arch

library8.0.0pypypi✓ verified 22d ago

ARCH is a Python library providing tools for financial econometrics, focusing on Autoregressive Conditional Heteroskedasticity (ARCH) models, unit root tests, cointegration analysis, and bootstrapping. It is actively developed with regular releases, with the current version being 8.0.0, requiring Python 3.10 or newer for optimal compatibility and performance.

data ai-ml

pip install arch

github ↗package ↗homepage ↗docs ↗changelog ↗

INSTALL

IMPORT

SIG · ARCH

arch

datapythonv8.0.0

Install

15.1s avg

Import

3807ms

Disk

380MB

Pass rate

9/ 10

Env Coverage9 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v8.0.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✓ —

✓ 14.85s

py 3.11

✓ —

✓ 14.25s

py 3.12

✓ —

✓ 15.25s

py 3.13

✓ —

✓ 15.25s

py 3.9

✕ build_error

✓ 15.65s

380MB installed

● package 380MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

arch_model

✓ from arch import arch_model

univariate

✓ from arch import univariate

unitroot

✓ from arch import unitroot

This example demonstrates how to fetch historical financial data, calculate returns, and then use `arch_model` to specify and fit a GARCH(1,1,1) model with a Student's T distribution. It prints a summary of the fitted model. Note that `pandas_datareader` is used for data fetching and needs to be installed separately.

import datetime as dt import pandas_datareader.data as web from arch import arch_model # Fetch financial data (example: FTSE 100 index) # Requires 'pandas_datareader' to be installed (pip install pandas_datareader) st = dt.datetime(1990,1,1) en = dt.datetime(2014,1,1) data = web.DataReader('^FTSE', 'yahoo', start=st, end=en) returns = 100 * data['Adj Close'].pct_change().dropna() # Initialize and fit an ARCH model am = arch_model(returns, vol='Garch', p=1, o=1, q=1, dist='StudentsT') res = am.fit(update_freq=5) print(res.summary())

arch --version

Debug

Known issues

breakingVersion 8.0.0 and later require Python 3.10+. Older Python versions are no longer supported. The build system has also moved from setuptools to Meson.

fix

Upgrade your Python environment to 3.10 or newer. If you encounter build issues, ensure your environment is compatible with Meson or consider `--no-binary` installation if performance is not critical and a compiler is unavailable.

affects: 8.0.0+

gotchaWhen using `arch` for financial econometrics, proper handling and preparation of time-series data (e.g., ensuring correct datetime indices, handling missing values, and calculating returns appropriately) is crucial for valid model results. External libraries like `pandas_datareader` (used in quickstart) are not core dependencies and must be installed separately.

fix

Always preprocess your time-series data carefully using libraries like Pandas. Validate data types and structures before feeding them into `arch` models. Install any external data acquisition libraries required for your specific workflow separately.

affects: All

gotchaMixing `pip` installations with system-managed Python packages (e.g., via `pacman` on Arch Linux) can lead to conflicts, especially during Python version updates. This can break virtual environments and lead to 'module not found' errors.

fix

Always use virtual environments (e.g., `venv`, `conda`, `pyenv`) for your Python projects to isolate dependencies. Install all project-specific packages within the activated virtual environment using `pip`.

affects: All

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'arch'

The 'arch' library is not installed in the Python environment.

fix

Install the 'arch' library using pip: 'pip install arch'.

ImportError: cannot import name 'ConstantMean' from 'arch'

Attempting to import 'ConstantMean' directly from 'arch' instead of its submodule.

fix

Import 'ConstantMean' from the correct submodule: 'from arch.univariate import ConstantMean'.

ModuleNotFoundError: No module named 'arch' despite it showing in pip list

The 'arch' library is installed in a different Python environment than the one currently in use.

fix

Ensure that the Python interpreter being used matches the environment where 'arch' is installed, or reinstall 'arch' in the correct environment.

ImportError: No module named 'arch'

The 'arch' package is not installed in the active Python environment, or the environment is not correctly configured or activated.

fix

Ensure 'arch' is installed using `pip install arch`. If using virtual environments, make sure the correct environment is activated before running your script.

AttributeError: type object 'arch.univariate.recursions.array' has no attribute '__reduce_cython__'

This error typically indicates a compatibility issue or conflict between different versions of Cython used to compile 'arch' or its dependencies, or a mismatch with the installed Python version.

fix

Try reinstalling 'arch' in a clean virtual environment (`pip install arch`). If the issue persists, consider trying a specific older version of 'arch' that is known to be compatible with your Python/Cython setup (e.g., `pip install arch==4.6.0`).

Upgrade

Version history

8.0.0latest on PyPI · released Oct 21, 2025

Audit

Dependencies

numpyrequiredFundamental package for numerical computing in Python, essential for array operations and mathematical functions underlying econometric models.

scipyrequiredProvides scientific computing tools, including advanced mathematical algorithms and statistical functions used in ARCH models.

pandasrequiredOffers high-performance, easy-to-use data structures and data analysis tools, crucial for handling time-series financial data.

statsmodelsrequiredIntegrates closely for a wide range of statistical models and tests beyond what `arch` directly implements.

matplotliboptionalUsed for plotting and visualizing results from econometric models.

cythonoptionalOptional dependency to improve performance through C extensions.

numbarequiredOptional dependency for just-in-time compilation to further enhance performance, especially if Cython is not used or a compiler is unavailable.

Agent activity

53 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/bashtage/arch ↗

packagehttps://pypi.org/project/arch/ ↗

homepagehttps://bashtage.github.io/arch/ ↗

docshttps://bashtage.github.io/arch/ ↗

changeloghttps://bashtage.github.io/arch/changes.html ↗