Momentum RSI Strategy Backtest: 80% Win Rate Over 2 Years

I'm always tinkering with new trading ideas and running backtests. It's one of my favorite parts of being a trader—exploring what works, what doesn't, and why. Recently, I came across a Reddit post in r/algotrading that caught my attention. The poster claimed an 81.6% win rate with impressive gains using a momentum-based approach. Naturally, I had to test something similar myself.

This is a stock-only strategy—no options involved yet. I often start with stock strategies because they're simpler to backtest and validate before considering how to adapt them to options. Could this become a put selling strategy or something more sophisticated? Maybe. But first, I wanted to see if the core concept held water.

The Strategy: Momentum Meets Mean Reversion

The Momentum RSI strategy combines two well-documented market effects:

1. Momentum Effect: Stocks that have outperformed recently tend to continue outperforming
2. Mean Reversion: Even strong stocks experience temporary pullbacks that tend to revert

The core idea is simple: trade only high-performing stocks, but enter when they're temporarily oversold. You're essentially buying the dip on winners—stocks that have already proven themselves but are experiencing short-term weakness.

Strategy Parameters

Here's exactly what I tested. Every parameter is documented so you could replicate this yourself:

Backtest Period

I ran this backtest over approximately two years:

• Start Date: January 1, 2024
• End Date: January 17, 2026
• Duration: ~2 years

Results Summary

Here's the high-level performance:

The 80% win rate is the headline number, but it's the combination of high win rate with reasonable profit factor (1.64) that makes this interesting. The average hold time of just 3.8 days means capital isn't tied up for long.

Exit Reason Breakdown

Understanding how trades exit is crucial for evaluating any strategy:

Over 78% of trades hit the 3% profit target. The max hold exits are where the losses come from—when a stock doesn't bounce within 10 days, you're often sitting on a loss.

Yearly Performance

2024 was clearly the better year with an 85.9% win rate and profit factor over 2. The strategy struggled more in 2025, though it still remained profitable. The 2026 data is too limited to draw conclusions (only 6 trades, some still open at backtest end).

Monthly Performance

March 2025 stands out as the worst month—a -$1,384 loss with only a 42.9% win rate. This is where having multiple strategies in your arsenal matters. No single approach works all the time, which is why I trade SPY Put Credit Spreads and the Wheel Strategy alongside my experimental backtests.

Key Observations

1. High Win Rate: 80% of trades hit the 3% profit target
2. Quick Exits: Average hold time is only 3.8 days
3. Asymmetric Risk: Winners average +$64, losers average -$157 (but losers are rare)
4. Concentrated Losses: Worst month was March 2025 (-$1,384) due to multiple max_hold exits
5. Seasonal Patterns: Strong performance in May, September, and November

Risk Considerations

No backtest is complete without discussing what can go wrong:

• No Stop Loss: Losses are only capped by the 10-day max hold rule. This means a stock could drop significantly before you exit.
• Worst Trade: VERX on 2025-02-19 lost -$630 (-30.37%). That's a painful single-trade drawdown.
• 100% Exposure: With 4 positions at 25% each, you can have 100% of capital at risk simultaneously.
• Max Drawdown: 12.9% drawdown experienced during the backtest—could you stomach that?

As I discuss in my article on backtesting and data analysis, past performance doesn't guarantee future results. This strategy worked over the test period, but market conditions change.

Complete Trade Log (All 165 Trades)

Full transparency—here is every single trade from the backtest:

Could This Become an Options Strategy?

This is where my mind naturally goes. A few ideas for adapting this to options:

• Selling Puts on RSI Oversold Signals: Instead of buying the stock, sell cash-secured puts on momentum stocks when RSI drops below 30. You'd collect premium and potentially get assigned at a discount.
• Bull Put Spreads: Use the same entry signal but with defined-risk spreads instead of stock positions.
• Covered Call Enhancement: If assigned shares via puts, immediately sell covered calls to generate additional income while waiting for the bounce.

I haven't backtested these options variations yet, but they're on my list. If you're interested in options strategies with documented results, check out my options trading course where I share real-time alerts and complete transparency on every trade.

Final Thoughts

This Momentum RSI backtest shows promise—an 80% win rate and 33% return over two years is nothing to sneeze at. But backtests are just the starting point. The real test is live trading with real money, where slippage, emotions, and unexpected events come into play.

I shared this because I enjoy the process of exploring ideas and believe in transparency. Not every backtest I run looks this good, and not every promising backtest translates to live success. But the exploration itself is valuable.

If you're interested in systematic trading and want to see how I apply similar thinking to my actual options strategies, explore the rest of Options Cafe. I publish all my trades—wins and losses—because real results matter more than theoretical backtests.

Happy trading!

Related Topics: Backtest Results, RSI Strategy, Momentum Trading, Algorithmic Trading, Stock Trading Strategy, Mean Reversion, Swing Trading, Quantitative Trading, Trading Backtest, Systematic Trading