Strategy backtesting
Validate every trading idea with data
Backtesting means simulating your trading strategy against historical market data — see the equity curve, max drawdown, and Sharpe ratio before risking a cent. On AlphaFox it's straightforward: pick history from exchanges like Binance and HyperLiquid, configure from a template or with the AI assistant, and run one-click backtests with batch parameter exploration, all on the free tier.
What is backtesting?
Backtesting simulates a trading strategy against historical market data to evaluate how it would have performed. Before risking real capital, you see the equity curve, max drawdown, Sharpe ratio, win rate, and other key metrics.
Backtesting can't predict the future — but it filters out broken ideas, compares parameter choices, and reveals how a strategy behaves across regimes. It's the first step from gut-feel trading to evidence-driven trading.
Engine Backtest capabilities
Batch parameter exploration
Configure multiple parameter sets at once, run them in batch, and quickly find combinations that are robust on historical data.
Multi-period comparison
Compare performance across different historical windows to spot overfitted strategies that only work in one regime.
Complete performance metrics
Returns, annualized, max drawdown, Sharpe, win rate, profit factor — the full risk/reward picture in one view.
Trade-level replay
Backtests record the key trade information — replay losing periods to diagnose what went wrong.
From backtest to live
- 1
Configure the strategy
Start from a template or let the AI assistant set parameters — hand the repetitive work to the tooling.
- 2
Run the backtest
Pick a historical window and run with one click. Explore parameters in batch and compare across periods.
- 3
Transition via paper trading
When the backtest looks good, validate on live data with paper trading before switching to automated execution.
Frequently asked questions
Do backtest results predict live performance?
Not exactly. Live trading brings slippage, fee changes, and liquidity differences that history can't fully capture. But backtesting is still irreplaceable: it filters out logically broken strategies and reveals risk character. The recommended path is backtest → paper trade → small-size live, validating step by step.
Do I need to code to backtest?
No. On AlphaFox you configure strategies visually from templates, or let the AI assistant generate and tune them — your time goes to trading ideas. The CLI keeps full power for users who prefer code.
What is overfitting, and how do I avoid it in backtesting?
Overfitting means parameters tuned too tightly to one slice of history, failing out of sample. Avoid it with cross-validation across non-overlapping periods, fewer parameters, and attention to out-of-sample results. Engine Backtest's multi-period comparison is built for exactly this.
Which trading pairs are supported for backtesting?
Spot and perpetual market data from exchanges such as Binance and HyperLiquid, including BTC, ETH, SOL, and other leading symbols. The supported universe keeps expanding — check the platform for the current list.
Is backtesting free?
Yes — the free tier covers strategy configuration and Engine Backtest so you can validate ideas first. Paid tiers unlock larger-scale automation. See the pricing page for details.
Validate your first idea today
Start free: configure a strategy and run a backtest; paper trading is usage-based. No credit card required.