- ## Conclusion: Insurance vs. Discipline This 1% "tax" on your returns is the price of certainty. * **Put Options** provide a hard floor. You sleep well at night knowing exactly what your worst-case scenario is. The downside is that this cost is **guaranteed** every single year, whether the market crashes or not. Over a decade, a 1% annual drag significantly reduces your compounding. * **Trend Following** aims to provide similar protection essentially for "free" (by simply moving to cash), but it charges you in **uncertainty** and **false alarms**. There is no free lunch in investing. You explicitly pay the option seller for insurance, or you implicitly pay the market in whipsaws and attention. The choice depends on which cost you are more willing to bear. >This post is not meant to be a primer on options trading, but instead to highlight the trade-off between uncertainty and cost, and to demonstrate one method to protect your portfolio. Anyone interested in trading options is going to need to consult a professional financial advisor and do their own research. --- ## The Roth vs Traditional IRA Trap: Marginal vs Effective Tax Rates URL: https://algorithmicfire.com/post/simplified-roth-versus-traditional-ira-conversations-may-be-costly Published: 2026-01-24 Category: Retirement Planning Abstract: Why standard Roth vs Traditional advice is often wrong. Discover why comparing current and future marginal tax brackets is flawed, and how to use effective tax rates to plan. Date: 2026-01-24 Video: true Youtube_ID: https://youtu.be/Dpdze-T409I Duration: PT7M32S SEO_Title: The Roth vs Traditional IRA Trap: Marginal vs Effective Tax Rates SEO_Description: Why standard Roth vs Traditional advice is often wrong. Discover why comparing current and future marginal tax brackets is flawed, and how to use effective tax rates to plan. # Simplified Roth Versus Traditional IRA Conversations May Be Costly ### The discussion is frequently reduced to comparing your current tax bracket to your expected tax bracket in retirement. While simple, this comparison is incomplete. The core decision between a Roth and Traditional IRA hinges on comparing your current marginal tax rate with your expected future **effective** tax rate. Your marginal tax rate matters for savings, as each dollar saved in a traditional IRA is sheltered from your current marginal tax rate. But during retirement, what matters is the effective tax rate. Given the increases in the standard deduction for tax year 2018, your effective tax rate is likely lower than you are assuming when comparing the two options. This makes the Roth IRA more attractive than it should. > This post focuses on the tax rate difference on withdrawals between Roth vs Traditional IRAs. It does not consider other factors such as estate planning, Required Minimum Distributions (RMDs), loans, or other considerations not related to the tax rate difference on withdrawals of the two options. --- ## The Simple Comparison Before we get into the details of our argument, let's look at a typical simple comparison of Roth vs. Traditional IRAs. Assumptions: 25% tax rate now and in retirement. You have $7,500 cash in hand to invest. |Step|Roth IRA|Traditional IRA| |---|---|---| |1. Invest|You put the $7,500 directly into a Roth.|You put $10,000 into a Traditional IRA. (This "costs" you $7,500 because your tax bill is reduced by $2,500).| |2. Growth|Your $7,500 doubles to $15,000.|Your $10,000 doubles to $20,000.| |3. Tax|You withdraw $15,000 tax-free.|You withdraw $20,000 and pay 25% tax ($5,000). You keep $15,000.| |Result|$15,000 Spendable|$15,000 Spendable| In a simple example like this, the two options are equivalent. As long as the current and future tax rates are the same, it does not matter which option you choose. It is your assumption of current vs future tax rates that is the decision maker Historically, personal exemptions and standard deductions were lower than they are today. Further, many people would work late in life, and have Social Security, a pension, or both. This simple math worked reasonably well. However, today's reality is more complex given large standard deductions, the lack of pensions, and the desire of the FIRE community to retire early (prior to any Social Security). With no other income sources, the difference between marginal and effective tax rates is much more pronounced. --- ## U.S. Taxes - A Primer on Marginal and Effective Tax Rates >In the U.S. tax system, there are different tax brackets depending on filing status: married filing jointly (MFJ), married filing separately (MFS), head of household (HOH), and single (S). Each filing status has its own tax brackets. For the rest of this article we will focus on single filers, and married filing jointly, as they are the most common filing statuses. The general concepts apply to all filing statuses. The U.S. tax system is a progressive tax system, meaning that the tax rate increases as the taxable income increases. People frequently call the highest rate of tax they pay on income their "tax bracket", but this is not accurate. The tax bracket is the range of taxable income that is subject to a specific tax rate. * **Marginal tax rate** - The tax rate a person pays on the next dollar of income. It is more accurate for a person to state their "marginal tax rate", which is the highest rate of tax they pay on income. * **Effective tax rate** - The effective, or average, tax rate paid on taxable income. It is the total tax paid divided by the taxable income. In summary, the marginal tax rate is the tax rate a person pays on the next dollar of income, while the effective tax rate is the average tax rate paid on taxable income. Since the tax system is progressive (made up by paying sequentially higher percentages of income as income increases), the marginal tax rate is always higher than the effective tax rate. ### Standard Deduction Another concept to understand is the standard deduction. The standard deduction is a fixed amount of taxable income that is not taxed. For tax year 2025 the standard deduction is $15,000 for a single filer and $30,000 for a married filing jointly. This means a single filer reduces income by $15,000, and a married filing jointly reduces income by $30,000, before calculating their tax liability. The standard deduction has the effect of reducing effective tax rates. I.E. The 24% marginal tax bracket starts at $103,350 for a single filer, but that $103,350 is after reducing your income by the $15,000 standard deduction. So you would need to earn $118,350 to be in the 24% marginal tax bracket. ![image_1.jpg](./image_1.jpg) The tables above show tax year 2025 tax brackets, marginal tax rates, and effective tax rates for joint and single filers. (These rates were taken from [Congress.gov](https://www.congress.gov/crs-product/RL34498)) The marginal rate is the value in the table just prior to "of the amount over". The effective tax rates are shown for all taxable incomes up to $626,350 (single filer) and 751,600 (married filing jointly). > Takeaway: **The effective tax rate is between 37% and 84% of the marginal tax rate** for incomes up to $626,350 (single filer) and 751,600 (married filing jointly). (As income goes to infinity, the effective tax rate approaches 100% of the marginal tax rate.) ### Example - Single Filer, 2025 Tax Year Let's look at an example of how to calculate the marginal and effective tax rates for a single filer with taxable income of $115,000. First, calculate Adjusted Gross Income (AGI): $115,000 - $15,000 = $100,000 Next, find the marginal tax rate. In this case, $100,000 is "over $48,475 to $103,350", and thus the marginal tax rate is 22%. Calculate Tax: $5,578.5 + 22% of ($100,000 - $48,475) = $16,914 **The marginal tax rate is 22%, while the effective tax rate is 14.7%, calculated as: $16,914 / $115,000.** --- ## Why Effective Tax Rate Matters for Retirement The core argument is that the tradeoff is between paying your marginal tax rate now on money that goes into a Roth IRA, OR paying no tax now on money that goes into a Traditional IRA and paying your effective tax rate in retirement. * Savings (Now): Every dollar put into a traditional IRA reduces your taxable income from the "top-down," meaning you save at your highest current marginal bracket. * Withdrawals (Future): When you withdraw from a traditional IRA in retirement, those dollars fill your future tax brackets from the "bottom-up." The first several thousand dollars are untaxed due to the standard deduction, and the next portions are taxed at the lowest rates (e.g., 10% or 12%). * The "Effective" Reality: Because your future dollars benefit from these lower tiers, the "cost" to withdraw those funds is indeed your effective tax rate on those specific withdrawals, which is significantly lower than your current marginal rate. Let's assume this hypothetical single filer saved enough to have the same income in retirement as they did when saving ($115,000). (We always use [real dollars](/post/understanding-safe-withdrawal-rate#real-return); inflation adjusted to keep purchasing power constant.) Assuming a withdrawal rate of 5%, this single filer would need to have saved $2,300,000. > Given the same income in retirement as during savings, our hypothetical single filer can either pay a 22% rate on their savings now and 0% tax on withdrawals in retirement (Roth IRA), or pay no tax now and 14.7% tax on withdrawals in retirement (Traditional IRA). Clearly, paying 14.7% tax is better than paying 22% tax. **For this example, an income of $274,637 would be required in order to pay the same effective tax in retirement as the marginal rate during savings**. ### Could Our Hypothetical Single Filer Save Enough to Have Retirement Income of $115,000? Assuming a withdrawal rate of 5%, our hypothetical single filer would need to have saved $2,300,000 to generate $115,000 in retirement income. ($2,300,000 * 5% = $115,000) * To have $2.3M in retirement would require saving roughly $21,000 per year, increasing savings at 3% per year (real - above inflation), for 30 years, and assuming 7% real returns on savings. * **For someone with $115,000 income, that savings is probably unrealistically high.** * If your thinking that savings is reasonable because "I'll be making more in the future and saving will be easier", then you need to read our [post on that subject](/post/its-ok-to-put-off-retirement-savings-until-youre-older-its-easier-then). * To have $274K of taxable income in retirement, our hypothetical single filer would need to save $4.5M. (Total income - Social Security benefit = $274,000 - $48,216 = $225,784. At a 5% withdrawal rate, $225,784 / 5% = $4,515,680). The annual savings required would be about $40K, which is entirely unrealistic for someone with $115K of income. ### Would Social Security Fill the Lower Buckets? For 2025 the maximum Social Security benefit for someone claiming their benefit when reaching full retirement is $48,216. For joint filers, where only one spouse worked, the maximum benefit, claimed at full retirement age, is $72,234. * Adding $48K to our hypothetical single filer's $115K retirement income results in total income of $163K; well below the $274K needed to pay the same effective tax in retirement as the marginal rate during savings. ### The Problem with the "Effective Tax Rate" Argument The potential flaw in this argument was mentioned in the [The Simple Comparison](#the-simple-comparison) section above. This argument assumes your taxable income in retirement will all be coming from your Traditional IRA. However, if you have a pension, Social Security, or other sources of income in retirement, those will boost your income. Your Traditional IRA withdrawals will be taxed at the marginal tax rate after those other sources of income are accounted for. Social Security alone will not increase the taxable income enough to offset the lower effective tax rate. **But if you expect to have a pension, a significant inheritance, or other sources of income in retirement, then the effective tax rate argument may not hold.** --- ## Will Taxes Go Up or Down in the Future? Higher future personal income tax rates are also possible, and those favor a Roth IRA. But for decades the supposition has been that personal income tax rates will go up in the future. So let's look at how they've changed in recent history. ![image_2.jpg](./image_2.png) ![image_3.jpg](./image_3.png) The charts above show the effective personal income tax rate, adjusted for inflation, for single and joint filers from 1988 to 2025. Note that effective tax rates have been relatively stable over this period. If anything, rates for incomes over $100,000 have declined over this period. (Contour lines, showing constant effective tax rates, are shown in black and generally only move upward, indicating it takes more income to achieve the same effective tax rate over time.) It is important to keep in mind that the government can also raise revenue from: corporate income taxes, payroll taxes, estate taxes, tariffs, and other sources of revenue. Raising personal income taxes is not the only way to raise revenue. --- ## Takeaways * The effective tax rate in retirement is what you need to compare to the marginal tax rate during savings. * The effective tax rate is lower, sometimes substantially lower, than the marginal tax rate. * It may be difficult to save enough to make the effective tax rate in retirement equal to the marginal tax rate during savings. In which case, the Traditional IRA is better. * For our hypothetical single filer with $115K income, with the same income during both the savings and retirement periods, the taxes paid using a Roth IRA are 22% versus 14.7% using a Traditional IRA. * Social Security income does not increase the taxable income enough to offset the lower effective tax rate. * To save enough money to have the same taxable income in retirement as during savings requires a relatively high savings rate. Saving enough to get the marginal tax rate during savings to equal the effective tax rate in retirement is unrealistic. * If you expect to have a pension, a significant inheritance, or other sources of income in retirement, then the effective tax rate argument may not hold. Tax issues are complex. This post uses many simplifications and assumptions to make the argument clear regarding the effective tax rate argument. This post is meant to give you the information you need to start questioning the conventional wisdom regarding Roth vs Traditional IRAs. But your personal situation will not be the same as our hypothetical single filer. You need to understand your own personal situation before making any decisions. This post is not tax advice. Please consult a tax professional before making any decisions. --- ## The True Cost of Financial Advisors: Is a 1% AUM Fee Worth It? URL: https://algorithmicfire.com/post/can-you-afford-an-investment-advisor Published: 2026-01-17 Category: Saving Abstract: Learn how a seemingly small 1% financial advisor fee can cost you hundreds of thousands of dollars in retirement. See the compounding math and compare index fund alternatives. Date: 2026-01-17 Video: true Youtube_ID: https://youtu.be/5ogSYeekdvU Duration: PT5M58S SEO_Title: The True Cost of Financial Advisors: Is a 1% AUM Fee Worth It? SEO_Description: Learn how a seemingly small 1% financial advisor fee can cost you hundreds of thousands of dollars in retirement. See the compounding math and compare index fund alternatives. # Can You Afford an Investment Advisor? ### The question isn't whether you can afford an advisor, but whether the long term costs of an advisor are worth the money; which will be measured in hundreds of thousands of dollars. We recently had conversations with friends of the channel, one early in their FIRE journey and one late in their journey. Both are paying financial advisors, neither really understand the long term costs of their advisors. We will use this post, not to judge their choices, but to highlight the importance of understanding the long term costs of an advisor, which are substantial. --- ## Why It Seems to Make Sense To Use an Advisor, Particularly Early in Your Journey Early in your FIRE journey, it seems like an easy decision to use an advisor. You're not sure what to do with your money. There are many investment options; it seems complicated. But someone will do this for you, and charge about 1% of your assets per year. You do the math, that seems incredibly reasonable. (With $100K in your portfolio, that's $1000 per year; seems like a small price to ensure you are on the right path.) --- ## Where The Decision Goes Wrong There are a few issues with this decision. 