Larry Connors' RSI Strategy Still Performing Well

Key Takeaways

• 321 trades generated 10.7% CAGR since 2000.
• 71% win ratio and 2.1 profit factor.
• Max drawdown 23% versus 82% buy‑hold.
• Exposure only 18% of time, boosting risk‑adjusted return.
• Simple rules make it accessible for beginner systematic traders.

Pulse Analysis

Larry Connors introduced his RSI‑based mean‑reversion system in the early 2000s, targeting short‑term oversold conditions in otherwise strong markets. The strategy’s core premise—buying temporary weakness and exiting on a defined sell trigger—requires only a handful of technical rules, making it attractive to traders who lack extensive programming resources. Over the past two decades, the approach has become a staple in systematic trading curricula, often cited alongside other beginner‑friendly models like the Turtle and Dual Momentum frameworks.

The recent backtest of the Connors RSI strategy on the Nasdaq‑100 (QQQ) from 2000 through 2026 underscores its durability. With 321 trades, the model delivered a 10.7% CAGR, a 71% win ratio, and a profit factor of 2.1, while limiting market exposure to just 18% of the time. Its maximum drawdown of 23% starkly contrasts with the 82% drawdown experienced by a simple buy‑and‑hold position, highlighting the strategy’s superior risk‑adjusted return of 58% when adjusted for time in the market. These metrics suggest that even in an era of high‑frequency algorithms, a well‑tuned, low‑frequency rule set can compete on a risk‑adjusted basis.

For practitioners, the findings reinforce the value of simplicity and disciplined execution. While the strategy’s historical performance is compelling, modern traders should consider transaction costs, slippage, and regime shifts that could erode returns. Integrating adaptive filters—such as volatility‑based position sizing or macro‑trend overlays—can enhance robustness without sacrificing the original concept. Ultimately, Connors’ RSI system serves as a reminder that clear, rule‑driven logic remains a potent tool in the systematic trader’s arsenal, especially for those seeking a balance between performance and operational ease.