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quantopian/empyrical

Common financial risk and performance metrics. Used by zipline and pyfolio. observed · 2026-08-28

github.com/quantopian/empyrical · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

23/100

  • Activity 0
  • Release rhythm 8
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3820
  • days_rel: n/a
  • days_push: 768
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1508 stars · 459 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library of common financial risk and performance metrics such as max drawdown, alpha, beta, and capture ratios, built on NumPy and pandas. It is used by Quantopian's zipline backtesting framework and pyfolio portfolio analysis tool.

Use cases

  • calculate max drawdown of a returns series
  • compute alpha and beta against a benchmark
  • compute rolling risk metrics like rolling sharpe or rolling max drawdown
  • calculate capture ratios for up and down markets
  • evaluate backtest performance statistics in zipline or pyfolio

When to choose

  • you need standard quantitative finance risk/performance statistics in Python
  • you are using zipline or pyfolio and need compatible metrics
  • you work with pandas Series or NumPy arrays of returns

When to avoid

  • you need built-in market data fetching - data reading via pandas-datareader is deprecated and unreliable
  • you need actively developed features - the library is in maintenance mode
  • you need a full backtesting or portfolio analytics platform rather than just metrics

Facets

library · maturity maintenance

math data-science fintech data-science analytics python quantitative-finance risk-metrics performance-metrics pandas numpy quantopian

3 sources

Member repositories

RepositoryRoleHealth v2
quantopian/empyricalmain23

For agents

markdown · JSON · MCP: product_card(name="quantopian/empyrical")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem