5 Proven Trend-Following Strategies That Survived Every Bear Market
Explore 5 legendary trend-following models validated across 130+ years of market history. Discover how the Turtle Trading rules, Meb Faber's 200-day filter, and AQR's Time Series Momentum delivered positive crisis alpha during every modern bear market.
1. The Concept of Crisis Alpha: Why Trend Following Survives Market Crashes
A Century of Empirical Evidence (1880–2026)
Every few years, financial markets experience a catastrophic bear market that erases trillions of dollars in paper wealth. From the Wall Street Crash of 1929 and the 1970s stagflation to the 2000 Dot-Com crash, the 2008 Global Financial Crisis, and the 2022 inflation shock, passive buy-and-hold equity investors watched their portfolios plummet between 30% and 85%.
Yet amidst every single one of these historic collapses, a specific class of quantitative models not only survived, but generated substantial positive profits. In quantitative finance, this phenomenon is known as 'Crisis Alpha'—the capacity of systematic trend-following strategies to deliver outsized gains precisely during systemic equity dislocations.
In their landmark 2014 study, 'A Century of Evidence on Trend-Following Investing' (published in the *Journal of Portfolio Management*), AQR researchers Brian Hurst, Yao Hua Ooi, and Lasse Heje Pedersen backtested trend following across more than 130 years of continuous data (1880–2016, extended to 2026). Their findings proved that trend-following produced positive returns in every single decade for over a century. In this guide, we analyze and rank the top 5 battle-tested trend-following playbooks.
2. The Top 5 Trend-Following Strategies Ranked & Benchmarked
Ranked by Crisis Alpha, Risk-Adjusted Compounding, and Maximum Drawdown
We evaluated the premier systematic trend playbooks across multi-decade historical simulations. Here is the quantitative ranking:
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Trader Toolkit Quantitative Research Team
Systematic Strategy Research
Researchers specializing in rule-based quantitative trading, risk attribution, and algorithm backtesting.