Backtesting
Point-in-time data, fill assumptions, slippage and funding, and the statistics that separate an edge from a lucky backtest.
Event vs State Signals: Why Cross Trades Last One Bar
A crossover is an event, a trend is a state. Mixing them with signal-flip exits makes 1-bar trades or heavy churn. Real backtest numbers, and three fixes.
Backtest Overfitting: 10 Warning Signs to Check
Backtest overfitting makes noise look like edge. Ten concrete warning signs, a quick test for each, and what to do when your strategy fails one.
Backtest vs Live Results: Why They Differ and How to Fix
Backtest vs live results rarely match. The main causes of the gap, from costs and fills to selection bias, and practical steps to make them closer.
Pine Script Backtest Accuracy: Why Results Look Too Good
Pine Script backtest accuracy depends on settings: zero default costs, same-bar fills, repainting and lookahead. What to check, and how Trigr handles each.
Selection Bias in Trading: The Best Backtest Is Luck
Selection bias in trading: the best of 100 backtests looks good partly by chance. How trial counts inflate Sharpe, how DSR corrects it, and how to stay honest.
Stop-Loss and Take-Profit in the Same Candle
When a stop-loss and take-profit hit in the same candle, a backtest has to guess the order. How the choice skews results, and the conservative way to decide.
Trading Fees: How They Decide If a Perp Strategy Works
Trading fees scale with how often you trade. See how fee drag compounds with frequency and leverage, and how to test whether a perp strategy's edge survives.
Backtest Fill Assumptions: Why Next-Bar-Open Fills Matter
Backtest fill assumptions decide which prices your trades get. Compare same-bar close, next-bar open and intrabar fills, with worked examples of the gap.
Backtest Slippage and Funding for Perps: Gross vs Net
How slippage and funding change a perp backtest, with worked examples for scalping, swing and trend strategies, and how to choose honest cost assumptions.
How to Read a Backtest Report: Costs, Drawdown, Trade Log
How to read a backtest in the right order: assumptions, Deflated Sharpe, PBO, drawdown, trade count and the trade log, with a worked example and red flags.
Look-Ahead Bias in Crypto Backtests, With Examples
Look-ahead bias lets a backtest use data it could not have known. See seven real examples in crypto backtests and two simple tests that catch them.
Point-in-Time Backtesting: Why Most Crypto Backtests Lie
Point-in-time backtesting only uses data that was knowable at each bar's close. Learn the leaks that inflate crypto backtests and how to close them.
The Deflated Sharpe Ratio Explained for Crypto Traders
The Deflated Sharpe Ratio corrects a backtest's Sharpe for how many strategies you tried. See the intuition, the formula and a worked example by trial count.
Put the idea to an honest test.
Describe a strategy in plain English or from your own AI assistant, backtest it on point-in-time data, and forward-test it on paper before any real money is involved.