1. Early in your journey, the decision is relatively easy. Buy-and-hold is the recommended strategy. But buy-and-hold what? The answer is buy the whole stock market via an ETF (Exchange Traded Fund). We'll cover this in the conclusion with a recommendation to read a book on the subject. (Don't worry, it is a short read.) If you pay anyone, any amount, to do this for you, you are paying too much. 2. Late in your journey, the decision is only slightly more complex. Now the answer is buy the whole stock market with a portion of your assets, and buy the whole bond market with the rest. Maybe you also add in some world-wide stock exposure. In all cases, you are buying ETFs with broad exposure. You can do this yourself, using just 3 ETFs. The same book mentioned above also covers this. Again, paying someone any amount to do this for you is paying too much. > What you will learn by reading the book is that few investors/advisors can outperform the market as a whole. You are generally better off buying broad index funds than paying for active management. If you are following that advice, buying the ETFs yourself is quite simple, and not worth the cost of an advisor. --- ## Costs During Wealth Accumulation Let's take a look at what a 1% annual advisor fee means for your wealth while you are building your wealth. (We'll use the defaults to our [Portfolio Wealth Simulator](/calculators#sor-calculator); start with 0 balance, save $12K/year, growing savings contributions 3%/year, save for 30 years.). The calculator performs a Monte Carlo simulation of 500 runs. Each run a different sequence of returns is generated to simulate returns you might experience if invested 100% in stocks. These returns are then applied to your savings to simulate your wealth over the 30 years. The result is a histogram of possible outcomes. ![image_2.jpg](image_2.jpg) ![image_3.jpg](image_3.jpg) The first chart above is without the advisor, the second chart is with the advisor. * Median accumulated wealth without an advisor: $1.2M - $1.5M * Median accumulated wealth with an advisor: $1.0M - $1.2M **Over the course of a 30 years savings period, the advisor cost you, on average, $200K-$300K.** > To be clear, this is not saying that you paid the advisor the $200K-$300K. It is saying that the advisor cost you $200K-$300K in terms of the returns you received. Compound interest is powerful, but you reduced the compounding from 7%/year to 6%/year; which is a significant drag on your returns. --- ## Costs During Retirement Now we'll use the same calculator to simulate retirement. We'll use the defaults to our [Portfolio Wealth Simulator](/calculators#sor-calculator); except we'll start with $1.2M since that is near the median of the wealth accumulated in the previous simulation. The SWR (Safe Withdrawal Rate) of 5% means you retired with $60K/year of income. Important point: This calculator is a fixed withdrawal rate calculator. That said, we ran the same analysis with a variable withdrawal rate, and the results were similar. The simulation is again a Monte Carlo simulation of 500 runs, similar to above, but now we are withdrawing money from the portfolio. This time we will look at the time series of portfolio balance for each run, instead of histograms of final wealth. ![image_4.jpg](image_4.jpg) ![image_5.jpg](image_5.jpg) The first chart above is without the advisor, the second chart is with the advisor. For the second chart, we adjusted SWR down to 4.4% to achieve a similar number of failures (zero balance) as the non-advisor simulation. * SWR without advisor: 5.0% * SWR with advisor: 4.4% (Note that you don't have to reduce the SWR a full 1% to achieve a similar number of failures. The reason is because the expense amount gets smaller as you lose money, whereas the withdrawal rate stays the same. Therefore, you don't need to reduce your SWR 1-for-1 to compensate for the advisor expense.) **Over a 30 year retirement period, that 0.6% of your portfolio is > $200K, and compared to the 5% income you are receiving, represents 12% of your income.** --- ## But Wait, There's More (Or Less Depending On Your Perspective) In the analysis above the SWR was adjusted such that the failure rate was similar between the two simulations. But, the resulting account balances at death were quite different. ![image_6.jpg](image_6.jpg) ![image_7.jpg](image_7.jpg) The median final wealth without the advisor was $1.6M - $2.0M, with the advisor it was $1.2M - $1.5M. In this case you see the impact of the fixed 1% annual expense of the advisor truncate the results of the best case simulations **The impact to your final (legacy) wealth is $400K - $$500K**. (Or, you can use a variable withdrawal rate to spend more while retired and pass on less wealth.) > Again - this is not saying that you paid the advisor the $400K-$500K. It is saying that the advisor cost you $400K-$500K in terms of the returns you received due to reduced compounding. --- ## Conclusion We modeled a savings plan that would result in a median final wealth of $1.0M - $1.5M; a typical target for FIRE. The net cost of an advisor, using our assumptions, is: * $200K-$300K during wealth accumulation. * A lower SWR of 4.4% instead of 5% (no advisor); which results in lower income by $200K or more during retirement. * And $400K-$500K less at death. (Or the option to use a variable withdrawal rate to spend more while retired.) In the title we said the advisor fees "will be measured in hundreds of thousands of dollars". It is really closer to $1M, and in best case investing scenarios, much more. The solution: **Don't use an advisor**. Buy the ETFs yourself, and save the money. If you don't know how to do this, we will recommend a starting point: [The Little Book of Common Sense Investing](https://www.amazon.com/dp/1119404509?lv=shuf&channelId=500&plpRedirect=mhFallback) The Little Book of Common Sense Investing This book is a quick read, two hundred and some pages, in a small format. It is a great starting point for understanding the basics of investing. Here is a description: >"Wiley's describes The Little Book of Common Sense Investing by John C. Bogle as a guide for long-term wealth building using low-cost index funds, advocating for a simple buy-and-hold strategy that captures market returns by minimizing fees, avoiding market timing, and understanding that costs erode long-term gains. Bogle, founder of Vanguard, argues that trying to beat the market is a "loser's game" and his book offers a proven, simple path to investing success for all levels of investors." --- ## Addendum - Other options * If you use an advisor, once your portfolio is larger than $1M, you should start inquiring about reducing the fee structure, as some advisors will offer a discount for larger portfolios. * Use a prebuilt portfolio, a target-date fund, or a robo-advisor. * Example: [ETrade](https://us.etrade.com/etx/pxy/prebuiltetfportfolios;jsessionid=D6FB6EB1C86B1EDF2922FA5D75B2CB60.tomcat1#/) has prebuilt portfolios. These are available as: aggressive, moderate, conservative, and income. Each has a small number of ETFs, designed to fit the portfolio description. You select your account, select the portfolio, and they populate an order to buy the ETFs for you. --- ## Retirement Planning: Forward vs Backward Planning Strategies Explained URL: https://algorithmicfire.com/post/hope-is-not-a-strategy-retirement-takes-planning Published: 2026-01-12 Category: Retirement Planning Abstract: Stop guessing. Learn the difference between Forward and Backward retirement planning and build an actionable, number-based roadmap to your financial independence goal. Date: 2026-01-12 Video: true Youtube_ID: https://youtu.be/St6gn7kW4Qo Duration: PT7M11S SEO_Title: Retirement Planning: Forward vs Backward Planning Strategies Explained SEO_Description: Stop guessing. Learn the difference between Forward and Backward retirement planning and build an actionable, number-based roadmap to your financial independence goal. # Hope Is Not a Strategy; Retirement Takes Planning ### You must have a savings plan, and a withdrawal plan; either can come first. We will show you how to make both plans so you have a clear path to retirement. In this post we will show you how to use our calculators to create a savings plan, and a withdrawal plan. We will work through two examples. First, we start with a savings plan, and then determine a withdrawal plan. Second, we start with a withdrawal plan, and then determine a savings plan that supports the withdrawal plan. When we are done, you'll understand how to use our calculators to create your own plans. --- ## Forward vs Backward Planning With forward planning, you start with your current savings, annual contributions, the amount by which you expect to grow your contributions each year, and your retirement age. You forecast out your future savings balance at retirement, then decide on a withdrawal strategy, and that determines how much income you will have each year in retirement. Forward planning works well in these cases: * You are young, and have a long time to save. * You know how much you can save, and when you want to retire. You want to know how much income you will have in retirement. With backward planning, you decide on a retirement income target, then work backwards to determine how much you need to save each year to achieve that income target. This approach assumes you have more control over how much you can save each year, and that you have the discipline to decide to save more each year to achieve your retirement income target. Backward planning works well in these cases: * You are older, and have a shorter time to save. (That is, your savings is already largely determined because you are close to retirement.) * You know how much income you want in retirement, and you want to know how much you need to save each year to achieve that income target. Neither method is better than the other; they are just different. We will walk through using our calculators to cover both methods. The examples aren't meant to be prescriptive; they are just examples. Our goal is to show you how to use our calculators to create your own plans. --- ## Real vs Nominal Returns Reminder that we will be using [real returns](/post/understanding-safe-withdrawal-rate.md#real-vs-nominal-returns) for our calculations; read the link if you need a refresher. (Real returns are the returns you earn after accounting for inflation. This keeps the purchasing power of your money constant. I.E. $1M today has the same purchasing power as $1M when you retire, even if that is many years in the future.) --- ## Forward Planning Example Quinn is 35 years old and has $100,000 in savings. Quinn plans to save $10,000 per year, expects to grow her contributions by 2% per year (real growth), and plans to invest the savings in 100% stocks. (In our calculator we used 7.0% real return with a 17% stdev to approximate the S&P 500.) Quinn plans to retire at age 65. ### Savings at Retirement - Forward Planning Example We put those values into our [Portfolio Wealth Simulator](/calculators#sor-calculator), and it shows us the future value of her savings at retirement. ![image_1.jpg](image_1.jpg) ![image_2.jpg](image_2.jpg) * Because stocks are volatile, the simulator shows a range of possible outcomes. The middle of the range is the most likely outcome, and the outer bounds are the least likely outcomes. * The simulation shows a median of between $1.3M and $1.8M at retirement. * The total range of outcomes is between about $300K and $10.3M. This is where _you_ have to make some decisions regarding risk tolerance. Do you want to plan for the median, or a worst case? There isn't a right or wrong answer; just the answer you will be comfortable with in 30 years time. * You might decide you need to save more to ensure the retirement you want. * Or you might decide that this is all you can do, and you'll take what comes as a result. ### Withdrawal Strategy - Forward Planning Example For this example, we will have Quinn plan on a savings of $1M at retirement; below the average, but well above a worst case. Once in retirement, Quinn will invest the portfolio in 50% stocks and 50% investment grade corporate bonds. (In our calculator we used 5.8% real return with a 6.1% stdev to approximate the portfolio.) Quinn has decided on a fixed withdrawal rate of 5%. ![image_3.jpg](image_3.jpg) ![image_4.jpg](image_4.jpg) The results of this withdrawal strategy show about 10 of 500 cases where Quinn runs out of money before death; Quinn is comfortable with this risk. * **The result of this saving and withdrawal strategy is an income of $50K/year in retirement.** To be clear, nothing is certain here. * There were assumptions made regarding risk during the savings period, and during the withdrawal period. * This withdrawal strategy is a simple fixed withdrawal rate. + We cover more advanced withdrawal strategies in our post [Variable Withdrawal Rates Enable Increased Retirement Income](/post/variable-withdrawal-rates-enable-increased-retirement-income); those could be used to increase the income Quinn receives in retirement, thereby reducing account balance at death. But variable withdrawal rates also increase the risk of either a period of reduced income or running out of money. * Consider these results a guide to what could happen, not a prediction of what will happen. --- ## Reverse Planning Example Jordan is also 35 years old, but has much more flexibility in planning than Quinn. Jordan currently has a high income, and foresees significant increases in their income in the future. Jordan wants to ensure a high income in retirement, but also wants to understand what the trade-offs are regarding quality of life now. ### Withdrawal Strategy - Reverse Planning Example Jordan wants to plan for a retirement with income of _at least_ $200K/year from their portfolio. Jordan plans to retire at age 65. (Jordan will use the same saving and retirement investment strategies as Quinn; 100% stocks during the savings period, and 50% stocks and 50% investment grade corporate bonds during the withdrawal period.) ![image_5.jpg](image_5.jpg) ![image_6.jpg](image_6.jpg) * Jordan chose a fixed withdrawal rate of 4.2%. This is lower than Quinn's withdrawal rate of 5%, but Jordan is more risk averse, and doesn't want to see any failures in the simulation. * This means Jordan will need to save at least $4.8M at retirement, but they chose to round up to an even $5M ### Savings at Retirement - Reverse Planning Example So what does it take to have $5M at retirement? Jordan currently has $600K in their portfolio. To get to a worst case $4.8M at retirement, Jordan will need to: * Save $80K/year. * Grow that savings at a real rate of 7%/year. * Save for 30 years. ![image_7.jpg](image_7.jpg) ![image_8.jpg](image_8.jpg) * Again, because stocks are volatile, the simulation shows a wide range of outcomes for savings at retirement. + **After an initial period of high savings, if the market performs well, Jordan could reduce the savings rate in order to achieve a higher standard of living now, while still targeting their retirement goal of $5M.** This is the power of compound interest; early savings can generate significant sums over long time periods. By starting with a high rate of savings, and getting those funds invested early, Jordan will likely be able to reduce their savings rate in the future, while still meeting their retirement goal. But, if Jordan is unlucky, and the market performs poorly, they will need to continue saving at a high rate to meet their retirement goal. We discussed this in our post [How Much Retirement Savings Can Be Accumulated with 30 Years of Saving $1000/month?](/post/how-much-retirement-savings-can-be-accumulated-with-30-years-of-saving-1000month). # Takeaways * You can plan forward, and plan backward. Choose what suits you best. * There are risks during both the savings and withdrawal periods. + Nothing is certain; planning is only a guide to what could happen, not a prediction of what will happen. * These simulations used fixed withdrawal rates, but variable withdrawal rates could be used to increase income in retirement, or to reduce account balance at death. * **Failure to plan is the only failure.