4 Backtesting Techniques I Used to Find 10 Profitable Trading Algorithms

If you’ve ever created a “perfect” trading strategy in backtests… only to see it fail in live trading, this article is for you.

In this post, I’ll guide you through 4 backtesting techniques I used to find my 10 profitable algos, and I’ll demonstrate how to understand them easily with code-style examples.

We’ll cover:

1. Parameter sensitivity
2. Walk-forward optimization
3. Stress testing
4. Monte Carlo simulation

And finally, I’ll give you a simple framework you can use to apply all of this in your own strategies.

Photo by Maxim Hopman on Unsplash

Why Most Backtests Lie to You

Backtests are like Instagram profiles:
You’re seeing the highlight reel, not the reality.

If you’re not careful, you’ll end up with a strategy that:

• Looks incredible on past data
• Has a beautiful equity curve
• Shows tiny drawdowns

…and then dies the moment you go live.

The main culprit?

Overfitting — your strategy “memorizes” historical noise instead of learning real…