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fincore | Quantitative Performance & Risk Analytics

fincore is a Python library for calculating common financial risk and performance metrics. It continues the empyrical analytics stack under active maintenance by cloudQuant. Current version: 0.3.0 (Beta), Python 3.11+.

Three API surfaces

  • Strict compatibility — fincore.empyrical: the frozen empyrical 0.6.0 surface (54/54 C0, 49/49 C1, core callables C3).
  • pyfolio façade — fincore.pyfolio: the frozen pyfolio 0.9.6 profile of 11 workflows (C1 all, main chains C4). Requires fincore[pyfolio].
  • Enhanced semantics — fincore.metrics, the flat API, and AnalysisContext: fincore's own interfaces with documented divergences.

See Compatibility for the full C0–C4 matrix.

Features

  • 150+ Financial Metrics — returns, risk, drawdown, alpha/beta, capture ratios, timing
  • AnalysisContext — one-liner fincore.analyze() with lazy cached computation
  • RollingEngine — batch rolling metrics in a single call
  • Pluggable Visualization — Matplotlib, HTML, Plotly, Bokeh backends
  • Portfolio Optimization — efficient frontier, risk parity, constrained optimization
  • Monte Carlo Simulation — bootstrap, scenario testing, path simulation
  • Performance Attribution — Brinson, Fama-French, style analysis
  • Lazy Imports — import fincore in ~0.04s

Quick Example

import pandas as pd

import fincore

index = pd.date_range("2024-01-02", periods=5, freq="B")
returns = pd.Series([0.01, -0.005, 0.002, 0.004, -0.001], index=index)
benchmark = pd.Series([0.008, -0.003, 0.001, 0.002, 0.0], index=index)

ctx = fincore.analyze(returns, factor_returns=benchmark)

print(f"Sharpe: {ctx.sharpe_ratio:.4f}")
print(f"Max DD: {ctx.max_drawdown:.4f}")

ctx.to_html(path="report.html")

The quick example above is executed with the same data and arguments by a matching test in tests/docs/test_examples.py.

Installation

pip install fincore

# With visualization extras
pip install "fincore[pyfolio]"
pip install "fincore[interactive]"

# Everything
pip install "fincore[all]"

Project status

Metric Value Source
Version 0.3.0 (Beta) pyproject.toml (single metadata source)
Python 3.11, 3.12, 3.13 requires-python = ">=3.11"
Quality numbers machine-generated current-baseline.md
Release readiness itemized checklist release-candidate-checklist.md
Platforms macOS, Linux, Windows CI matrix
License Apache 2.0 LICENSE