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.

In our previous post (“U.S.-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, 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 methods have been heavily researched and the results support the methods as legitimate. Here is one example: Hurst, Ooi, Pedersen, "A Century of Evidence on Trend-Following Investing", 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 mis-informed, 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?

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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 (Nasdaq 100 index ETF),and (yellow) the gain from trading using a trend following method. 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 method 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 Two Trend Following Methods

With that understanding of what we hope to achieve, we present results from 2 trend following methods:

  • Excess Return. This approach compares the one-year moving average (MA) of a security against the one-year MA of a ‘risk-free’ benchmark (in this case, 10-Year U.S. Treasuries). If the security is outperforming the benchmark on a trend basis, it triggers a ‘buy’; if it falls behind, it triggers a ‘sell’ to preserve capital.
  • Moving Average (A.K.A The Golden Cross/Death Cross). This is a classic trend-following indicator using the 50-day and 200-day moving averages. A ‘buy’ is triggered when the short-term momentum (50-day) climbs above the long-term trend (200-day), signaling a potential Golden Cross. Conversely, a ‘sell’ is triggered when short-term momentum breaks below the long-term trend.

Both methods will invest in U.S. 10-Year treasuries when not holding the target security.

It should be noted that these are just two methods in the general realm of trend following. There is limitless range of possible methods that use differing strategies, including but not limited to: different time frames, different types of moving averages (simple, exponential, weighted), stop-loss value or no use of a stop-loss, possibly incorporating use of a “risk-free” investment and selection of that investment, etc.

Quick-Buy and Stop-Loss Solve Reaction Time Problems

Standard moving averages are slow to react. This can be a problem during moves both up and down. To solve this, we’ve added two additional algorithms: quick-buy and stop-loss:

  • Quick-Buy: if a security closes higher for seven consecutive trading days, the algorithm triggers a buy signal regardless of the longer-term averages. This ensures we aren’t left on the sidelines during a ‘V-shaped’ recovery. (The quick-buy transitions to a normal buy signal if the moving averages cross, and sells on 5% drop in the security while in the quick-buy.)

  • Stop-loss: A stop-loss is a risk management tool that automatically triggers a sell order for a security once it drops to a predetermined price, limiting potential losses and preventing emotional decisions.

    • The results presented used a 70% stop-loss.

That is the extent of the algorithms:

  • Buy/sell based on moving averages crossing.
  • Possibly buy when a security is consistently advancing.
  • Possibly sell a security if it drops significantly and too fast for a reasonable response from the moving averages.

Performance

To validate these strategies, we backtested both algorithms against the 54 largest ETFs by market capitalization, comparing their performance directly to a traditional buy-and-hold approach. (The list was originally 55, but we had to remove IBIT for not having enough history.)

This list is mostly stock ETFs, but there are a few bond funds as well. We chose to NOT edit the list as we want it to be clear we didn’t filter the list to funds with favorable results. (Full data and the ETF list are provided at the end of this post.)

The testing period for each fund spans its entire available history, adjusted for the ‘lead-in’ time required to calculate our moving averages.

  • The lead-in time is different for the two methods we are using. We used the longer lead-in for both methods so that the analysis is not biased by differing time periods.

We will use the following benchmarks:

  • Maximum drawdown: A key risk metric showing the largest percentage drop from a peak value to a subsequent trough (low point) in an investment’s history, revealing the worst potential loss an investor could have experienced, expressed as a negative percentage
  • CAGR: (Compound Annual Growth Rate) A financial metric showing an investment's average yearly growth over a period.
  • Sharpe ratio: A measure of investment efficiency. It reveals whether your returns are a result of smart risk-taking or simply excessive volatility. A higher ratio means more “reward per unit of risk.”

Maximum Drawdown

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For each ETF, using each method, the maximum drawdown was determined and is charted above. Note that the drawdowns are significantly reduced using either trend following strategy.

  • The median is ~ -30% for both trend following methods, but -50% for buy-and-hold.

  • The worst case drawdowns were: excess return (-40%), moving average(-46%), buy-and-hold(-83%).

    • Losses larger than the stop loss occur when a security closes higher than the stop loss, then opens the next trading period lower than the stop loss.

  • Buy-and-hold had about a -60% drawdown during the Great Financial Crisis (GFC) if you held QQQ (Nasdaq 100 index ETF), compared to -33% for the excess return method.

CAGR

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Again, for each ETF, using each method, the CAGR was determined and is charted above.

  • The excess return method matches buy-and-hold (9.9% median CAGR)
  • The moving average method trails both (7.8% median CAGR).

This was as we expected and mentioned earlier; trend following offers some insurance, but insurance usually comes at some cost. In this case, the cost of reduced drawdowns is reduced CAGR for the moving average method.

But is the cost worth it?

Sharpe Ratio

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Sharpe ratio says “yes”, the reduced gains are worth the reduced volatility, as sharpe ratio for both trend following methods are substantially higher than buy-and-hold.

  • The CAGR for the moving average method was lower than buy-and-hold, but the sharpe ratio, an indication of risk-adjusted return is higher than buy-and-hold.
  • This indicates that both trend following methods have a risk-adjusted return that is higher than buy-and-hold.

Takeaways

  • Trend following can be used to reduce the probability of holding securities into a significant downturn.

  • The reduction in risk may come at the expense in reduction of CAGR.

    • The sharpe ratios indicate better risk-adjusted return for trend following as compared to buy-and—hold

We performed this same analysis on a group of bond ETFs, as well as a group of large market capitalization stocks, see below to get access to those results.

A Practical Example

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The chart above is the same chart we showed earlier, but now includes overlays for the excess return method and resulting trades.

As discussed, the excess returns method avoided the dot-com crash and GFC; though it did stay 2022 invested through most of the 2022 downturn.

Subscriber Access to All Results, Updated Daily

If you enjoyed this post and would like to follow along, we have shared all results, similar to above for QQQ, with paid subscribers via Google Drive. If you already paid for a subscription to AlgorithmicFIRE.com, you have access.

Those results include:

  • The 54 ETFs we used in this analysis (largest market cap stock ETFs)
  • Results for the 100 largest market cap stocks
  • Results for the 100 largest market cap bond ETFs
  • If there are other results you'd like reported on, and you're a paid subscriber, contact us at algorithmicfire@gmail.com

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We’ve made it easy to see what is changing. At the top of the Trade Analysis files, there is table like the image above that shows recent trade. So you don’t need to check every ticker to see what has recently happened.

  • There are two reports for each asset type (bond ETFs, stock ETFs, stocks - large cap).

    • The aggregate report has the charts CAGR, Max Drawdown, sharp ratio chart (reviewed above) for the group.

    • The analysis reports (both stocks and bonds) are the per ticker chart and trade table.

We now have online calculators for paid subscribers that can duplicate the above analysis.

Run it to see the results for whatever scenario you prefer.

If you would like access to the results, or the calculator, become a paid subscribe!

  • You will immediately have access to the premium calculators, but access to the Google Drive results may be delayed by up to 48 hours. We will email you upon adding your access.
  • Your account email address will be used for sharing via Google Drive.

Results will be updated at the end of each trading day; baring any issues that prevent us running the models. Generally results will be updated by 7PM Eastern U.S. time.

Aggregate Report at Time of Publishing

The data that is published to Google Drive will change each day it is updated. Below you can download the aggregate trade analysis at the time this post was written.

Download PDF

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**For Educational Purposes Only:** All content on this site, including articles, tools, and simulations, is for informational and educational purposes only. It should not be construed as financial, investment, legal, or tax advice. The information provided is general in nature and not tailored to any individual’s specific circumstances.

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