Features
Analysis
Measure returns and risk, dissect trades, chart results, and study market events
Measure returns and risk, study drawdowns, dissect trades, chart results, explore recurring market events, and query the event records behind all of them. This section is for anyone who has a backtest, or any return series, and wants to know how good it was and why it behaved the way it did. Each page below answers one of those questions, for one portfolio or for thousands at once.
Start here
Begin with Performance and risk metrics for the full report on a backtest and how to compare it with a benchmark. Then follow the question you want to answer:
| Your question | Where to look |
|---|---|
| How deep were the losses, and how long did recovery take? | Drawdown analysis for individual drawdowns, time underwater, and unfinished recoveries |
| Which trades made money, and did the exits leave profit behind? | Trade analytics for entry and exit records, MAE, MFE, and long/short comparisons |
| How can I inspect a trade or compare a parameter grid visually? | Interactive charts for price overlays, dashboards, heatmaps, and sharing charts |
| What happened after similar patterns or dated events? | Patterns and event studies for historical matches and forward price paths |
| How can I analyze just the events or groups I care about? | Records and mapped arrays for filtering and regrouping orders, trades, and intervals |
Explore analysis features
features/analytics pages
Performance and risk metrics
Compute returns, Sharpe, Sortino, benchmark, and rolling metrics on any backtest
Drawdown analysis
Measure the depth, duration, and recovery of every drawdown as records
Trade analytics
Analyze trades and positions with MAE, MFE, edge ratio, profit factor, and plots
Interactive charts
Plot backtests, candlesticks, indicators, signals, and parameter heatmaps with Plotly
Patterns and event studies
Search price history for similar patterns and study what happened after events
Records and mapped arrays
Store sparse events and intervals as records, then filter, reduce, and regroup them
Work with results you already have
The analysis tools also work with your own data. Use a Pandas return series or an external equity curve with Performance and risk metrics, or inspect its losses with Drawdown analysis. If you have a list of earnings, news, or signal dates, the event calendar example shows how to compare the price paths that followed them.
Turn findings into the next test
A trade breakdown might suggest a different exit, while a parameter heatmap might reveal a region worth exploring. Take those ideas back to Backtesting and Parameter optimization, then use Walk-forward and cross-validation to test them on periods that were not used to choose them.
For a worked example of pattern detection and projections, follow the Patterns and projections tutorial.
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