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The One Flaw That Breaks Every Trading Strategy
Why almost every backtest looks perfect until it meets the real market
When I first began developing algorithmic and technical trading strategies, I believed that creating a system that generated profits in backtests was the difficult part.
I spent weeks optimizing entry points, modifying indicators, and fine-tuning parameters until the results appeared perfect. The numbers made sense, and the drawdowns were minimal.
However, everything went wrong when I began trading it live. What once appeared to be a winning idea turned out to be a letdown, trades failed in unexpected ways, and performance plummeted.
Almost every trader eventually learns something from that experience. The main issue with the majority of trading strategies is not the strategy per se, but rather the way it is validated and tested.
Overfitting is a flaw that subtly undermines even the most intelligent systems.
Overfitting hides in every “perfect” backtest
When you create a strategy that too closely resembles the past, it’s called overfitting. It occurs when your model begins to identify noise rather than actual patterns.
