mfe — Financial Econometrics for Python

Python port of Kevin Sheppard's Oxford MFE Toolbox, optimised for HFT data. Complements arch — covering everything arch is missing.

What's inside

Module Contents
mfe.realized RV, BPV, MedRV, realized kernel, TSRV, MSRV, Hayashi-Yoshida, multivariate kernel, BNS jump test
mfe.multivariate DCC, CCC, BEKK, O-GARCH, GO-GARCH, RCC
mfe.univariate HAR-RV (standard / MODIFIED / matrix intervals / HAR-J), HEAVY
mfe.timeseries VAR (4 VCV options), Granger causality, IRF, Beveridge-Nelson
mfe.bootstrap Wild bootstrap, SPA test (Hansen 2005), StepM (Romano-Wolf 2005)
mfe.crosssection Fama-MacBeth, OLS/OLSNW, PCA
mfe.tests_stat ARCH-LM, Ljung-Box, HAC LM, Diebold-Mariano, Mincer-Zarnowitz
mfe.distributions Skew-t (analytic score), GED, multivariate normal log-likelihood

Installation

pip install mfe

Cython extensions (optional, recommended for production)

Cython compilation gives 10–800× speedups on hot paths (realized kernel inner loop, Hayashi-Yoshida sweep, DCC/BEKK recursions):

pip install cython numpy setuptools
python setup_cython.py build_ext --inplace

Quick start

from mfe.realized import price_filter, returns_from_prices, realized_kernel, bns_jump_test
from mfe.realized._types import SamplingType

prices_5m, times_5m = price_filter(
    tick_prices, tick_times,
    sampling_type=SamplingType.CALENDAR_TIME,
    sampling_interval=300,
)
r = returns_from_prices(prices_5m)
rk  = realized_kernel(r)
jmp = bns_jump_test(r)

from mfe.multivariate import DCC, RCC
dcc = DCC().fit(returns)          # (T, K) → (T, K, K) sigma_t
rcc = RCC().fit(returns)          # covariance targeting by construction

from mfe.univariate import HEAVY
heavy = HEAVY().fit(daily_returns, realized_variances)

Development

uv sync --all-groups
PYTHONPATH=src pytest tests/     # 246 tests
mkdocs serve                     # documentation

Relationship to MATLAB MFE Toolbox

This package ports bashtage/mfe-toolbox to Python, fixing several bugs present in the MATLAB source (memory leaks, silent non-convergence, O(N²) algorithms replaced with O(N log N) Cython implementations).

Key dates

PyPI data
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  • Released:
Newer release available (0.1.2)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for luxor from gravatar.com luxor

Credits

Author: Gabin Taibi

License expression

MIT
View SPDX License List

Requires

Python >=3.11

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