#AIImpactOnForex Navigating the backtesting process requires awareness of common pitfalls that can lead to misleading results and flawed conclusions about a trading strategy's viability. One significant pitfall is look-ahead bias, where the backtest inadvertently uses future information that would not have been available at the time of a simulated trade. This can artificially inflate performance metrics. Another common mistake is selection bias, where the strategy is tested on a limited or cherry-picked dataset that happens to favor its rules. Insufficient consideration of transaction costs and slippage can also paint an overly optimistic picture of profitability. Furthermore, neglecting to account for market microstructure effects or failing to test the strategy across diverse market conditions can lead to a false sense of security. Avoiding these pitfalls through careful data handling, realistic simulation parameters, and rigorous testing protocols is crucial for obtaining a reliable assessment of a trading strategy's potential.