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ARCH for Python

Project description

Documentation Status CI Status Coverage Status


This is a work-in-progress for ARCH and related models, written in Python (and Cython)

What is this repository for?

  • Mean models
  • Constant mean
  • Heterogeneous Autoregression (HAR)
  • Autoregression (AR)
  • Zero mean
  • Models with and without exogensou regressors
  • Volatility models
  • ARCH
  • EWMA/RiskMetrics
  • Distributions
  • Normal
  • Student’s T


See the example notebook for a more complete overview.

import datetime as dt
import as web
st = dt.datetime(1990,1,1)
en = dt.datetime(2014,1,1)
data = web.get_data_yahoo('^FTSE', start=st, end=en)
returns = 100 * data['Adj Close'].pct_change().dropna()

from arch import arch_model
am = arch_model(returns)
res =


Documentation is hosted on read the docs


  • NumPy (1.7+)
  • SciPy (0.12+)
  • Pandas (0.14+)
  • statsmodels (0.5+)
  • matplotlib (1.3+)

Installing * Cython (0.20+) * nose (For tests) * sphinx (to build docs) * sphinx-napoleon (to build docs)


Setup does not verify requirements. Please ensure these are installed.


pip install git+git://


Anaconda builds are not currently available for OSX.

conda install -c arch


With a compiler

If you are comfortable compiling binaries on Windows:

pip install git+git://

No Compiler

All binary code is backed by a pure Python implementation. Compiling can be skipped using the flag --no-binary

pip install git+git:// --install-option "--no-binary"

Note that it isn’t possible to run the test suite will fail if installed with --no-binary


conda install -c arch

More about ARCH

More information about ARCH and related models is available in the notes and research available at Kevin Sheppard’s site.

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