Backtesting, from first principles
Backtesting is how you estimate whether a trading rule has any edge — and it is the easiest thing in quantitative trading to get wrong. These pages build the foundation: what a backtest actually is and what it can and cannot prove, why so many backtests fail live, and the data, rules, execution assumptions and validation discipline that separate an honest test from a flattering fiction — grounded in how the Indian market (NSE, Nifty, F&O) works.
Backtesting Fundamentals: Backtesting is the process of simulating a fully-specified trading strategy on historical market data to estimate how it would have behaved, so you can study and falsify it before risking capital. An honest backtest needs clean point-in-time data, explicit rules, realistic execution assumptions and costs, a benchmark to beat, and out-of-sample validation. It is a hypothesis test that reduces uncertainty — never a prediction of future profit.
What is Backtesting?
Core conceptBacktesting is the process of simulating a fully specified trading strategy on historical market data to estimate how it would have behaved, so its e…
Why Backtesting Fails
Core conceptBacktesting fails when the reported result reflects fitting to historical noise, information leakage, biased data, ignored frictions or too few trade…
Historical Data
DataHistorical data is the recorded market information (prices, volumes, corporate actions and reference data) that a backtest replays, and its accuracy,…
Trading Rules
Core conceptTrading rules are the fully specified, unambiguous logic (entry, exit, position sizing, timing and edge-case handling) that a backtest engine execute…
Execution Assumptions
RealismExecution assumptions are the modelled details of how orders actually reach the market in a backtest (fill prices, slippage, transaction costs, laten…
Data Quality
DataData quality is the degree to which backtest data is accurate, complete, consistently adjusted and point-in-time correct, and it sets the hard upper …
Benchmark Comparison
EvaluationBenchmark comparison evaluates a strategy's performance relative to an appropriate reference such as a market index or risk-free rate, so that its re…
Validation Process
ValidationThe validation process is the structured sequence of tests (out-of-sample evaluation, walk-forward analysis, parameter sensitivity, Monte Carlo resam…
Research Workflow
ProcessThe research workflow is the disciplined, repeatable pipeline that turns a trading idea into a deployed strategy (hypothesis, data preparation, rule …
Strategy Lifecycle
Core conceptThe strategy lifecycle is the full arc a trading strategy travels through (idea, research, validation, deployment, monitoring, decay and eventual ret…