Backtesting
Test your strategies on historical data before risking real capital
What is Backtesting?
Backtesting runs your node-graph strategy against historical market data to measure how it would have performed. Instead of risking real money, you replay past price action and see every trade the strategy would have taken — along with a complete profit & loss breakdown, drawdown profile, and risk metrics.
Validate Your Strategy
Confirm your trading idea has a real edge on years of historical data before going live.
Find Optimal Parameters
Test hundreds or thousands of parameter combinations automatically to identify the best settings.
Understand Risk
See your true max drawdown, win rate, and profit factor — real numbers, not estimates.
Avoid Costly Mistakes
Discover hidden weaknesses in your strategy without losing real money in live markets.
How It Works
When you press Run, the engine executes this pipeline:
- 1
Decompile Graph
Converts your node graph into Slang source code, extracting all variable names, function calls, and parameter values.
- 2
Generate Combinations
Computes the Cartesian product of all parameter sweep ranges. For example SMA1 [5,10,15] × SMA2 [20,30] produces 6 combinations.
- 3
Pre-fetch Market Data
Downloads OHLC bars for all configured markets in parallel before running any backtests.
- 4
Parallel Execution
Distributes work across up to 8 Web Workers (capped at your CPU core count). Each worker independently runs one parameter combination.
- 5
Stream Results
As each worker finishes, results are streamed live into the Leaderboard and Heatmap. You can stop at any time.
⚡ Turbo Mode
Turbo Mode bypasses React state updates during a sweep and uses direct DOM manipulation for the progress bar. This eliminates re-render overhead when running large sweeps (500+ combinations), giving noticeably faster completion times. Toggle Turbo Mode in the bottom strip of the Configuration panel.
Explore in Detail
Each panel of the Backtesting component is documented in depth:
Configuration
Set up markets, date ranges, and parameter sweep ranges. Define what to test and how.
Statistics & Metrics
Every metric the engine computes — win rate, profit factor, drawdown, expectancy, and 25 more.
Heatmap & Leaderboard
Visual parameter heatmap and sortable leaderboard to compare all sweep results at a glance.
Equity Curve
Interactive equity curve chart showing account balance over time. Overlay multiple runs.
Trade Inspector
Deep-dive into any single result. Inspect every node's output, individual trade logs, and data export.
UI Layout
The Backtesting panel uses a 3-column resizable layout. All panel boundaries can be dragged to resize.
Best Practices
Use at least 2+ years of data for statistical significance.
Always configure slippage and commission to simulate real trading costs.
Avoid over-optimizing — parameters tuned too tightly to history fail live.
Validate promising parameters with Walk-Forward Analysis on out-of-sample data.
Profit Factor > 1.5 and Win Rate > 50% is a good baseline to target.
Test on multiple timeframes — strategies often behave differently across them.