Skip to content

UI Workflow

Steps

  1. Load data in the Data Loader page.
  2. Create a strategy in the Strategy Editor, or skip strategy sizing entirely and use target-weight portfolio construction in the Backtest Runner.
  3. Run backtest in the Backtest Runner.
  4. Review results in Results Dashboard and Portfolio Analyzer.
  5. Deep-dive analytics in the Advanced Analytics page.

Advanced Analytics (New)

The 🔬 Advanced Analytics page provides:

Heatmaps

  • Monthly returns heatmap — calendar grid (month × year) colour-coded by return.
  • Correlation matrix — pairwise return correlations for multi-symbol backtests.
  • Drawdown heatmap — worst monthly drawdown in calendar form.

Rolling Statistics

  • Rolling Sharpe ratio with configurable window (30/60/90/252 days).
  • Annualised rolling volatility with percentile bands.
  • Rolling beta against an actual benchmark series loaded into the run.
  • Rolling maximum drawdown (trailing window).

Compare Runs

Save multiple backtest results and compare them side-by-side with an equity-curve overlay and metrics table.

Parameter Sensitivity

Sweep two parameters across a grid and visualise the impact on return, Sharpe, drawdown, or win rate as a surface heatmap.

Export

  • Download equity curve and trades as CSV.
  • Download summary metrics as JSON.
  • Download an institutional-style tearsheet in JSON or Markdown.
  • Use browser print (Ctrl+P) for a quick PDF snapshot.

Dark Mode

Toggle 🌙 Dark Mode in the sidebar for a dark colour scheme.

Portfolio Construction Workflow

The Backtest Runner now supports a target-weight portfolio construction mode for multi-symbol research:

  • Enter target weights as SYMBOL=percent pairs, for example AAPL=60, MSFT=40.
  • Choose a rebalance schedule: daily, weekly, or monthly.
  • Add guardrails for drift, max position weight, max turnover per rebalance, cash floor, and a drawdown-triggered de-risking threshold.
  • Review realized weights, drift, turnover, cash buffer, rebalance reasons, and constraint hits in the Portfolio Analyzer tab.
  • Benchmark-relative analytics remain available when the benchmark symbol is present in the loaded market data.

Tips

  • Start with sample data to validate logic quickly.
  • Save configurations for reproducibility.
  • Include benchmark bars in the loaded dataset to unlock real beta/alpha/information-ratio analytics.
  • Use portfolio construction mode when you want reusable allocation policy + rebalance diagnostics instead of ad hoc strategy sizing.
  • Export results or tearsheets for offline analysis.
  • Use the Compare Runs tab to evaluate strategies against each other.