Backtesting a 0DTE strategy means testing your rules against historical data to estimate its edge — useful but fraught with pitfalls like overfitting and unrealistic fills. Here’s how to do it sensibly.

How to backtest

Define your rules precisely (entry, exit, sizing), then apply them to historical data and measure the results — expectancy, win rate, drawdowns — over a meaningful sample. The goal is honest evidence of whether the strategy has a positive edge before you risk real money. Discipline in defining rules upfront prevents the biggest trap: fooling yourself.

The pitfalls (especially for 0DTE)

Overfitting: tuning rules to fit past data perfectly produces a strategy that looks great historically and fails live. Unrealistic fills: backtests often assume perfect fills, ignoring slippage and the spread — huge for frequent scalping. Data quality: accurate intraday 0DTE options data is hard to get and model. Regime change: a past edge can vanish as markets evolve. 0DTE’s fast, path-dependent nature makes clean backtesting genuinely hard.

A backtest that looks perfect is usually overfit. Honest backtesting includes costs, out-of-sample tests, and humility — it estimates an edge, it doesn’t guarantee one.

How to do it honestly

Include realistic costs, test out-of-sample (reserve data the strategy never “saw”), keep rules simple (fewer parameters = less overfitting), and treat results as an estimate, not a promise. Then forward-test and start tiny live. Backtesting informs; live results decide.