** --- ## Capital Gains Tax Impact on Trend Following: Is Downside Protection Worth the Tax Drag? URL: https://algorithmicfire.com/post/capital-gains-tax-impacts-on-trend-following-strategies Published: 2025-12-30 Category: General Investing Abstract: Quantifying the hidden capital gains tax drag on active trend following strategies. Compare tax-drag vs downside protection benefits in taxable accounts. Date: 2025-12-30 Video: true Youtube_ID: https://youtu.be/cQx6A1Gq7Tk Duration: PT7M50S SEO_Title: Capital Gains Tax Impact on Trend Following: Is Downside Protection Worth the Tax Drag? SEO_Description: Quantifying the hidden capital gains tax drag on active trend following strategies. Compare tax-drag vs downside protection benefits in taxable accounts. # Capital Gains Tax Impacts on Trend Following Strategies ### Retirement accounts are generally tax deferred, but if you have taxable accounts you should be aware of the tax implications of increased trading frequency. In our last post “[Defending Your Savings Against Significant Downturns](/post/defending-your-savings-against-significant-downturns)“, we presented results for two trend following methods applied to a basket of the 50 largest (by market capitalization) stock ETFs. We didn’t address tax implications. (Since the trend following methods buy/sell more frequently than buy-and-hold, the trend following methods will subject you to capital gains taxes.) We have since updated that post with the below to make this explicitly clear: > We are **not including the tax impact of capital gains** in this analysis. There are three reasons for this: > 1. The focus of this analysis is downside protection, not tax efficiency. > 2. Retirement funds are frequently held in tax-advantaged accounts. > 3. The tax impact is complex to calculate and would require additional assumptions. >That said, the impact may be non-zero and **we will address this in a future post**, so if you hold significant assets in taxable accounts you can understand the impact of capital gains taxes on trend following performance. In this post, **we WILL address the tax impact of capital gains** on trend following strategies. --- ## Tax Impacts are Highly Variable The problem with including the impact of capital gains is that they are not applicable to tax advantaged accounts (401K, traditional/Roth IRA, HSA, etc.), and are otherwise highly variable. * Long term capital gains tax rates: 0%-20% + Long term capital gains are taxed at 0% up to income thresholds: $48,350 (Single filers), or $96,700 (Married couples filing jointly) * Short term capital gains tax rates: taxed at your ordinary income tax rates, which range from 10% to 37% for the 2025 tax year Since our prior analysis covered the zero tax case, we will select **a short term capital gains rate of 35% and long term capital gains rate of 20% for this analysis**. Thus the prior analysis represents a best case, and this a near worst case. (Not the absolute worst case as we selected 35% and not 37% for the short term capital gains tax rate.) These tax rates are applied to every trade, for each trend following strategy, AND to buy-and-hold results at the end of the analysis period. (Any trades that are open at the conclusion of the analysis are closed and taxes paid at the applicable rate.) **Please review** “[Defending Your Savings Against Significant Downturns](/post/defending-your-savings-against-significant-downturns)“ for a description of the trend following methods and details of the analysis. We will not repeat that here, and will just proceed straight to the results. --- ## Performance - Stock ETFs ### Maximum Drawdown ![image_1.jpg](image_1.jpg) * Median maximum drawdown results are largely unchanged. * Reference: Median Maximum drawdown with **zero capital gains taxes** + Excess return strategy median: -31.6% + Moving average strategy median: -30.6% + Buy and hold median: -54.9% ### CAGR ![image_2.jpg](image_2.jpg) * Median CAGR results decreased for both trend following methods. + Excess Returns Strategy median CAGR reduced 1.8%. + Moving Average Strategy median CAGR reduced 1.5%. * Reference: Median CAGR with **zero capital gains taxes** + Excess return strategy: 10.2% + Moving average strategy: 8.3% + Buy and hold: 10.3% ### Sharpe Ratio ![image_3.jpg](image_3.jpg) * The advantage seen in the sharpe ratio with no taxes has been eliminated. + That said, the sharpe ratios are all now quite close, indicating that the loss in CAGR is justifiable considering risk-adjusted returns. * Reference: Median Sharpe Ratio with **zero capital gains taxes** + Excess return strategy: 0.67 + Moving average strategy: 0.65 + Buy and hold: 0.56 --- ## Performance - Bond ETFs We didn’t cover bonds in our prior analysis, but decided to add them for this analysis. We selected the 100 largest bond ETFs (by market capitalization) for this analysis. ### Maximum Drawdown ![image_4.jpg](image_4.jpg) * Median maximum drawdowns are reduced significantly with either trend following strategy, but drawdowns are much less than with stock ETFs. ### CAGR ![image_5.jpg](image_5.jpg) * Median CAGR is better with either trend following strategy than buy-and-hold; substantially better with the Excess Return strategy. ### Sharpe Ratio ![image_6.jpg](image_6.jpg) * Sharpe Ratio for the Excess Returns Strategy is significantly higher than buy-and-hold. * Sharpe Ratio for the Moving Average Strategy trails buy-and-hold, but not by much. --- ### Takeaways * Either trend following method, applied to either stock or bond ETFs, maintains a **significant drawdown advantage over buy-and-hold**. * Our premise of trend following was that it can be used to reduce drawdowns, at the expense of some CAGR. + We likened trend following to insurance; the downside protection will cost you a bit of upside. * CAGR - Stock ETFs + In a tax advantaged account, the Excess Returns Strategy CAGR with stock ETFs **was only 0.1% worse than buy-and-hold**. + With near worst case capital gains tax, the Excess Returns Strategy CAGR is 0.9% worse than buy-and-hold, but the moving average strategy is 2.5% worse than buy-and-hold. + Thus the downside protection does come at a cost in accounts that are not tax advantaged. * CAGR - Bond ETFs + There is no insurance cost; either trend following method does better than buy-and-hold with bond ETFs. * **The Excess Returns Strategy is the better choice of the two trend following methods.** --- ## Put Trend-Following to Work: Explore the Live Dashboard Ready to see how trend-following applies to your own investments? Our live interactive **[Dashboard](/dashboard)** updates daily to show you exact buy, sell, and cash-sweep signals for your specific holdings. Use the dashboard to: * **See Today's Signals:** Find out if SPY, QQQ, and 100+ other index and bond ETFs are currently in the market or swept to cash. * **Build a Custom Portfolio:** Model your own retirement allocation (e.g., a 60/40 split) and overlay our Excess Return trend models to see how it would have performed historically. * **Compare Strategies:** Toggle between SMA, MMA, and Cash Alternative (CA) styles to find the best fit for your risk tolerance.
Explore the Interactive Dashboard
--- ## Protect Your Portfolio from Market Crashes: Downside Protection vs Buy-and-Hold URL: https://algorithmicfire.com/post/defending-your-savings-against-significant-downturns Published: 2026-05-23 Category: General Investing Abstract: Discover the risks of a buy-and-hold strategy in retirement. Learn how trend following and downside protection rules can shield your retirement nest egg from severe market drawdowns. Date: 2026-05-23 Video: true Youtube_ID: https://youtu.be/0OxGyHKqPRA Duration: PT8M23S SEO_Title: Protect Your Portfolio from Market Crashes: Downside Protection vs Buy-and-Hold SEO_Description: Discover the risks of a buy-and-hold strategy in retirement. Learn how trend following and downside protection rules can shield your retirement nest egg from severe market drawdowns. # Defending Your Savings Against Significant Downturns ### What happens if the market doesn’t just "dip," but stays down for a decade or more? We explore strategies to safeguard your savings from prolonged stagnation. *Last Updated: May 23, 2026 (Refreshed to include Multiple Moving Average ensemble strategies and updated risk-free benchmark)* In our previous post (“[U.S.-Based Investors Think the Worst-Case Scenario is the Great Depression or GFC. Other Countries Disagree](/post/us-based-investors-think-the-worst-case-scenario-is-the-great-depression-or-gfc-other-countries-disagree)“), we looked at a sobering historical precedent: the 1989 Japanese asset bubble. Following its peak, the Nikkei 225 averaged just 39% of its original value for over three decades. While U.S. investors haven’t faced a 30-year stagnation in modern history, relying solely on prior U.S. data for retirement planning can leave a portfolio vulnerable to “worst-case” scenarios that have happened elsewhere. Below we will discuss techniques to mitigate the damage such a downturn can cause to your investments. --- ## The Limitations of Buy-and-Hold For young investors with decades to go, “buy-and-hold” remains a gold standard. However, those nearing or in retirement face a different math. As we detailed in our analysis of [Safe Withdrawal Rate failures](/post/safe-withdrawal-rate-failure), even a few years of zero real returns can deplete a fixed-withdrawal account much faster than anticipated. To protect your lifestyle, you may need a more responsive approach—one that sacrifices a portion of peak returns for significantly better downside protection. Trend following is a general approach to this problem. --- ## Trend Following: A Rules-Based Safety Net Trend following is often confused with “market timing,” but the difference is critical. While market timing attempts to predict the future, trend following reacts to the present. It uses disciplined, algorithmic rules to identify sustained price movements, aiming to “ride” major gains while systematically cutting losses before they become catastrophic. Think of it as a behavioral release valve that helps you stick to your long-term plan during high-stress cycles. * ***The goal of trend following is NOT to beat the market, or any particular indices; it is to provide downside protection*** --- ## General Academic Acceptance of Trend Following as an Investment Strategy Trend following strategies have been heavily researched and the results support the strategies as legitimate. Here is one example: Hurst, Ooi, Pedersen, ["A Century of Evidence on Trend-Following Investing"](https://fairmodel.econ.yale.edu/ec439/hurst.pdf), Yale University, 2015. We tried to find counterfactual arguments with this prompt to Google’s Gemini AI: “*are there any academic references that conclude trend following is misinformed, reckless, or generally a poor investment strategy*“. The response: *“Academic literature generally views trend following as a legitimate, well-documented investment strategy rather than "misinformed" or "reckless". The consensus is that it provides a valuable source of **diversification** and "crisis alpha" (strong performance during major market downturns).“* --- ## What Are We Hoping To Achieve? ![image_1.jpg](image_1.jpg) The chart above is a visual representation of what we are aiming to achieve. Shown (blue) is the normalized price (starting value = 1.0) for [QQQ](/report/QQQ_STRATEGY_EXCESS_RETURN_MMA_investing.html) (Nasdaq 100 index ETF), and (yellow) the gain from trading using a trend following strategy. As the chart illustrates, the trend-following strategy effectively sidestepped the worst of the dot-com bubble and the 2008 Financial Crisis. While out of the market, the portfolio continued to generate modest returns by pivoting into U.S. Treasuries. In this case, the strategy resulted in substantially higher overall gain, with much less volatility. Consider the higher gain of the trend following results an anomaly; you will usually give up some gains in order to have the downside protection—a phenomenon we’ll explore across more ETFs below. --- ## Examination of Trend Following Methods With that understanding of what we hope to achieve, we present results from three trend-following strategies: * **Excess Return (SMA)**: This approach compares the moving average of a security against the moving average of a "risk-free" benchmark (using the 3-Month U.S. Treasury yield, `DGS3MO`). If the security is outperforming the benchmark on a trend basis, it triggers a buy signal. Otherwise, it triggers a sell and sweeps the proceeds to cash. This is a binary strategy (either 100% invested or 100% in cash). * **Excess Return (MMA)**: An ensemble version of the Excess Return strategy that uses multiple moving averages to scale in and out of the security. Instead of an all-or-nothing approach, the portfolio holds varying percentages (0%, 33.3%, 66.7%, or 100%) in the security, with the remainder swept to cash earning interest. This strategy offers smoother transitions but generates more trades. * **Excess Return (MMA CA)**: Built on the exact same ensemble logic and signal parameters as the Excess Return MMA strategy. However, instead of sweeping out-of-market capital to a static cash interest rate, it dynamically rotates capital among a high-liquidity, defensive basket of ultra-short Treasury and floating-rate ETFs ([FLOT](/report/FLOT_STRATEGY_EXCESS_RETURN_MMA_investing.html), [SHV](/report/SHV_STRATEGY_EXCESS_RETURN_MMA_investing.html), [BIL](/report/BIL_STRATEGY_EXCESS_RETURN_MMA_investing.html)) based on their momentum and trend signals. This serves as a "Cash Alternative" sleeve to optimize defensive yields while strictly managing duration risk (see Addendum: Dynamic Cash Alternatives below). * **Moving Average** (A.K.A. The Golden Cross/Death Cross): A classic trend-following strategy using the 50-day and 200-day simple moving averages. A buy is triggered when the 50-day MA climbs above the 200-day MA (Golden Cross), and a sell is triggered when it breaks below (Death Cross). The standard strategies invest in U.S. 3-Month Treasuries when not holding the target security, while the Cash Alternative (CA) variant dynamically rotates across defensive ETFs during cash-sweep periods. ### Strategy Styles: Investing vs. Trading Each strategy in our analysis is backtested under one of two execution styles: * **Investing Style**: Uses longer-term trends to minimize transaction frequency, reducing portfolio turnover and potential tax drag in taxable accounts. **The statistics and charts throughout this post are based on the Investing Style.** * **Trading Style**: Uses shorter-term trends for faster responsiveness. While it reacts more rapidly to market turns, it generates significantly more trades. Up-to-date results for both styles across all assets are available on the live [Dashboard](/dashboard). > We are **not including the tax impact of capital gains** in this analysis. There are three reasons for this: > > 1. The focus of this analysis is downside protection, not tax efficiency. > 2. Retirement funds are frequently held in tax-advantaged accounts. > 3. The tax impact is complex to calculate and would require additional assumptions. > > That said, the impact may be non-zero, and we address this in a separate post on capital gains tax impacts, which is particularly relevant if you hold significant assets in taxable accounts. It should be noted that these are just three strategies in the general realm of trend following. There is a limitless range of possible strategies using different timeframes, moving average types (simple, exponential, weighted), stop-losses, and cash sweeps. ### Quick-Buy and Stop-Loss Solve Reaction Time Problems Standard moving averages are slow to react. To solve this and prevent being left behind during V-shaped recoveries or caught in rapid crashes, we incorporate two supplementary algorithms: * **Quick-Buy**: If a security closes higher for seven consecutive trading days, the algorithm triggers a buy signal regardless of the longer-term moving averages. (This transitions to a normal buy signal if the averages eventually cross, and sells on a 5% drop while in the quick-buy state.) * **Stop-Loss**: An automatic risk-mitigation tool that triggers a sell if the security drops below a predetermined threshold (varying by asset class to account for historical volatility), protecting the portfolio from rapid, vertical selloffs. That is the extent of the algorithms: * Buy/sell based on moving average trends. * Buy when a security is consistently advancing (Quick-Buy). * Sell a security immediately if it drops significantly and too fast for the moving averages to react (Stop-Loss). --- ## Performance To validate these strategies, we backtested all three algorithms across the 106 stock ETFs in our coverage universe, comparing their performance directly to a traditional buy-and-hold approach. The testing period for each fund spans its entire available history, adjusted for the lead-in time required to calculate the moving averages. We will evaluate the strategies using three key metrics: * **Maximum Drawdown**: The largest peak-to-trough drop in a portfolio's value, showing the worst potential loss. * **CAGR** (Compound Annual Growth Rate): The average yearly rate of return. * **Sharpe Ratio**: A metric of risk-adjusted return (reward per unit of volatility). A higher Sharpe ratio indicates a more efficient portfolio. ### Maximum Drawdown ![image_2.jpg](image_2.jpg) For each ETF, using each strategy, the maximum drawdown was determined and is charted above. Drawdowns are significantly reduced using any of the trend-following strategies: * The median drawdown is **-51.3%** for buy-and-hold, but drops to **-28.3%** for Excess Return SMA, **-21.2%** for Excess Return MMA, and **-24.6%** for the Moving Average strategy. * **First quartile (worst 25th percentile) drawdowns were: buy-and-hold (-58.9%), Excess Return SMA (-34.6%), Moving Average (-28.4%), and Excess Return MMA (-26.3%)**. * During the Great Financial Crisis (GFC), **buy-and-hold experienced a -60.7% drawdown if you held QQQ**, compared to just **-29.2% for the Excess Return SMA strategy** and **-20.9% for the Excess Return MMA strategy**. ### CAGR ![image_3.jpg](image_3.jpg) For each ETF, using each strategy, the CAGR was determined and is charted above: * Buy-and-hold achieved a median CAGR of **10.7%**. * The Excess Return SMA strategy closely matched this at **10.4%** median CAGR, while the Excess Return MMA strategy followed at **10.1%**. * The Moving Average strategy trailed both at a **9.0%** median CAGR. This aligns with our expectations: trend following behaves like portfolio insurance. While insurance significantly reduces drawdowns (risk), it comes at a minor cost to the compound annual growth rate (CAGR), especially in the Moving Average strategy. ### Sharpe Ratio ![image_4.jpg](image_4.jpg) The Sharpe ratio indicates that the reduction in drawdowns is well worth the minor drag on returns: * The median Sharpe ratio for buy-and-hold is **0.53**. * All three trend-following strategies achieved substantially higher median Sharpe ratios: **0.64** for Excess Return SMA, **0.65** for Moving Average, and **0.75** for the ensemble Excess Return MMA. * This demonstrates that trend following significantly improves risk-adjusted returns compared to buy-and-hold. ### Asset Class Suitability: Why Indices and Fixed-Income Excel While we provide comprehensive backtests on our live dashboard across a wide range of asset classes—including bond ETFs, stock ETFs, individual equities, and commodities—the quantitative reality is that **trend-following does not perform equally across all categories**: * **Fixed-Income (Bonds)**: Trend-following performs exceptionally well on bond ETFs. Fixed income is highly sensitive to macroeconomic interest rate regimes, which tend to persist in multi-year macro cycles (bull and bear bond markets). With lower natural volatility, whipsaws are minimal, and trend-following shields capital cleanly from prolonged rate hikes. * **Equity Index ETFs**: Diversified stock indices (like [SPY](/report/SPY_STRATEGY_EXCESS_RETURN_MMA_investing.html) or [QQQ](/report/QQQ_STRATEGY_EXCESS_RETURN_MMA_investing.html)) represent broad economic growth trends. Diversification naturally smooths out individual company news, making these index ETFs highly responsive to macro-economic momentum. * **Individual Stocks**: Trend-following is far less effective here. Individual stocks are subject to high idiosyncratic volatility, corporate events, and "gap risk" (e.g., earnings releases causing a stock to gap down 20% overnight). Trend algorithms get whipsawed frequently by this corporate noise, cutting winners too early and taking sudden gap-down losses. * **Commodities**: Assets like Gold, Oil, or Agriculture are highly cyclical and prone to sudden supply shocks and extended periods of range-bound mean-reversion. Trend-following in commodities often suffers from severe whipsaw drag during choppy, sideways markets. We have included individual equities and commodity ETFs on our platform primarily to satisfy the common query, *"but how does this perform on X?"