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DASHBOARDS: Portfolio Hub Market Pulse Performance Compare Studio

DYNF

iShares U.S. Equity Factor Rotation Active ETF
TREND FOLLOWING PERFORMANCE HISTORY
2026-09-09
Executive Summary
The quantitative backtest for DYNF (iShares U.S. Equity Factor Rotation Active ETF) using the Moving Average (50/200)* strategy in a Investing context demonstrated its primary role in risk mitigation, experiencing a maximum drawdown of -20.4% (compared to the benchmark's drawdown of -27.0%). Over the evaluated period, this protective approach generated a Compound Annual Growth Rate (CAGR) of 14.1%, compared to a Buy-and-Hold benchmark return of 16.0%. The strategy executed 2 total trades.

* Moving Average (50/200): Classic Moving Average Crossover (e.g., 50-day crossing 200-day). The foundational basis of research-grade trend following.

🛡️ DYNF Drawdown Shield & Downside Protection

Why Drawdown Dictates Longevity →
Peak Drawdown Defense
-20.4% (vs -27.0% B&H)
+6.6% shallower drawdown
Drawdown Shield
6.6% Cut
Protected capital vs -27.0% B&H
Capital Sheltered from Risk
18.2% of Time
Earning Treasury yield during downturns
* Drawdown Shield demonstrates how systematic trend-following bounded historical drawdowns and protected principal capital compared to passive Buy & Hold.

📊 DYNF Quality Metrics & KPI Summary

Metric 1Y5YFull
StrategyB&HStrategyB&HStrategyB&H
Max Drawdown-8.67%-8.67%-20.39%-26.97%-20.39%-26.97%
Sharpe Ratio1.431.430.910.810.990.87
Sortino Ratio2.112.111.081.121.191.20
CAGR21.42%21.42%13.14%15.18%14.11%15.99%
% Time Invested100.0%100.0%80.1%100.0%81.8%100.0%
Trades / Year0.00.00.20.00.40.0

Cumulative Growth Performance

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Hydrating Performance Trajectory... Loading historical performance data
Figure 1: Cumulative Trajectory Analysis. Logarithmic growth comparison of DYNF under the Moving Average (50/200) strategy (Investing) versus Buy & Hold. The strategy produced a 14.1% CAGR with a -20.4% Max Drawdown across 2 trade signals (compared to Buy & Hold's 16.0% CAGR and -27.0% Max Drawdown).

Return Distribution Analysis

Histogram of monthly return distribution for DYNF under Moving Average (50/200) strategy in Investing context, illustrating downside risk mitigation and return skewness.
Figure 2: Monthly Return Distribution Profile. Monthly return distribution for DYNF under Moving Average (50/200) (Investing). Visualizes return frequency, volatility clustering, and tail-risk truncation relative to standard buy-and-hold returns.
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Top 5 non-correlated asset sleeves evaluated on 1Y daily percentage returns (Pearson r). Compare them side-by-side in Compare Studio to analyze portfolio diversification.

Diversifier Asset Category 1Y Correlation (r) Action
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Trade History

This log shows every signal-driven transition. Completed trades reflect standard market cycles. An Open or Mark-to-Market exit denotes an active position (either in the primary asset or a cash/yield sleeve) valued at the current price for reporting purposes. Interest entries record yield accrued from cash or cash alternatives (like BIL) during out-of-market defensive periods.

Entry DateExit DateTypeAllocationEntry PriceExit PriceNet Return %Exit Reason
🔒 Active Positions & Recent Execution Signals Hidden
Trading on delayed data carries high execution risk. Current allocations, pending next-day rebalances, and active execution signals (last 60 days) require a Premium subscription.
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2025-04-07 2025-05-01 Interest (CASH) 100% $1.00 $1.00 0.29% Interest Income
2023-01-27 2025-04-07 Completed 100% $30.56 $42.12 37.77% Stop
2022-02-23 2023-01-27 Interest (CASH) 100% $1.00 $1.02 2.36% Interest Income
2021-03-16 2022-02-23 Completed 100% $30.85 $31.44 1.85% Signal
2021-03-12 2021-03-16 Interest (CASH) 100% $1.00 $1.00 0.00% Interest Income

Next Steps: Portfolio Integration & Comparative Analysis

Single-ticker trend following is designed to truncate tail risk inside a broader portfolio. View where DYNF ranks across 40+ tracked assets, evaluate correlation against non-correlated diversifiers, or model it inside a custom all-weather asset mix.

📊 View Full 40-Asset Backtest Matrix → 🛠️ Build Custom Portfolio with DYNF → ⚖️ Compare DYNF vs Non-Correlated Assets →