QF-Lib Quant Report: full strategy performance analytics

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Backend: strategies/quant_report.py
  - equityCurve: daily PnL from trade history
  - monthlyReturns: heatmap matrix (years x months)
  - yearlyReturns: bar chart data with mean
  - monthlyReturnDistribution: histogram bins
  - qqPlot: theoretical vs observed quantiles
  - rollingStats: 6-month rolling return + volatility

API: /api/quant-report/{name}
  Computes full report from any backtest JSON file

Frontend: QuantReport.tsx
  - Strategy Performance chart (equity curve, blue line)
  - Monthly Returns heatmap (blue saturation)
  - Yearly Returns bar chart with mean line
  - Distribution histogram
  - Normal QQ plot with diagonal reference
  - Rolling Statistics (6-month, dual line)
  - QF-Lib header with logo and metadata
  - Access via QF-Lib Report button in detail view

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ramseshk

2026-08-06 03:37:25 +00:00

parent 03ebe9e795

commit 0e08543823

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