* However, for systematic retirement protection and safe withdrawal security, the data strongly favors sticking to diversified index and fixed-income ETFs. To support this flexibility, the platform's custom portfolio builder allows you to incorporate these assets into your personal allocations while electing a passive, buy-and-hold strategy for these specific sleeves instead of forcing a trend-following overlay. --- ## Takeaways * Trend following systematically **reduces the probability of holding securities into a significant downturn**. * While the reduction in risk can come at the expense of a minor reduction in CAGR, the risk-adjusted returns (Sharpe ratios) are significantly superior to buy-and-hold. * The ensemble Excess Return MMA strategy offers the best risk-adjusted profile (highest median Sharpe ratio at 0.75) and lowest median drawdown (-21.2%). --- ## A Practical Example ![image_5.jpg](image_5.jpg) The chart above shows the QQQ price history with overlays indicating the periods when the Excess Return SMA strategy was invested in the market (shaded in gold). As illustrated, the strategy successfully exited QQQ, sidestepping the worst of the dot-com crash and the 2008 Financial Crisis, while capturing the subsequent bull runs. The compound effect of avoiding these major downturns—while continuing to accumulate interest income during down cycles—is what drives the substantial wealth outperformance shown in the cumulative growth chart (Chart 1) at the beginning of this post. --- ## Addendum: Trading Style Comparison While the main analysis of this post focuses on the **Investing Style** (designed for long-term builders, using longer-term trends to minimize transaction frequency and turnover), our platform also backtests a more active **Trading Style**. This style uses shorter moving averages to react more rapidly to market turns. Below is the statistical performance of the Trading Style across the stock ETF universe: ### Maximum Drawdown (Trading Style) ![image_6.jpg](image_6.jpg) *The median maximum drawdown for the Trading style is **-21.6%** (compared to **-21.2%** for the Investing style).* ### CAGR (Trading Style) ![image_7.jpg](image_7.jpg) *The median CAGR is **8.2%** (compared to **10.1%** for the Investing style).* ### Sharpe Ratio (Trading Style) ![image_8.jpg](image_8.jpg) *The median Sharpe ratio is **0.70** (compared to **0.75** for the Investing style).* ### Core Comparison Summary The data illustrates a key trend-following lesson: **faster responsiveness is not always better**. While the Trading Style exits positions slightly quicker during sharp declines, the increased frequency of trades leads to "whipsaws" (buying and selling on short-term market noise). This friction drags the median CAGR down to **8.2%** (vs. **10.1%** for the Investing style) and lowers the risk-adjusted return (Sharpe ratio of **0.70** vs. **0.75**), while yielding virtually identical drawdown protection. ### Utility of the Trading Style While the long-term historical averages favor the Investing Style, the **Trading Style** serves a specific utility for investors prioritizing rapid risk mitigation. In periods of high market volatility or swift, severe market downturns, the shorter moving averages trigger defensive cash sweeps significantly faster, protecting capital early in the sell-off. The tradeoff, however, is that you must be willing to accept more frequent false signals ("whipsaws") and higher transaction turnover in exchange for this response time. --- ## Addendum: Dynamic Cash Alternatives (Excess Return MMA CA) In our standard strategies, out-of-market capital is swept into a cash proxy pegged to the 3-Month U.S. Treasury yield. However, in low or shifting interest rate environments, holding raw cash or standard short-term treasuries can leave yield on the table or introduce mild interest rate risk. To address this, we developed a dynamic cash management option: **Excess Return MMA CA** (Cash Alternative). This strategy executes the identical ensemble entry and exit signals on the primary asset as the Excess Return MMA strategy, but manages the cash sleeve dynamically by rotating capital among a high-liquidity defensive basket of three ETFs: 1. **[FLOT](/report/FLOT_STRATEGY_EXCESS_RETURN_MMA_investing.html)**: iShares Floating Rate Bond ETF (Floating-rate corporate debt yielding credit spread premium) 2. **[SHV](/report/SHV_STRATEGY_EXCESS_RETURN_MMA_investing.html)**: iShares Short Treasury Bond ETF (0-12 Month U.S. Treasuries) 3. **[BIL](/report/BIL_STRATEGY_EXCESS_RETURN_MMA_investing.html)**: SPDR Bloomberg 1-3 Month T-Bill ETF (Ultra-short Treasury bills) > **Design Note**: We analyzed versions of the CA sleeve that included medium-term and corporate bond funds ([BNDX](/report/BNDX_STRATEGY_EXCESS_RETURN_MMA_investing.html), [VCSH](/report/VCSH_STRATEGY_EXCESS_RETURN_MMA_investing.html), [VTIP](/report/VTIP_STRATEGY_EXCESS_RETURN_MMA_investing.html)). However, quantitative audits revealed that during stock market drawdowns, these funds introduced **duration risk** and **credit risk**, resulting in capital losses at the exact moment the strategy was seeking defensive shelter. To prevent this, the CA sleeve is strictly restricted to near-zero duration assets, ensuring capital preservation matches standard cash. ### Cash Alternative Sleeve Rules On the **second trading day of each month**, the cash sleeve dynamically selects the optimal defensive ETF: * **Trend Filter**: Each candidate ETF is evaluated using a simple trend filter—its price must be above its 25-day moving average. * **Momentum Ranking**: Among the ETFs that pass the trend filter, the strategy ranks them by their **54-day** absolute momentum (return over the lookback period) and selects the asset with the strongest performance. * **Defensive Fallback**: If all candidate ETFs fail the trend filter, the sleeve defaults to **BIL** as the baseline cash holding. For historical backtesting dates prior to BIL's launch on May 25, 2007, the system seamlessly falls back to standard 3-Month Treasury interest rates (`DGS3MO`), which are logged in our reports as `"CASH"`. By utilizing a 54-day momentum lookback and rebalancing on the second trading day, the strategy avoids ex-dividend date clustering noise. This allows the portfolio to capture higher yields from corporate credit spreads ([FLOT](/report/FLOT_STRATEGY_EXCESS_RETURN_MMA_investing.html)) or short-term rates ([SHV](/report/SHV_STRATEGY_EXCESS_RETURN_MMA_investing.html), [BIL](/report/BIL_STRATEGY_EXCESS_RETURN_MMA_investing.html)) during stable environments, while automatically retreating to T-bills when rates or credit markets show stress. > **Tax & Execution Friction Note**: Because the CA sleeve dynamically rotates between ETFs on a monthly basis, it generates frequent transaction events: > > * **Transaction Drag & Bid/Ask Spreads**: For these specific ETFs ([FLOT](/report/FLOT_STRATEGY_EXCESS_RETURN_MMA_investing.html), [SHV](/report/SHV_STRATEGY_EXCESS_RETURN_MMA_investing.html), [BIL](/report/BIL_STRATEGY_EXCESS_RETURN_MMA_investing.html)), transaction costs are negligible. Because they are highly liquid institutional-grade funds, they trade with extremely tight bid/ask spreads (typically $0.01 per share, or under 0.02% friction) and zero commission on modern brokerages. The cumulative annual drag of these rotations is under 0.15%, which is easily offset by the yield premium. > * **Tax Consequences**: In a taxable brokerage account, these monthly rotations generate short-term capital gains tax liabilities and reporting friction. This tax drag can quickly consume the marginal yield advantage. Consequently, the **Excess Return MMA CA** strategy is recommended for tax-advantaged accounts (such as IRAs or 401ks), while the standard **Excess Return MMA** strategy (which sweeps to static interest-bearing cash) is generally more practical for taxable accounts. --- ## Understanding the Backtest Trade Logs When exploring the interactive simulations on the dashboard, each asset and portfolio features a detailed **Trade History** log table. To understand the output, keep these three trade types in mind: * **Completed Trades**: Standard trades showing when the system bought an asset (entry) and sold it (exit) based on moving average signal crossovers. * **Open / Mark-to-Market Trades**: If the system is currently holding an asset at the end of the backtest simulation, the final position is marked to market using the latest available price so that all cumulative gains are accounted for. * **Interest Trades**: When the system is out of the market (holding cash/yield), these entries record the yield/interest income accrued over the out-of-market duration. For standard strategies, this tracks the Treasury rate; for CA strategies, it tracks the active defensive ETF (like [SHV](/report/SHV_STRATEGY_EXCESS_RETURN_MMA_investing.html) or [FLOT](/report/FLOT_STRATEGY_EXCESS_RETURN_MMA_investing.html)). --- ## Put Trend-Following to Work: Explore the Live Dashboard Ready to see how trend-following applies to your own investments? Our live interactive **[Dashboard](/dashboard)** updates daily to show you exact buy, sell, and cash-sweep signals for your specific holdings. Use the dashboard to: * **See Today's Signals:** Find out if [SPY](/report/SPY_STRATEGY_EXCESS_RETURN_MMA_investing.html), [QQQ](/report/QQQ_STRATEGY_EXCESS_RETURN_MMA_investing.html), and 100+ other index and bond ETFs are currently in the market or swept to cash. * **Build a Custom Portfolio:** Model your own retirement allocation (e.g., a 60/40 split) and overlay our Excess Return trend models to see how it would have performed historically. * **Compare Strategies:** Toggle between SMA, MMA, and Cash Alternative (CA) styles to find the best fit for your risk tolerance.
Explore the Interactive Dashboard
--- ## The Nikkei Nightmare: Why the 4% Rule Fails Outside the US (Japan Scenario) URL: https://algorithmicfire.com/post/us-based-investors-think-the-worst-case-scenario-is-the-great-depression-or-gfc-other-countries-disagree Published: 2025-12-20 Category: General Investing Abstract: Why 100 years of US stock market data creates a dangerous bias. Understand how Japan's 30-year Nikkei stagnation redefines safe withdrawal rate risk for global investors. Date: 2025-12-20 Video: true Youtube_ID: https://youtu.be/zUauxkzL_VI Duration: PT6M27S SEO_Title: The Nikkei Nightmare: Why the 4% Rule Fails Outside the US (Japan Scenario) SEO_Description: Why 100 years of US stock market data creates a dangerous bias. Understand how Japan's 30-year Nikkei stagnation redefines safe withdrawal rate risk for global investors. # U.S.-Based Investors Think the Worst-Case Scenario is the Great Depression or GFC. Other Countries Disagree. ### When investment planning for retirement, it is important to consider all possible outcomes. We take a look at Japan in the 1990s to redefine "worst case". U.S.-based investors have had it quite good, for a long time. As we showed in our post “[Safe Withdrawal Rate Failure](/post/safe-withdrawal-rate-failure)”, using a fixed Safe Withdrawal Rate (SWR) of 5% and a 50%/50% stocks/bonds allocation would have been successful, except for retirements starting in: 1937, 1962-69 (most years), 1973, and 2000. If you had used a 4.5% SWR with the same portfolio, there were zero failures. ![image_1.png](image_1.png) Even if you were 100% stocks with a 5% SWR, there were only a few more failing years. (See above chart.) This has left U.S.-based investors confident in general, and confident in U.S. stocks in particular. This historical data, or statistics derived from it, are used in models to determine Safe Withdrawal Rates. Thus the 4% Rule, now the 4.5% Rule, doesn’t fail against the prescribed 50/50 (stock/bond) portfolio. But does this data really represent a proper range of scenarios, including worst case? --- ## It can be worse - Japan in the 90s ![image_2.png](image_2.png) The chart above shows the Nikkei 225 (JAN 1970 - SEP 2025). The Nikkei 225 is roughly the Japanese equivalent of the S&P 500, as it is the most prominent stock index tracking major Japanese companies on the Tokyo Stock Exchange, serving as a key economic barometer. (The Nikkei 225 and S&P 500 differ significantly in calculation as the Nikkei 225 is price-weighted, while the S&P 500 is market-cap weighted.) The obvious problems: * The index peaked in December 1989 at ¥38,915, and didn’t see that level again until February 2024. * The chart is nominal price; not inflation adjusted. That 1989 level represents about ¥47K in today's Japanese Yen. Thus, in real terms, the index only regained its 1989 peak in October 2025. * From 1/1992 to 1/2020, the index averaged ¥15418, or 39% of its peak. * It reached a low of ¥7054, or 18% of its peak. --- ## Retirement Scenario Results We are going to use the investment returns of the Nikkei 225, and treat them like a U.S.-based investor had this same return, just to show how a scenario like this plays out for retirement. Let’s take an optimistic scenario. A person retires in January 1985, well prior to the peak. They believe in stocks, and thus stay invested 100% in stocks. They have 5 years where the account goes up **over 200%** (a factor of 3.12). That is an INCREDIBLE start; who could ask for better. Yet, the results are bleak: * With a 5% fixed withdrawal rate. Balance hits zero in 2004; retirement lasted 19 years. * With a 3% fixed withdrawal rate. Balance hits zero in 2011; retirement lasted 26 years * With a 2% fixed withdrawal rate. Balance hits a low of about $90K in 2012, then recovers to about $120K in 2015 when the 30 year retirement ends. Just made it... + Even though the index is recovering strongly after 2012, a longer retirement would have ended with $0 in 2022; the significant gains just weren’t enough on the reduced balance. * All that, and this was a scenario for retirement starting in 1985. Anyone retiring between 1985-1990 had it much worse. Just to be clear on those results - it took **living off of only 2% of the portfolio to last a 30 year retirement**. --- ## What would you have done? It is valuable to contemplate such a scenario and ask yourself “what would I have done?”