Test an idea before committing capital.
Evaluate a strategy against historical data with transaction-cost and slippage assumptions, walk-forward evaluation, Monte Carlo analysis, and portfolio simulation. Results include risk-adjusted metrics and drawdown analysis so you can judge robustness — not just returns. Backtested performance is hypothetical and does not guarantee future results.
Backtest — equity curve
Strategy vs. benchmark, hypothetical
Return
+34%
Max DD
-9.4%
Sharpe
1.42
Win rate
57%
Core capabilities
Simulate strategies against historical data with realistic cost and slippage assumptions, benchmark comparison, and risk-adjusted metrics.
Realistic simulation
Transaction-cost and slippage assumptions, walk-forward and Monte Carlo analysis.
Risk-adjusted metrics
Drawdown, volatility, Sharpe, Sortino, profit factor, alpha, and beta.
Benchmark comparison
Measure a strategy against a relevant benchmark, not just against zero.
Metrics that describe robustness
A strategy is more than its headline return. Backtesting surfaces the full risk profile.
- Total and annualized return
- Maximum drawdown and volatility
- Sharpe, Sortino, win rate, and profit factor
- Alpha and beta versus a benchmark
Hypothetical by nature
Backtested and simulated results are illustrative and do not guarantee future performance. Real conditions differ.
- Assumptions are explicit and adjustable
- Walk-forward evaluation reduces curve-fitting
- Monte Carlo analysis stresses sequence risk
Related features
Capabilities that work well alongside this one for the way you trade or invest.
Build a more disciplined trading process.
Bring research, strategy, risk, and review into one workflow — and keep control of every decision.
Not investment advice. Trading involves risk of loss. You are responsible for your decisions.