Free crypto strategy backtesting — 7 years of Binance data, no signup
Start from one of these
Load one, then change the numbers and test. These are hypotheses worth checking, not strategies worth trusting.
1Market
2Entry Triggers (1/5)
3Exits2 active
What this strategy does
- RSI(14) crosses above 50
- 1.stop loss at -2%
- 2.take profit at +3%
If several conditions hit on the same candle, the one listed first applies.
Build a strategy
Stack up to five indicator triggers, then add filters and exit rules.
Run it
The engine replays seven years of candles in seconds, inside your browser.
Read it honestly
ROI, drawdown and win rate across periods. Catch overfitting before it costs you.
We ran the popular strategies for real
Eight widely used strategies, each run on six coins under the same conditions. 11 of 48 combinations made money.
11+ indicators
RSI, Bollinger, Supertrend, MACD, Stochastic, Donchian and more.
5 exit types
Fixed TP/SL, ATR stops, trailing, time exit, opposite signal.
8 timeframes
From 5-minute scalps to weekly swings.
Calculators
Compound interest and Kelly criterion, built in.
CSV export
Every trade, downloadable for your own analysis.
Shareable links
Your whole strategy encoded in one URL.
Learn before you risk
All guides →Overfitting: The "Perfect Settings" You Found Will Fail Live
Test enough parameter combinations and something will always look amazing, by pure luck. How to tell a robust strategy from a curve-fit illusion.
How to Backtest an RSI Strategy (Without Fooling Yourself)
RSI is the most-used oscillator in crypto, and the most misused. A practical, honest guide to backtesting RSI entries, exits and filters on real Binance data.
Position Sizing: The Decision That Outweighs Your Entry
Most traders obsess over entries and ignore how much to bet. Yet position size, leverage and risk-per-trade decide whether an edge compounds or blows up. A practical guide.
Market Regimes: Why Your Strategy Suddenly Stopped Working
Crypto alternates between trends, ranges and chop. Most strategies only earn in one regime, and give it back in the others. How to see regimes in a backtest.
What is backtesting?
Backtesting is the practice of running a trading strategy against historical price data to see how it would have performed. Instead of risking real money on a hunch, you define a set of rules — when to enter, when to exit, how much to risk — and measure the outcome across years of past candles. A good backtest will not tell you the future, but it will quickly expose whether an idea has any edge at all, or whether it only ever looked good in your head.
This tool backtests crypto trading strategies on seven years of Binance spot data for BTC, ETH, SOL, XRP, DOGE and ADA, across eight timeframes from 5-minute to weekly candles. It is free, requires no account, and every calculation runs inside your own browser — your strategies are never uploaded anywhere.
How to use it
- Pick a market. Choose a coin, a timeframe, and a direction (long, short, or both).
- Stack up to five entry triggers. Combine indicators like RSI, Bollinger Bands, Supertrend, MACD, moving-average crosses and more. Triggers are joined with AND, so all conditions must be true to enter.
- Add filters. Narrow entries with a higher-timeframe trend filter, an ADX strength filter, an RSI range, or a time-of-day window.
- Define your exits. Fixed take-profit and stop-loss, ATR-based stops, a trailing stop, a time exit, or exit on the opposite signal.
- Set your capital. Starting balance, fee per side, leverage and position size — so the result reflects real trading costs, not a frictionless fantasy.
Press Run backtest and the engine replays every candle in order, opening and closing trades exactly as your rules dictate. Results appear in seconds.
How to read the results
The summary shows total ROI, maximum drawdown (MDD), win rate, trade count and profit factor. The period table breaks performance down across the last several years so you can see whether an edge is consistent or a one-window fluke. The equity curve shows the shape of the ride — a strategy with the same final return but a smoother curve is usually the better one. Below that, every individual trade is listed and can be exported to CSV.
Pay special attention to max drawdown: it tells you the deepest peak-to-trough loss you would have had to sit through. A high return means nothing if the drawdown would have liquidated you or made you quit first. And be honest about overfitting — if a setting only wins at one exact parameter value and collapses one step to either side, you have found a lucky peak, not a durable edge.
Why you can trust the numbers
The backtest engine is validated against an independent Python reference implementation with golden tests: the two engines must produce trade-for-trade identical results, so the math is not guesswork. Signals are evaluated only on closed candles and trades open on the next candle's open, which prevents look-ahead bias — the most common way backtests lie. Trading fees are charged on both sides of every trade by default, and leverage is modelled with isolated-margin liquidation, so a blown-up position is reported as a real loss rather than a fantasy recovery.
Data is loaded from committed historical files and topped up with the latest closed candles from Binance's public data API on every run, so your backtest always includes the most recent completed bar. Nothing here is investment advice: past performance never guarantees future results, and this tool exists to help you test ideas skeptically, not to promise profits.