. * You might think that not being 100% in stocks would have fixed it, but the results hardly change due to the huge run-up at the start of retirement that you would have missed in a mixed portfolio. * Go to international stocks? The 1990 Nikkei collapse was isolated to the Japanese market. But the downturn in the Nikkei in 2000 was the dot-com bust, and in 2008 the GFC took all markets with it. + This is an example of really unfortunate timing. The local (Japanese) market collapses, then a decade later there are 2 market setbacks that are worldwide. --- ## Takeaways What can we learn from this? * Buy the dip! + Not every dip is a buying opportunity. It will work sometimes, otherwise you are trying to catch a falling chainsaw and it will take your hands off. * “It’s different this time, valuations don’t matter”. + That was literally being said at the time about Japanese asset prices; both stocks and real estate. + Valuations matter. Maybe not today, or next month, but at some point they will matter again. * Buy and hold is appropriate for someone with very long time horizons. But your retirement may be shorter than the long term that justifies buy and hold. * We are advocates for having a strategy to get out of stocks in such circumstances. There are different strategies, we will discuss that in a future post(s). Last it is important to point out that most retirement calculators, safe withdrawal rate models, etc., don’t account for a scenario like this. Maybe this is an extreme case, and they shouldn’t account for a scenario like this. But it is important to know that even in recent history, in an advanced economy, asset collapses do happen. Did we mention AI, or current U.S. asset prices? No. Our intention is not to debate the current situation, but just post a reminder that asset bubbles can happen, have happened not long ago, and they were driven with the same “but this time is different” or “valuations don’t matter” logic. P.S. [Wikipedia](https://en.wikipedia.org/wiki/Japanese_asset_price_bubble) has a good write-up on the Japanese asset collapse. One of our favorite statistics from the era: * “*At their peak, prices in central Tokyo were such that the **1.15 square kilometer** Tokyo Imperial Palace grounds were estimated to be worth more than the **entire real estate value of California***” --- ## Why the 4% Rule is Dead: Best Alternative Retirement Withdrawal Strategies URL: https://algorithmicfire.com/post/the-4-rule-is-dead-heres-whats-replaced-it Published: 2025-12-18 Category: Retirement Planning Abstract: Is the 4% rule safe? Explore why the traditional 4% safe withdrawal rule is dead and compare modern dynamic and variable withdrawal alternatives for early retirement. Date: 2025-12-18 Video: true Youtube_ID: https://youtu.be/CNBv8Gu2ru8 Duration: PT7M29S SEO_Title: Why the 4% Rule is Dead: Best Alternative Retirement Withdrawal Strategies SEO_Description: Is the 4% rule safe? Explore why the traditional 4% safe withdrawal rule is dead and compare modern dynamic and variable withdrawal alternatives for early retirement. # The 4% Rule Is Dead, Here's What's Replaced It ### The 4% rule, which we wrote about in our post regarding Safe Withdrawal Rate, was established back in 1994. Since then, many alternatives have been suggested. We review the major alternatives. Bob C., a friend of the channel, asked us, “Isn’t the 4% rule a bit antiquated? Does it still matter?”. Thank you, Bob, for the inspiration for this post, we hope this answers your questions. (If you have your own questions, please contact us at we’re happy to do the work so you don’t have to.) --- ## Newer Strategies The 4% Rule is a specific method implementing a Safe Withdrawal Rate (SWR), more generally called a withdrawal strategy. Since its inception, alternatives have gained popularity. * In 2006, the author of the 4% rule changed his recommendation to 4.5%. (Reference: [1](https://www.forbes.com/forbes/2011/0523/investing-retirement-bill-bengen-savings-spending-solution.html)) There are three general types of withdrawal strategies that are widely discussed: * Fixed Withdrawal Strategies (FWS) - the 4% rule is one of these. The withdrawal rate is fixed when you start your withdrawals, only updated for inflation. (“Fixed” refers to the fact that the withdrawal rate is fixed in terms of real dollars; or dollars of constant purchasing power. The withdrawals are allowed annual inflation adjustment.) + Pros - You know your income, it doesn’t change. + Cons - As we discussed in our post “[Does Using a Safe Withdrawal Rate Mean I Likely Die With No Money?](/post/does-using-a-safe-withdrawal-rate-mean-i-likely-die-with-no-money)“, this approach risks accumulating a large savings balance. * Percent of Portfolio Strategy (PPS): This strategy is simple; you take a fixed percent of the portfolio each year. + Pros - It is better at avoiding accumulation of wealth. + Cons - There is a significant chance of having income substantially lower than initially planned. This can be mitigated by adding a floor for the withdrawal amount. * Variable Withdrawal Strategies (VWS) - These build on the FWS and PPS by adding rules to allow changes in withdrawal rate; there are many variations. Commonly, they have your withdrawal rate increase or decrease in proportion to the investment return, capped at some amount each year. The changes in withdrawal rate *may* only occur if your actual withdrawal rate has gone above/below a “guardrail”. + Pros/Cons - This method is really just a more extreme version of PPS, and its Pros/Cons are similarly more extreme. ### Other Strategy Considerations The original 4% Rule prescribed a portfolio of 50% stocks and 50% intermediate-term U.S. government bonds. More modern strategies are less prescriptive in both investment options, as well as model inputs like withdrawal rate. Rate of failure is another input. The **original 4% rule was based around a 0% failure rate assumption**. Many modern methods are satisfied with **much higher failure rates**; read results carefully. --- ## Types of Analysis Before moving on, it is important to mention that when analyzing withdrawal strategies, there are two common methods: * Backtesting - (A.K.A Historical analysis) This method of analysis uses actual historical investment return data as the inputs to simulations to model effectiveness of any given withdrawal strategy. + Pros - You can model how a given strategy would have actually performed in the past, against difficult periods like the Great Depression and Great Financial Crisis. + Cons - There is very limited data. That, and people question how relevant data from the early 1900s is, as markets and regulatory requirements have changed greatly since then. * Monte Carlo - (A.K.A. statistical modeling) The core idea, named after the famous casino in Monaco due to its reliance on chance, is to run a model hundreds- or thousands-of-times, each time using different random values for the unknown variables (investment returns). + Pros - You can quickly model 1000s of unique scenarios. + Cons - It is not real data. It doesn’t answer the specific question “what if I had been using this prior to the Great Financial Crisis?”. Thus, when you are presented with results from models of withdrawal strategies, you have got to understand: withdrawal strategy, type of analysis, failure criteria, and investment strategy used. All will impact the results. --- ## Wait, Three General Types of Withdrawal Strategies? The three withdrawal strategies previously listed are all actually variations on a single algorithm. That single algorithm can be defined: * Pick a withdrawal rate used to determine withdrawals for the first period; periods will generally be one year. * Choose to allow the amount of withdrawals to be modified, or not. + If the withdrawalal amount is not modified, this is FWS, otherwise it is PPS/VWS. * If the withdrawalal amount modification is enabled: + Each year, a percentage of the investment return is used to modify your withdrawal rate. - The withdrawal rate modification may only occur if the actual withdrawal rate has crossed some high/low thresholds. These thresholds may be the same value, in which case withdrawal rate adjustments happen every period. - The change in withdrawal rate may be limited to a maximum positive or negative value. With that algorithm: * Fixed Withdrawal Strategies (FWS) - disables the investment return modifier, and thus the withdrawal rate caps are irrelevant. * Percent of Portfolio Strategy (PPS): sets the percent of investment return withdrawal rate modifier at 0, and no caps on withdrawal rate changes. * Variable Withdrawal Strategies (VWS): sets the percent of investment return withdrawal rate modifier and caps. I.E. investment return withdrawal: 50%, positive cap: 5%, negative cap: 2.5%. **All of these seemingly different withdrawal strategies are really the same algorithm, with different input variables**. --- ## Performance of FWS vs. PPS vs. VWS Below, we will analyze the three strategies. **Important modeling detail**: With variable withdrawal strategies, your income may be reduced considerably. For the purpose of this post, we have limited variable strategies such that **no withdrawal will be less than 90% of the initial withdrawal**. Full modeling details are at the end of the post. ### Chart Description For each model we will show the same two charts: * Balance Trajectories - these plots show the account balance for each of the 500 runs; failing runs are shown in red. * Distribution of All Annual Withdrawal Amounts - These plots are box plots showing the range of withdrawals that occurred in all 500 of the runs; distributions are shown for failing runs, passing runs, and all runs. * SWR is shown at the top of each plot; for PPS and VWS this is just the starting withdrawal rate, which is changing during the simulation. ### Fixed Withdrawal Strategy (FWS) ![image_1.jpg](image_1.jpg) ![image_2.png](image_2.png) Key observations: * There were 8 failures; success rate = 98.4%. * The withdrawals are a constant value: $50K every year. * The account value at the end of the simulation is frequently well over $2M, the **range is: $0 - $6,093,122.** ### Percent of Portfolio Strategy (PPS) ![image_3.jpg](image_3.jpg) ![image_4.png](image_4.png) Key observations: * There was one failure; success rate = 99.8%. * The median annual withdrawal increased from $50K to $53K; there are some withdrawals well over $160K. * The bottom quartile of withdrawals is between $45K-$48K; less than the initial withdrawal of $50K. * The final balance range has been **greatly reduced to $0 - $3,290,417.** ### Variable Withdrawal Strategy (VWS) ![image_5.jpg](image_5.jpg) ![image_6.png](image_6.png) Key observations: * There was one failure; success rate = 99.8%. * The median annual withdrawal increased to $62K, from $50K (FWS) and $53K (PPS); there are some withdrawals over $200K. * The bottom quartile of withdrawals is between $45K-$51K; less than the initial withdrawal of $50K. * Triggering the **failure was just barely avoided in several cases**. * The final balance range has been further **reduced to $0 - $1,213,253.** --- ## Takeaways * The models are not as different as they appear, and can generally be reduced to one algorithm. * Fixed withdrawal strategies have the advantage of a fixed income amount, at the expense of a possible large range of final account balance. * Variable withdrawal strategies (PPS and VWS) will, on average, allow you to live off of a higher income AND reduce the range of final account balance, but there is a significant chance you will need to live off of less income than initially planned for some period. (**Minimum withdrawal amount was fixed at 90% of the initial withdrawal in this model**). + Since the alternative to a 5% VWS, with similar success rate, is a 4.5% FWS, VWS seems like a clear winner; start higher, if it doesn’t work, cut back to the income an FWS would have provided. --- ## The King Is Dead! Long Live The King! So the 4(.5)% Rule may be dead, but the thing that replaced it is pretty much the same thing; the differences are values of the inputs to the models, portfolio selection, and what you consider failure. * The 4(.5)% Rule is still a great starting point for determining if you are nearing being financially ready to retire. + Note that all the cases modeled in this post started with a 5.0% withdrawal rate, because higher withdrawal rates increase failure rates. * If failure is income below what you initially determined, the 4(.5)% rule still works well. * If failure is passing with a very high account balance, and you are comfortable with possibly living off less than initially planned, then a variable strategy will suit you better. **Also consider a mixture of strategies**. I.E. start with FWS to guarantee income early in retirement. Then if you do see your balance accumulate significantly later in retirement, switch to a variable strategy where, even if you wind up on a “reduced income” path, your income is still acceptable. --- ## Model Details We wanted to get straight to model results, but here are details on the modeling for those interested. **General model inputs**: * The model is a Monte Carlo simulation with 500 runs, where each run models one 30 year retirement based on random samples of investment returns matching the designated portfolio. * Portfolio of 50% stocks and 50% investment grade corporate bonds. * The account starts with $1M. * Retirement lasts 30 years. * **Failure is if the withdrawal amount goes below 75% of the initial withdrawal amount, or the account balance drops below 5% of the initial balance.** + Failure criteria is probably what differentiates these models the most. With FWS, all that matters is the account doesn’t run out of money. With variable strategies, you may not run out of money, but you also may not be happy with substantially reduced income. **Model specific inputs**: * FWS - 5.0% withdrawal rate based on initial portfolio value; I.E. withdrawals are always $50K every year. * PPS - 5.0% withdrawal rate based on actual account value. + Withdrawals amounts are variable but limited to at least $45K (90% of the initial withdrawal amount). * VWS - 5.0% initial withdrawal rate. Each year the half of the investment return value is used to adjust the withdrawal rate for the next year. (I.E. if there is a 8% investment return, the withdrawal rate is increased 4%. Similar for negative returns.) + Withdrawal amount changes are capped at +5%/-2.5% + Withdrawals amounts are variable but limited to at least $45K (90% of the initial withdrawal amount). ### Algorithm Description * Starting withdrawal rate of 4.5%. * Each year that your investment return is positive, your withdrawal rate increases 50% of the investment return gain up to a maximum of 5% change in withdrawal rate. + I.E. your investments have a [real return](/post/understanding-safe-withdrawal-rate#real-return) of 10%, your withdrawal rate is allowed to increase 5% (50% of the 10% investment return). In this case, that increase in withdrawal rate is the maximum allowed. * Similarly, if investment return is negative, your withdrawal rate decreases by 50% of the (negative) return and is capped at a 2.5% reduction. * (The above caps are picked to try to allow you to enjoy gains, while not reducing income too far from the initial plan.) --- ## Variable Safe Withdrawal Rates: Ditch the 4% Rule for More Income URL: https://algorithmicfire.com/post/variable-withdrawal-rates-enable-increased-retirement-income Published: 2025-12-16 Category: Retirement Planning Abstract: Increase your retirement spending safely. See how dynamic variable safe withdrawal rates (VSWR) adapt to market conditions and outperform the rigid 4% rule. Date: 2025-12-16 Video: true Youtube_ID: https://youtu.be/sgJGfTvo4JM Duration: PT4M58S SEO_Title: Variable Safe Withdrawal Rates: Ditch the 4% Rule for More Income SEO_Description: Increase your retirement spending safely. See how dynamic variable safe withdrawal rates (VSWR) adapt to market conditions and outperform the rigid 4% rule. # Variable Withdrawal Rates Enable Increased Retirement Income ### But why do they work? Why not just start with a higher withdrawal rate? We’ve covered the 4% Rule in our post [Understanding Safe Withdrawal Rate](/post/understanding-safe-withdrawal-rate). The 4% Rule is one example of a Fixed Safe Withdrawal Rate. (“Fixed” refers to the fact that the withdrawal rate is fixed in terms of real dollars; or dollars of constant purchasing power. The withdrawals are allowed annual inflation adjustment.) The 4% Rule ([revised to the 4.5% Rule](https://www.forbes.com/forbes/2011/0523/investing-retirement-bill-bengen-savings-spending-solution.html)) has since been built upon by various other strategies that involve variable rates. (We will be publishing an extensive post on different strategies shortly.) A question this often raises is, “Why vary the withdrawal rate? Why not just start with a higher withdrawal rate?”