bashtage/arch

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1555 stars · 290 forks observed · 2026-08-28

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

A Python library for financial econometrics providing ARCH/GARCH volatility models, unit root tests, cointegration analysis, bootstrapping, and multiple comparison procedures. It uses Cython and Numba for performance and is actively maintained with regular releases.

Use cases

• fit GARCH models to estimate asset return volatility
• forecast financial time series variance and risk
• run Dickey-Fuller and Phillips-Perron unit root tests
• bootstrap confidence intervals for time series statistics
• perform model confidence set and reality check multiple comparison procedures
• estimate long-run covariance of financial data
• test and estimate cointegration relationships

When to choose

• you need ARCH/GARCH volatility modeling in Python
• you want econometric unit root or cointegration tests alongside volatility models
• you need fast, well-tested bootstrap methods for time series
• you are doing academic or applied financial econometrics research

When to avoid

• you need multivariate volatility models like DCC-GARCH
• you want general-purpose machine learning forecasting rather than econometric models
• you need a full statistical stack rather than a specialized toolbox
• you work outside Python

Facets

library · maturity stable

machine-learning data-science math data-science fintech time-series mathematics python econometrics garch volatility-modeling time-series bootstrap unit-root-tests finance forecasting

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