Why most backtests are useless — the 7 biases you need to know
After 3 years of algo trading and hundreds of backtests, here's why 90% of backtests you see online are misleading:Survivorship bias: you test on stocks that still exist. The ones that went bankrupt are excluded. Inflates returns.Look-ahead bias: using data that wasn't available at the time of the trade. Even split adjustment can cause this.Overfitting: 20 parameters optimized over 10 years = perfect curve, catastrophic real performance.Slippage ignored: "I made 200%" — with perfect fills at mid-price that you'll never get in reality.Transaction costs: commission + spread + market impact. On a high-frequency algo, it changes everything.Data snooping: testing 50 strategies and keeping only the best one. Probability it works forward: close to zero.Regime change: what worked in 2015-2020 (infinite QE, zero rates) doesn't work in 2024-2026 (high rates, inflation).