. In our post [Safe Withdrawal Rate Failure](/post/safe-withdrawal-rate-failure), we showed how failures generally happen during prolonged periods of low or no [real returns](/post/understanding-safe-withdrawal-rate#real-return). (Where “real return” here means inflation adjusted return, as opposed to nominal return.) That implies that the longer a retirement is designed to last, the higher the probability of encountering such a period. We’ve modeled a fixed safe withdrawal rate, using a portfolio of 50% stocks and 50% investment grade corporate bonds, for durations of 10 to 40 years. The model is a statistical (Monte Carlo) model that uses 5000 runs at each duration and withdrawal rate. The success rate was recorded and charted below. ![image_1.jpg](image_1.jpg) * The green arrow shows a path of decreasing years in retirement. + Early on, the slope of the arrow is quite steep, indicating any increase in withdrawal rate comes with high risk. + Later on, the slope of the arrow is quite shallow, indicating withdrawal rate can be increased rapidly without taking on increased risk. * If you have enough money to live on about 3.5% or less of the portfolio, your retirement can last indefinitely. You will likely pass money on when you pass. * For a retirement shorter than 10 years, you can use a relatively high withdrawal rate; up to about 8%. It’s the nature of this curve that enables variable withdrawal rate strategies to work. Once you have succeeded at a given withdrawal rate, your remaining retirement years move you lower, and into yet safer (more green) space. Once well into safe space, you can then move right and increase your withdrawal rate while still staying at or near 100% predicted success. Another mechanism that enables higher withdrawals later in retirement is that once you have survived early [Sequence of Return Risk](/post/understanding-sequence-of-returns-risk), there is a possibility that you will have excess funds. The compounding of those excess funds can also enable higher than initially planned withdrawals, as the higher balance effectively reduces withdrawal rate. --- ## Does Luck Dictate Your Retirement? S&P 500 Returns & Market Timing URL: https://algorithmicfire.com/post/how-much-retirement-savings-can-be-accumulated-with-30-years-of-saving-1000month Published: 2025-12-09 Category: Saving Abstract: Does your retirement date depend entirely on luck? We analyze historical S&P 500 sequences to show how market timing dramatically affects your final retirement savings balance. Date: 2025-12-09 Video: true Youtube_ID: https://youtu.be/auetViFp6wo Duration: PT6M21S SEO_Title: Does Luck Dictate Your Retirement? S&P 500 Returns & Market Timing SEO_Description: Does your retirement date depend entirely on luck? We analyze historical S&P 500 sequences to show how market timing dramatically affects your final retirement savings balance. # How Much Retirement Savings Can Be Accumulated with 30 Years of Saving $1000/month? ### Historical analysis shows luck plays a huge role In our prior post, [It's OK to Put Off Retirement Savings Until You're Older - It's Easier Then...](/post/its-ok-to-put-off-retirement-savings-until-youre-older-its-easier-then), we analyzed saving at different rates, for different time periods, assuming [real returns](/post/understanding-safe-withdrawal-rate#real-return) of 7%. The astute reader, who read our post on [Sequence Of Returns Risk](/post/understanding-sequence-of-returns-risk), would have wondered how those results would have changed given actual historic returns, which is what is analyzed below. ## Savings Invested in the S&P500 ![image_1.jpg](image_1.jpg) The chart above is the result of simulating 30 years of saving $1000/month, savings are being invested in the S&P500, where savings start in each year from 1929-1995. Each line represents the savings growing over the 30 years for each potential savings starting year from 1929-1995. Note that real returns(inflation adjusted) **are used to keep dollar value constant** for all years. ![image_2.png](image_2.png) The chart above is a histogram of those returns, with the savings starting year shown in each histogram box. I.E. On the left we see savings starting in the years 1950, 1952-1955 had the lowest performance, with final savings balances for those years between $527K - $629K. Conversely, the late 1930’s was a great time to start saving, with years 1932, 1936, 1935, 1938, and 1939 resulting in savings balances of $2.27M - $2.47M. * The constant return analysis showed a final savings balance of $1.2M * Using actual historic returns shows final balances ranging from **$527K - $2.4M**, with a mean: $1.36M and median: $1.21M * Following the same savings methodology, **the luckiest people wound up retiring with 4.6 times more money than the most unlucky**. ($2.4M/$527K=4.6) ## Savings Invested 50%/50% (S&P500/Investment Grade Corporate Bonds) ![image_3.png](image_3.png) ![image_4.png](image_4.png) This is a repeat of the analysis above, but now assuming the money is invested in a mix of 50% S&P500 and 50% investment grade corporate bonds. (The actual simulation uses the 10YR U.S. Treasury rates + 1.0% as a proxy for investment grade corporate bonds. Reference: [AAA vs 10Y Yield](https://fred.stlouisfed.org/series/AAA10Y).) * Using actual historic returns with a mixed portfolio shows final balances ranging from $513K - $1.4M, with a mean: $861K and median: $843K * Interestingly, while the general results (mean, median, maximum) were better for an all stock portfolio, the worst case results were quite similar ($512K for the mixed portfolio vs $527K for all stocks). ## Takeaways It's important to always keep in mind that while a given portfolio has a long term average return, the following apply: * **Past results are not indicative of future results** * **Your mileage may vary** Fundamentally, don’t just assume you will get the average return for any given index or portfolio. History is long, but our lives are not; **plan for outcomes substantially different than average**. --- ## The Cost of Delaying Retirement Savings: Time Value of Money Explained URL: https://algorithmicfire.com/post/its-ok-to-put-off-retirement-savings-until-youre-older-its-easier-then Published: 2025-12-08 Category: Saving Abstract: Think you can catch up on retirement savings later? See the harsh compounding math of the Time Value of Money and why waiting even 5 years dramatically spikes your required savings. Date: 2025-12-08 Video: true Youtube_ID: https://youtu.be/v-IA0BPd7Io Duration: PT5M38S SEO_Title: The Cost of Delaying Retirement Savings: Time Value of Money Explained SEO_Description: Think you can catch up on retirement savings later? See the harsh compounding math of the Time Value of Money and why waiting even 5 years dramatically spikes your required savings. # It's OK to Put Off Retirement Savings Until You're Older - It's Easier Then... ### Except it's not. It is actually harder, unless you get lucky. ## Saving is Hard, Regardless of Age I recently had a conversation with a friend who explained she had used an online retirement calculator, and it said she needed $2M to retire. Her reaction: ### “*How am I going to save $2M?”* The number is not important; yours may be higher or lower. But the sentiment is common. My statement back to her, a bit flippant but not wrong, was “you don’t save $2M, you save maybe $500K, wait for the stock market to rip like it did from 2010-2024, and now you have $2M”. --- ## Retirement is a Time Value of Money Problem The Time Value of Money (TVM) is the core financial concept that a dollar today is worth more than a dollar tomorrow, primarily because money available now can be invested to earn returns, and grow through compound interest. TVM uses formulas to calculate Present Value (PV) and Future Value (FV) to help individuals and businesses make sound financial decisions. ### Future Value Defined `Future Value = (Present Value) * (1 + annual return)^(number of years)` Example: you expect 7% annual **real** return for 40 years. FV = **$1** \* (1 + 0.07)^40 = **$14.97** **Which means each dollar you spend at age 25 would have been worth $14.97 at age 65, in today's (or constant spending value) dollars. (**Note that 7% is the long term average real return on the S&P500.) ([Real Return](/post/understanding-safe-withdrawal-rate#real-return) is nominal return minus inflation; dollars of constant value. We discussed real vs nominal returns in our post on [Safe Withdrawal Rate](/post/understanding-safe-withdrawal-rate); see that for more information.) ## Saving Gets Easier as you Make More Money, Right? You will likely be making more money in the future, so saving IS easier in that sense. But the later you wait, the more you have to save, and the question is whether or not you can save enough more in the time left. ### How Much More Are You Likely to Make? For most people, **your real compensation will increase about a factor of 3 from the start of your career (early 20’s) to mid career** (around 50). This is what I observed during my career, and is backed up by this [ADP report](https://www.adpresearch.com/the-wage-lifecycle-is-more-complex-than-you-think/); and that largely holds true across the income scale. Beyond around age 50, real compensation actually starts to drop for most people. This can be for a number of reasons: people step away from higher pressure roles for quality of life, at that age you are likely working in an aging industry where compensation is lower, etc. There are some who will break beyond this; most won’t. --- ## Can You Save Enough Later In Life? Now we know how TVM works, and that we will make around 3x our starting compensation at 50. How does that play out for getting to a given retirement savings versus the number of years of saving? ![image_1.png](image_1.png) The chart above shows how a monthly savings of $1K-$5K, compounded at 7% return, for up to 40 years. ![image_2.jpg](image_2.jpg) I’ve converted the first chart to use a log scale for $, zoom into account balances > $1M, and to add a line showing the $2.5M target. **Critical Idea:** Note that as you move from right to left across the $2.5 line, the time between where the savings lines cross the $2.5M is getting shorter and shorter for constant changes in monthly contribution. (The arrows indicating the crossing points are closer together as you move right to left.) What this is saying is that **the longer you wait to start saving, the amount you have to save each month is rapidly increasing**. ### Paths to $2.5M in Retirement * Save $1000/month - after 40 years you have $2.56M. * Save $2000/month - after 30 years you have $2.43M. * Save $4000/month - after 22 years you have $2.52M. * Save $5000/month - after 20 years you have $2.63M. That last bullet drives home the Critical Idea above. An extra $1000/month savings reduces the time to $2.5M from 40 years to 30, but it also takes $1000/month more to reduce the time from 22 years to 20 years. --- ## Saving Gets Harder The Longer You Wait. Which seems easier: * Save $1000/month starting early in your career. * Save $5000/month starting mid-career. Given that most people will only be making about 3X their early compensation when they reach mid-career, saving **5X seems much more difficult**. This is the result of TVM. **Those early dollars saved generated free money.** --- ## How Much of the $2.5M Did You Save? Another way to look at this is to determine how much of the final $2.5M came from your contributions to savings, versus how much was a result of investment returns. * At the $1000/month for 40 years, **you contributed $480K** of the $2.5M. * At the $5000/month for 20 years, **you contributed $1.2M** of the $2.5M. --- ## Delaying Saving Makes it Harder * $1 today is worth much more in the future: $3.9 (20 years), $7.6 (30 years), and $14.9 (40 years) with 7% real return * You will likely be earning more mid-career than early career, by about 3x. * However, due to TVM, if you delay saving for retirement you will have to save a significantly larger portion of your income to reach your goal. While it is possible you will be someone who breaks way above the typical 3x mid-career compensation level, most won’t. Regardless of what people say, most don’t win in Vegas. Hope for the best, plan for the worst. --- ## Will You Die Broke Using a Safe Withdrawal Rate? The 4% Rule Myth URL: https://algorithmicfire.com/post/does-using-a-safe-withdrawal-rate-mean-i-likely-die-with-no-money Published: 2025-12-08 Category: Retirement Planning Abstract: Uncover the great retirement paradox. Learn why standard safe withdrawal rates (like the 4% rule) usually result in leaving a massive portfolio balance behind rather than dying broke. Date: 2025-12-08 Video: true Youtube_ID: https://youtu.be/0qbNdB1H5IU Duration: PT6M41S SEO_Title: Will You Die Broke Using a Safe Withdrawal Rate? The 4% Rule Myth SEO_Description: Uncover the great retirement paradox. Learn why standard safe withdrawal rates (like the 4% rule) usually result in leaving a massive portfolio balance behind rather than dying broke. # Does Using a Safe Withdrawal Rate Mean I Likely Die With No Money? ### No, in fact, you are likely to leave behind substantial assets. Plan for it. It is a common misconception that if you use a Safe Withdrawal Rate (SWR) approach to generating income from your investments, that you will die with zero money. But that is not the case. (If you’ve not read our initial posts on [Sequence of Returns Risk](/post/understanding-sequence-of-returns-risk) and [Safe Withdrawal Rate](/post/understanding-safe-withdrawal-rate), you might want to read those before continuing.) --- ## The Word “Safe” in SWR is the Key The work on SWR generally suggests an SWR that did not fail in historical backtests and/or a large number of simulations of various rates of return and variation on that return. As we show below, what happens when you pass with more than $0 is often a very large balance. --- ## Balance at Death Based on Simulations Simulations are a convenient way to analyze problems like this, and allow us to run a wide range of parameters like investment return and variation and generate a large number of outcomes. ![image_1.png](image_1.png) The chart above is a simulation of the balance of a retirement account, that starts with $1M, over a 30 year retirement. There are 500 runs of the simulation, and thus 500 simulated balances, for a SWR of 4.5% assuming average returns of 5.8% at a 6.1% stdev. (This is the approximate return and stdev for a portfolio of 40% stock, 60% high yield bonds.) In these simulated results, there was a **single failure** where the account balance reaches 0 before the 30 year retirement; that was at about 28 years. But there are times the balance is ~ $7M. Let’s look at histogram of the final balances for the above data as that is easier to understand the distribution of final account balances. ![image_2.png](image_2.png) There is a 20.8% chance ((15+42+47)/500) you pass with < $1M; which means there is a **79.2% chance you pass with > $1M** (or $1.095M to be precise). Further, there is a **15.4% chance you pass with > $2.9M** remaining in your account. --- ## Balance At Death Based on Historical Data The downside to a simulation is that it isn’t real data. The downside to historical data is that there isn’t that much history, and even then you have to question if what happened in financial markets 100 years ago still applies. That said, let's look at a similar simulation: starting balance $1M, 4.5% SWR, portfolio of 50% stocks and 50% investment grade corporate bonds, where corporate bonds are proxied by the yield on 10YR U.S. Treasuries + 1.0%. (Reference: [Aaa Corporate Bond Yield Relative to Yield on 10-Year Treasury](https://fred.stlouisfed.org/series/AAA10Y)) (This points out a complexity with historical data; just getting reliable data on bond rates, for a given rating, for the last 100 years is difficult.) ![image_3.jpg](image_3.jpg) ![image_4.png](image_4.png) Similar to the simulated results, there were no failures; but there were two results that had a final balance of < $40K. The results at the high end were not as optimistic. There is a **21.8% chance you pass with > $2.172M** remaining in your account; which is still not bad and certainly worth having a plan in place to handle that outcome. --- ## Is This Success, or Failure? There are plenty of people who would say that **dying with a large balance is failure**; they could’ve/should’ve lived a better life. That is a bit of the retirement conundrum. You want to have enough money to be safe for a range of outcomes, including significant recessions, stagnation, inflation over your entire retirement. But that means that if those scenarios don’t play out, you end up with more money than planned; maybe A LOT more. --- ## What To Do? Here are two options: * Make plans (early in retirement) for this eventuality. Decide who (people, charities, etc.) should get what, and work with a lawyer to have a trust in place to distribute the money per your wishes when you pass. * Periodically, maybe every 8-10 years, check in with your financial advisor. If your withdrawal rate has dropped substantially as a percent of your portfolio due to high returns, you might decide to up your withdrawal rate. + **DO NOT** increase your withdrawal rate each year your returns seem high. Part of the safety of the SWR approach is that years of high(er) returns create the buffer to withstand a downturn. * Consider a variable withdrawal rate. After writing this post, we have added a [Variable Withdrawal Rate](/post/variable-withdrawal-rates-enable-increased-retirement-income) post to our site. Variable Withdrawal rates help solve the problem of accumulating a large amount of wealth, but have their own set of challenges. See the post for more details.. --- ## Is Your Index Fund Actually Diversified? S&P 500 Concentration Risk URL: https://algorithmicfire.com/post/your-index-investments-likely-arent-as-diversified-as-you-think Published: 2025-12-06 Category: General Investing Abstract: Are you exposed to hidden portfolio risks? See how market-cap weighting creates high concentration risk in the S&P 500, and learn how to achieve true diversification. Date: 2025-12-06 Video: true Youtube_ID: https://youtu.be/dvY97EM5TPg Duration: PT5M31S SEO_Title: Is Your Index Fund Actually Diversified? S&P 500 Concentration Risk SEO_Description: Are you exposed to hidden portfolio risks? See how market-cap weighting creates high concentration risk in the S&P 500, and learn how to achieve true diversification. # Your Index Investments Likely aren't as Diversified as You Think ### Large cap indices are dominated by a few large stocks. What to know and how to get more diversified. Index investing gained popularity in the 1990’s and 2000’s, largely because it was an easy and cost effective way to get broad exposure to the stock market. Investors learned that being exposed to just a few stocks greatly increased their risks. Further, for anyone generating income from their portfolio, we previously posted on how volatility increases [Sequence of Returns Risk](/post/understanding-sequence-of-returns-risk) and the detriment that has on [Safe Withdrawal Rates](/post/understanding-safe-withdrawal-rate). --- ## How it Used to be, How it is Now ![image_1.jpg](image_1.jpg) Above is a table showing the top 10 companies in the S&P 500, by market capitalization (share price \* shares outstanding), from 2005-2025. (References: [1](https://www.goldmansachs.com/pdfs/insights/goldman-sachs-research/25-years-on-lessons-from-the-bursting-of-the-tech-bubble/redaction.pdf), [2](https://www.slickcharts.com/sp500)) * From 2005-2015, the 10 largest companies in the S&P 500 represented about 20% of the total weight of the index, versus over 40% in 2025. This demonstrates a significant increase in market concentration. * From 2005-2015, the 5 largest companies in the S&P 500 each represented 1.6%-3.3% of the index; versus 4.0%-7.2% in 2025. (The largest company, Nvidia, holds a weight of over 7%.) --- ## Some Background ### What is Market Capitalization? Market capitalization (frequently abbreviated “market cap”) is just the price of a stock multiplied by the total number of shares outstanding. Basically it is the price you’d pay for the company if you tried to buy all the shares. (Well, not really, because if you tried that, people would notice and that alone would move the price higher.) Fundamentally, it is a way to answer the question “how much does the stock market think this company is worth?” ### Types of Stock Indices Stock indices can be composed several ways; two common ways are market cap weighted and equal weight. * Market cap weighted index: Each stock's impact on the index price is “weighted” based on its market cap. If you own an ETF that tracks a market cap weighted index, your money is effectively buying an amount of stock in each company according to its weight in the index. * Equal weight index: All stocks have the same weight on the index price. If you own an ETF that tracks an equal weighted index, your money is effectively invested equally in every company in the index. * Both statements above have the caveat that indices are only periodically updated to reflect constituent weights; frequent changes would wreak havoc for fund managers. --- ## Why Does This Matter? All that brings us to this fact: ***If you hold an S&P 500 index fund (like [SPY](/report/SPY_STRATEGY_EXCESS_RETURN_MMA_investing.html), [VOO](/report/VOO_STRATEGY_EXCESS_RETURN_MMA_investing.html), [IVV](/report/IVV_STRATEGY_EXCESS_RETURN_MMA_investing.html), etc.), you have essentially invested 40+% of your money into just 10 companies.*** --- ## What About the Nasdaq 100? ![image_2.jpg](image_2.jpg) Nasdaq 100 index market cap and index weights of the 10 largest companies The Nasdaq 100 index is represented in the ETF world by ETFs like [QQQ](/report/QQQ_STRATEGY_EXCESS_RETURN_MMA_investing.html) and [QQQM](/report/QQQM_STRATEGY_EXCESS_RETURN_MMA_investing.html). The Nasdaq 100 index is a modified market cap weighted index; there are rules to limit the impact of a few large stocks on the index value. The **left table** is what the weights of each company would be on the index in a purely market cap weighted index. With “modified market cap weight“ it is actually the weights as shown in the **right table**. The top 10 stocks in the Nasdaq 100 index currently have an unadjusted market cap weight of roughly 70% of the index total (**left table above**), while their current adjusted weights “only” represent about 53% of the index (**right table above**). (References: [1](https://www.slickcharts.com/nasdaq100), [2](https://www.invesco.com/qqq-etf/en/about.html)) * **Even with the modified weights, 37% of the Nasdaq 100 Index is composed of just 5 stocks.** ### Details on Nasdaq 100 Index Methodology In 2023, Nasdaq implemented a “[special rebalance](https://ir.nasdaq.com/news-releases/news-release-details/nasdaq-100-index-special-rebalance-be-effective-july-24-2023)” to this effect; more on their methodology [here](https://indexes.nasdaq.com/docs/Methodology_NDX.pdf). There have only been 2 prior special rebalances. Key from the linked methodology document: * The aggregate weight of the companies whose weights exceed 4.5% may not exceed 48%. --- ## What to Do? If you were buying index funds 10 or more years ago, you likely didn’t make the purchase thinking: *I really want about half my money in 10 stocks, and the other half in diversified investment(s).* ### Simple Solution The indices that stand out as having a problem with diversification are the S&P 500, Nasdaq 100, and Nasdaq Composite. The simple solution to this is to recognize that market cap weighted index investing is not as diversified as it once was, and find ETFs that use equal (or other suitable) weighting. Examples: * [RSP](/report/RSP_STRATEGY_EXCESS_RETURN_MMA_investing.html) - Invesco S&P 500 Equal Weight ETF * [QQQE](https://finance.yahoo.com/quote/QQQE/) - Direxion NASDAQ-100 Equal Weighted Index Shares Another solution is an ETF that excludes the largest stocks from the index. An example of this is [XMAG](https://finance.yahoo.com/quote/XMAG/) (Defiance Large Cap ex-Mag 7 ETF); “*The First ETF Offering Exposure to the S&P 500 Excluding the “Magnificent 7” Tech Giants*“. I expect we will see more products like this as demand for investment diversification will drive product development in the ETF space. **(The above products are for reference to the type of product suggested; this is not an endorsement of any of the products.)** Fundamentally, you first have to recognize the problem. Hopefully this post helped with that. Now you need to review your investment holdings and decide what, if any, actions to take. --- ## Safe Withdrawal Rates (SWR) for Short Retirements: 10 to 25-Year Horizons URL: https://algorithmicfire.com/post/safe-withdrawal-rate-for-shorter-retirements Published: 2025-12-05 Category: Retirement Planning Abstract: Retiring with a shorter time horizon? Analyze the historical data showing how Safe Withdrawal Rates (SWR) can safely increase for 10, 15, 20, and 25-year retirements. Date: 2025-12-05 Video: true Youtube_ID: https://youtu.be/dZ0BUUhZmBQ Duration: PT7M53S SEO_Title: Safe Withdrawal Rates (SWR) for Short Retirements: 10 to 25-Year Horizons SEO_Description: Retiring with a shorter time horizon? Analyze the historical data showing how Safe Withdrawal Rates (SWR) can safely increase for 10, 15, 20, and 25-year retirements. # Safe Withdrawal Rate For Shorter Retirements ### Not everyone needs a 30 year retirement. How does Safe Withdrawal Rate change for shorter retirements? ## How Long is Retirement? ### 30 Years? * 30 Years is a common assumption. * The reasoning is that most people wait until they are eligible for Social Security and Medicare, which historically has been 65. * Life expectancy past 65 is low. SSA (Social Security Administration) estimates that only 1 in 7 live to 95; that is 14%. (Reference: When to Start Receiving Retirement Benefits ### Why it Might be Less? * You worked until very late in life. * You’re terminally ill. * You’re only using retirement funds as a bridge to something else (inheritance, Social Security, pension, etc.) --- ## This is Part Two - Please Read Part 1 If you haven’t read our prior posts on [SWR](/post/understanding-safe-withdrawal-rate) and [SWR Failure](/post/safe-withdrawal-rate-failure), **please do so now**. Those posts provide detail about the simulation and charts shown next. --- ## Simulation Results ### Reminder of what is shown… #### Heatmaps * Red points indicate failure (the account ran out of money), green points indicate success. * These are **based on SIMULATED** returns given an asset class's average return and stdev; these use simulated returns, not historical data. #### Historical Data * These charts show the [real return](/post/understanding-safe-withdrawal-rate#real-return) for a given investment strategy versus time, based on historical data, with success/failure for a given retirement start mapped on top of that in red/green --- ## Charts for a 4.5% SWR for 10, 15, 20 and 25 Year Retirements See chart titles for details (SWR, retirement years, etc.) ### ![image_1.jpg](image_1.jpg) ### SWR: 4.5%, Retirement Duration: 15 years ![image_2.jpg](image_2.jpg) ### SWR: 4.5%, Retirement Duration: 20 years ![image_3.jpg](image_3.jpg) ### SWR: 4.5%, Retirement Duration: 25 years ![image_4.jpg](image_4.jpg) ## What these charts show * For a retirement of 15 years or less, the investment space is largely “green”. * For 20-25 years, investments with a stock profile (return and stdev) are becoming risky. With an SWR of 4.5% being so successful for short periods, let’s look at a 6.0% SWR and 7.0% SWR for just 10-15 years. --- ## Charts for 6.0% and 7.0% SWR at Shorter Retirement Durations See chart titles for details (SWR, retirement years, etc.) ### 6.0% SWR, Retirement Duration: 10 years ![image_5.jpg](image_5.jpg) ### 6.0% SWR, Retirement Duration: 15 years ![image_6.jpg](image_6.jpg) ### 7.0% SWR, Retirement Duration: 10 years ![image_7.jpg](image_7.jpg) ### 7.0% SWR, Retirement Duration: 15 years ![image_8.jpg](image_8.jpg) ## What these charts show As you might expect, the shorter retirement periods allow for substantially higher withdrawal rates. The heatmaps use simulated data based on an asset class's [real return](/post/understanding-safe-withdrawal-rate#real-return) and stdev. Let’s take a look at how some of these scenarios play out against **historic data**. --- ## Historic Simulation - 20 Year Retirement, Starting in 1920, 4.5% SWR See chart titles for details (SWR, retirement years, etc.) ![image_9.png](image_9.png) ![image_10.jpg](image_10.jpg) These charts are for a 4.5% SWR, for a 20 year retirement, invested 100% in the S&P500. (We simulate a retirement for every year, starting in 1920, until 2015. For years after 2010, less than 20 years are simulated.) * We ran a 15 year retirement and it had zero failures since 1920. * The chart of real return for a 20 year retirement shows a single failure for retirement starting in 1969. (See the red line segment in the otherwise green line.) * The balances chart (balances from each simulation starting in 1920) shows the failure and some lower balances. * 100% stocks is not a recommendation, but used to show that at this shorter retirement duration a portfolio can take more risk with a 4.5% SWR. Running against historic data shows the portfolio was a bit more robust than when based on simulated returns. ## Historic Simulation - 10 Year Retirement, Starting in 1920, 8.0% SWR See chart titles for details (SWR, retirement years, etc.) ![image_11.png](image_11.png) ![image_12.jpg](image_12.jpg) These charts are for a 8.0% SWR, for a 10 year retirement, invested 100% in the S&P500. (We simulate a retirement for every year, starting in 1920, until 2015. For years after 2010, less than 20 years are simulated.) * We ran a 10 year retirement at **7.0% SWR and it had zero failures** since 1920. * The **8.0% SWR** chart of real return shows **two failures** for retirement starting in 1973 and 2000. (See the red line segment in the otherwise green line.) * The balances chart (balances from each simulation starting in 1920) shows the failures and some lower balances. * Again, this is not a recommendation, but used to show that at this shorter retirement duration a portfolio can take more risk with a higher SWR. --- ## Key Takeaways * Retirement duration of less than 30 years may be appropriate for some. * For these shorter durations, SWR can be increased, and the portfolios can withstand higher volatility. *“Just because you can, doesn’t mean you should”* Again - these are not recommendations. Just because simulations and historical data suggest you could take on more risk, doesn’t mean you should. The optimal approach is generally to take on the LEAST risk, at a real return required to get to the desired SWR. --- ## When the 4% Rule Fails: Safe Withdrawal Rate Failure Rates by Retirement Length URL: https://algorithmicfire.com/post/safe-withdrawal-rate-failure Published: 2025-12-05 Category: Retirement Planning Abstract: Historical SWR failure rates for 30, 40, and 50-year retirements. See exactly how often the 4% rule runs out of money — and what withdrawal rate has a 95%+ success rate. Date: 2025-12-05 Video: true Youtube_ID: https://youtu.be/hwfczMF1IdY Duration: PT7M35S SEO_Title: When the 4% Rule Fails: Safe Withdrawal Rate Failure Rates by Retirement Length SEO_Description: Historical SWR failure rates for 30, 40, and 50-year retirements. See exactly how often the 4% rule runs out of money — and what withdrawal rate has a 95%+ success rate. # Safe Withdrawal Rate Failure & Success Rate Dashboards ### What happens if your Safe Withdrawal Rate (SWR) is too high? A look at history and some tips for recovery. ## Withdrawal Success Rate Dashboards & Historical Success Rates In our post about [Safe Withdrawal Rate (SWR)](/post/understanding-safe-withdrawal-rate), we showed relatively high success rates\* for a 5% SWR with a mixed portfolio of stocks/bonds. But that was using simulated returns. ![image_1.png](image_1.png) This chart shows the success rates using historical data going back to 1920. This portfolio is using 50% S&P500, and 50% bonds. But what does 90% success for a 5% SWR mean? What does failure look like? \* This is not an endorsement for a 5% SWR. The intent is to show what happens when your SWR is too high. --- ## Some Simulation Details The modeled portfolio consists of 50% S&P500, and 50% bonds. (The actual simulation uses the 10YR U.S. Treasury rates + 1.0% as a proxy for investment grade corporate bonds. Reference: [AAA vs 10YR Yield](https://fred.stlouisfed.org/series/AAA10Y)) ![image_2.png](image_2.png) The chart shows nominal and [real returns](/post/understanding-safe-withdrawal-rate#real-return) of this portfolio since 1913. A 30 year retirement is modeled for years prior to 1995 after which the model stops at 2025. ### Inflation matters Note that in the 1960’s, nominal returns seem to follow the general upward trend, but the [real return](/post/understanding-safe-withdrawal-rate#real-return) is flat. The nominal returns were similar to inflation; purchasing power stayed flat. --- ## Failures Aren’t Random ![image_3.png](image_3.png) This chart shows success/failures mapped onto the [real return](/post/understanding-safe-withdrawal-rate#real-return) data; red means a retirement that started that year ran out of money. Note that the “failure year” is the starting year of retirement, not the year the balance hit zero. ### Key finding The failures are clustered: 1937, 1962-69 (most years), 1973, 2000 --- ## Failure Details * Failures occurred when retirement started in the years: 1937, 1962, 1964, 1965, 1966, 1967, 1968, 1969, 1973, 2000 * Years until failure: 24, 29, 29, 26, 24, 28, 24, 23, 28, 24 * 4 of 10 failures occurred in years 28-30; so close… * All failures occurred at year 23 or later. ### Critical insight The failures occurred deep into retirement, long after the SWR was chosen. It would have been easy to not see failure coming until it was too late. --- ## Key Finding The failures all occur when retirements start prior to a long period of near zero real returns. See the following charts... ![image_4.png](image_4.png) ![image_5.png](image_5.png) ![image_6.png](image_6.png) --- ## How did you go bankrupt? *Two ways. Gradually, then suddenly* *Ernest Hemingway, The Sun Also Rises, 1926* --- ![image_7.jpg](image_7.jpg) ![image_8.png](image_8.png) The above charts show the simulated balance vs time; the top chart is all runs, while the bottom chart is ONLY failing runs. At 15 years into retirement (180 months), the failing simulations had depleted the account to around half it starting value --- ## Insights on a 5% SWR, and 90% Success ### 5% is robust-ish * It survived the Great Depression years. * There were three periods of extended low [real return](/post/understanding-safe-withdrawal-rate#real-return) that produced clusters of failures. ### Beware of low real returns * History shows that the periods of low [real return](/post/understanding-safe-withdrawal-rate#real-return) have been more dangerous than large corrections which recover (Depression, Great Financial Crisis). * Keep an eye on REAL returns and adjust spending/income if needed. ### Timing * You may not time the market, but it may time you. * Timing plays a critical role in having a successful retirement. --- ## What if Timing Fails? * Compare your SWR inflation adjustments to investment returns. If real returns are near zero for more than a few years, reduce spending or increase income (go back to work). * Going back to work doesn’t have to mean full time and your old career. You need enough to get your SWR down enough to ride out the economic cycle. * Reducing your SWR from 5% to 3.5% means you need to generate 30% of your income. (5%-3.5%)/5% = 30%. * Make sure you are considering all your investment options. Just because your economy is bad doesn’t mean other markets aren’t doing better. --- ## Key Takeaways This analysis focuses on a 5% SWR, only to demonstrate what failure looks like. * Failure is likely to happen deep into retirement, at a time you may not be able or willing to return to work. * Keep your SWR conservative (not 5%) and aim to allow a better lifestyle to come from a conservative SWR on a balance that has compounded, and thus you are getting more income from the conservative SWR. * Monitor real returns to make sure your withdrawal rate is actually safe; adjust spending/income if needed. * Monitor returns in alternative investments/markets, stay diversified. --- ## Adjusting Your SWR There are several proposals for how to deal with failing scenarios, generally using some type of “guardrails” approach. The idea is to formulaically change your SWR based on particular rates of return. Our preference, aligned with our “keep it simple, keep it memorable” approach is to reevaluate your withdrawal rate each year and verify it is still a SWR; in particular take action if your withdrawal rate increased too much due to loss of principal. That begs the question, how does SWR change as retirement horizon reduces. That will be the subject of one of our next posts. --- ## If 5% Isn’t so Bad, What About 6%? ![image_9.png](image_9.png) ![image_10.png](image_10.png) The success rate drops to 67%, the failure clusters get longer, and failure occurs as soon as about 16 years. Kids - **DO NOT try this at home**… --- ## Wait - What Were The Best Cases? ![image_11.jpg](image_11.jpg) Earlier we showed the chart above, with account balances plotted vs time. The astute reader will ask “*there are cases where the account value INCREASES to $2M-3M?*”. The answer is “yes”. More details regarding that in an upcoming analysis. --- ## Safe Withdrawal Rate (SWR) Explained: Meaning, 4% Rule & FIRE Calculator URL: https://algorithmicfire.com/post/understanding-safe-withdrawal-rate Published: 2025-12-05 Category: Retirement Planning Abstract: What is SWR in finance? The Safe Withdrawal Rate tells you how much to withdraw annually without running out of money. Run our interactive SWR calculator to test your retirement plan. Date: 2025-12-05 Video: true Youtube_ID: https://youtu.be/QCoQnc6OuCM Duration: PT7M17S SEO_Title: Safe Withdrawal Rate (SWR) Explained: Meaning, 4% Rule & FIRE Calculator SEO_Description: What is SWR in finance? The Safe Withdrawal Rate tells you how much to withdraw annually without running out of money. Run our interactive SWR calculator to test your retirement plan. # What is SWR in Finance? Safe Withdrawal Rate Meaning & Guide ### Safe Withdrawal rate (SWR) is the key to answering “Am I (financially) ready to retire?” ## What is SWR? Safe Withdrawal Rate Meaning Explained The Safe Withdrawal Rate (SWR) is the percentage of your retirement portfolio you can withdraw annually, adjusted for inflation, without depleting your savings over a typical 30-year retirement. ## The 4% Rule Financial planner William Bengen established the widely-cited 4% rule (SWR of 4%) through historical market analysis, providing a benchmark for sustainable retirement withdrawals. More recently Mr. Bengen has suggested 4.5% is a better number… --- Reference: [Wikipedia - William Bengen](https://en.wikipedia.org/wiki/William_Bengen) More information: [The Retirement Spending Solution](https://www.forbes.com/forbes/2011/0523/investing-retirement-bill-bengen-savings-spending-solution.html) --- ## Why Not a Higher SWR? People frequently think a SWR of 4%-4.5% sounds low, since the S&P 500 has real returns around 7%. With constant (no variability) returns, the SWR could be significantly more than 4%. ## Sequence of Returns Risk When an appropriate standard deviation is applied to reflect real-world market volatility, higher SWRs frequently fail. See our content on Sequence of Returns Risk for more information: [Understanding Sequence of Returns Risk](/post/understanding-sequence-of-returns-risk) --- ## Real vs. Nominal Returns ### Nominal Return The percentage change in your investment’s value before accounting for inflation, taxes, or fees. This is the “headline” number you’ll see reported. ### Real Return Your actual purchasing power gain, calculated as nominal return minus inflation. This is what truly matters for your retirement lifestyle. ### Example: 1. S&P 500 starts at 1,000 2. Ends year at 1,100; **Nominal return = 10%** 3. Inflation was 4%; **Real return = 6%** ## Important Note: Real Returns in This Analysis Throughout this presentation, all financial figures and analyses, including withdrawal rates and portfolio values, are expressed in terms of real returns. This means all dollar amounts are adjusted for inflation and represent constant purchasing power, equivalent to today’s money. This approach is crucial for retirement planning because it provides a clearer, more accurate picture of what your money can truly purchase in retirement. By accounting for inflation, we ensure our discussions reflect actual buying power, allowing for more realistic and actionable financial strategies. --- ## Understanding Standard Deviation Throughout this presentation, we will frequently refer to Standard Deviation (abbreviated stdev or STDEV) as a key measure of investment risk. It quantifies the amount of variation or dispersion of a set of values, giving us insight into how much an investment’s returns fluctuate from its average. In simple terms, standard deviation tells you how spread out the numbers are in a data set. A low standard deviation indicates that data points are generally close to the mean, while a high standard deviation indicates that data points are spread out over a wider range of values. For a normal distribution, understanding standard deviations helps predict the probability of outcomes: * 68.2% of values fall within 1 STDEV * 95.4% of values fall within 2 STDEV * 99.7% of values fall within 3 STDEV --- ## Mechanics of SWR Simulations ### Generate data * Select an average real rate of return and return STDEV. * Generate 30 years of random data for that return and stdev. ### Simulate account * Apply the 30 years of data to an account balance that has annual withdrawals at the given SWR. ### Success/Failure * Success is the account balance is > 0 at the end of the simulation; failure is a zero or negative balance. Repeat the above 500 times for every SWR/return/STDEV combination, recording the **ratio** of Success/Failure. --- ## SWR Simulation - 4.5% SWR ![image_1.jpg](image_1.jpg) Red points indicate the account ran out of money during a 30 year retirement at that return/STDEV. I.E. at a real return of 5%, with a 5% stdev, the success rate is high; while the same return at 10% stdev (or more) has a low success rate. **Critical Insight:** High returns don’t guarantee success. --- ### SWR Simulation - 6.0% SWR ![image_2.png](image_2.png) At this higher SWR, there is little space for success. Where can you get 5% real return at near 0 stdev? Or 7% real return at 4% stdev or lower? **Question**: How do investment options map into this space? --- ## Historical Real Returns ### High Quality Corporate bonds Based on data from 2005-NOV 2025 * Real mean return: 1.3% * stdev: 1.7 * Ref: ### High Yield Corporate bonds Based on data from 2005-NOV 2025 * Real mean return: 5.4% * stdev: 2.7 * Ref: ### S&P500 Based on data from 1991-NOV 2025 * Real mean return: 7.6% * stdev: 17.2% * Real CAGR: 6.1% Compound Annual Growth Rate (CAGR) is generally lower than the arithmetic mean (or average) return, especially in volatile markets, because CAGR accounts for compounding while the arithmetic mean does not. See our content on [“Average Annual Return, It is Not What You Think”](/post/average-return-its-not-what-you-think) --- ## Investment Options Overlayed On The 4.5% SWR Simulation ![image_3.jpg](image_3.jpg) ### Key observations: * Treasury and/or investment grade bonds don’t have enough return to be successful * 100% stocks has too much volatility to be successful * A mix of investments is needed to reduce volatility in order to be successful (Current yield spreads are lower than shown.) ## Simulated Sequences of Returns with Mixed Portfolio ![image_4.jpg](image_4.jpg) This plot shows the results of 500 simulated 30 year retirements using the mixed portfolio return and stdev. Note: a single failure, but many cases where the portfolio grows, up to ~ $10M ## Simulated Sequences of Returns with 100% Stocks ![image_5.png](image_5.png) This plot shows the results of 500 simulated 30 year retirements using returns of the 100% stock portfolio. Note: MANY failures. --- ## Key Takeaways: ### Diversification Over High Returns Diversification and managing return variability are more crucial than solely chasing the highest returns, as demonstrated by the diversified portfolio’s superior position. A thoughtful asset allocation strategy, balancing risk and reward, is paramount. ### The Value of Anti-Correlated Assets Anti-correlated assets (like stocks and bonds) move in opposite directions during different market conditions, which reduces overall portfolio variability. This reduced variability is what creates the superior success rates we see in diversified portfolios - it’s not just about mixing assets, but specifically combining assets that don’t move together. --- ## How to Use (and Not Use) This Information ### Success Depends on Managing Return Variability * A successful retirement plan is highly sensitive to both investment returns AND the variability of those returns. * Diversify with anti-correlated assets to try to reduce return variability. ### Understanding Model Limitations * The models used assume investment returns follow a “normal distribution” (a specific statistical pattern). In reality, market returns don’t always behave this way, even with portfolio diversification. * Real economies are cyclical, leading to periods of expansion and contraction. This means your personal results may be biased by market timing, but predicting these biases is impossible. ### Practical Application Guidance **DO NOT**: Rely on this analysis to pick exact Safe Withdrawal Rates (SWRs), precise return targets, or specific standard deviations for your personal financial plan. **DO**: Focus on understanding the underlying principles of investment variability and its impact. Use these insights to inform a flexible and adaptive retirement strategy that can adjust to evolving market conditions and personal circumstances. --- ## Sequence of Returns Risk (SRR) Explained: Protect Your Retirement Portfolio URL: https://algorithmicfire.com/post/understanding-sequence-of-returns-risk Published: 2025-12-05 Category: General Investing Abstract: What is sequence of returns risk? Discover why the order of your investment returns matters more than average returns in early retirement, and learn rules to shield your nest egg. Date: 2025-12-05 Video: true Youtube_ID: https://youtu.be/vPo0R9Vt910 Duration: PT5M32S SEO_Title: Sequence of Returns Risk (SRR) Explained: Protect Your Retirement Portfolio SEO_Description: What is sequence of returns risk? Discover why the order of your investment returns matters more than average returns in early retirement, and learn rules to shield your nest egg. # Understanding Sequence of Returns Risk ### A critical risk factor that can make or break your retirement portfolio, regardless of average returns ## What is Sequence of Returns Risk? It is the danger that poor market performance early in retirement severely depletes your portfolio. * The order of investment returns is critical when you are making withdrawals. * A market downturn early in retirement has a greater impact than a later one. * Early poor returns can create a deficit that is difficult to overcome. This risk primarily applies once you’ve retired and are generating income from your portfolio. Early poor returns create a deficit that compounds with each withdrawal as losses get locked in. ## Example - Initial Loss ![image_1.png](image_1.png) ### Starting Scenario * Initial Balance: $1,000,000 * Annual Withdrawal: $100,000 ### Simulated Market Returns * Year 1: -50% loss * Years 2–4: 0% change * **Final Year: +100% gain** **Critical Insight**: A significant early market loss, combined with ongoing withdrawals, severely depleted the portfolio. The early withdrawals meant less capital remained to benefit from the final year’s 100% recovery, resulting in a much lower final balance than the returns alone would suggest. I.E. withdrawals “locked in” the losses. ## Example - Initial Gain ![image_2.png](image_2.png) ### Starting Scenario * Initial Balance: $1,000,000 * Annual Withdrawal: $100,000 ### Simulated Market Returns * Year 1: +100% gain * Years 2–4: 0% change * Final Year: -50% loss **Critical Insight**: The opposite is true with high gains. With no net return, and annual withdrawals of $100K, you would expect a balance of $500K. But the account has a higher balance as the withdrawals were at an inflated account balance. ## Key Takeaways ### Timing matters The order in which your investment returns occur is as critical as the average return, particularly when withdrawing funds for income. ### Volatility and Withdrawals High-volatility, high-return investments may leave your portfolio poorer than lower-return investments if you are drawing down the principal for income. ### Mitigation Diversified portfolios (including stocks, bonds, gold, etc.) can be used to reduce volatility and, consequently, mitigate Sequence of Returns Risk. A successful retirement has an element of luck, as the sequence of returns, not just the average, significantly affects your final account balance. ***You may not time the market, but it may time you.*** --- ## Arithmetic Average Return vs CAGR: How to Calculate Investment Growth URL: https://algorithmicfire.com/post/average-return-its-not-what-you-think Published: 2025-12-05 Category: General Investing Abstract: Don't let average returns mislead you. Learn the difference between arithmetic average returns and CAGR (Compound Annual Growth Rate) with real formulas and examples. Date: 2025-12-05 Video: true Youtube_ID: https://youtu.be/7Xhw7k8zYRo Duration: PT6M27S SEO_Title: Arithmetic Average Return vs CAGR: How to Calculate Investment Growth SEO_Description: Don't let average returns mislead you. Learn the difference between arithmetic average returns and CAGR (Compound Annual Growth Rate) with real formulas and examples. # Average Return - It’s Not What You Think ### Compound Annual Growth Rate (CAGR) is the proper way to express investment returns over a period, not (arithmetic) average If you are used to averaging the last few months/years of an investment to determine your “average return”, you are not getting the answer you want. Below will explain why and show you how to calculate CAGR. ## Let’s start with a simple example: A stock you own goes from $100 to $50. Your gain was ($50-$100)/$100 = -50%. Now the stock goes from $50 to $100. Your gain was ($100-$50)/$50 = 100%. You average **arithmetic gain was 25%**: (-50% + 100%)/2 = 25%. But the stock started at $100, and ended there. **There was no gain.** Claiming a gain of 25% is very misleading. ## Investments Compound The correct way to calculate investment returns is by multiplying successive gains/losses. Using the prior example, the calculations are: $50/$100 \* $100/$50 = 1.0 Each period's gain/loss is calculated as the ratio of (ending value)/(starting value). To get the net gain/loss, multiply the values from all periods. CAGR is the calculation to determine average growth rate, which is the value most people think of when they say “average return”. CAGR answers the question “If I earn X% for Y% periods, how much did my balance change”. ## CAGR Calculation Explained * CAGR is the Compound Annual Growth Rate. * This calculation shows the true annualized growth rate. * It calculates the geometric mean of investment returns. * CAGR uses the formula (End Value/Start Value)^(1/Years) - 1. ## CAGR Example You bought a stock for $100 in 2010. You sold the stock for $280 in 2020. CAGR = ($280/$100)^(1/(2020-2010)) - 1 = .108 = 10.8%. Or, on average, each year the balance increased by 10.8%. The reverse of the calculation is: ( 1 + 0.108)^10 = 2.8 I.E. the value of the investment increased by a factor of 2.8 over the 10 years. ## CAGR - Generally Lower Than Arithmetic Average Below is a histogram of the output from 10,000 runs of a simulation that generates 30 year long random sequences of returns with arithmetic mean 7.0% (stdev 17%). ![image_1.png](image_1.png) The arithmetic average of returns is 7.1%, yet the average CAGR is just 5.7%. Using the **arithmetic average** for this data **overstates annual returns by 1.4%**. This demonstrates how arithmetic averages generally overstate returns. ---