pymlfinance
Python bindings for mlfinance — a Rust implementation of concepts from Advances in Financial Machine Learning by Marcos López de Prado.
Installation
pip install pymlfinance
With Polars plugin support:
pip install pymlfinance[polars]
Quick Start
import numpy as np
import pymlfinance as ml
# EWMA smoothing
prices = np.array([100.0, 101.5, 99.8, 102.3, 101.0])
smoothed = ml.core.ewma(prices, 3)
# CUSUM event filter
events = ml.data.cusum_filter(prices, 1.5)
# Triple-barrier labeling
from pymlfinance import TripleBarrierConfig
config = TripleBarrierConfig(upper_barrier=0.02, lower_barrier=0.02, max_holding_period=10)
# Fractional differentiation
stationary = ml.sampling.frac_diff_ffd(prices, 0.5, 1e-4)
# HRP portfolio allocation
returns = np.random.randn(100, 5) * 0.02
weights = ml.features.hrp_weights(returns)
# Sharpe ratio
ret = np.random.randn(252) * 0.01
sr = ml.backtesting.sharpe_ratio(ret)
Modules
| Module | Description |
|---|---|
pymlfinance.core |
EWMA, cumsum, returns, matrix utilities |
pymlfinance.data |
Bar generation (tick, volume, dollar, information-driven), CUSUM filter |
pymlfinance.labeling |
Triple-barrier, meta-labeling, trend-scanning |
pymlfinance.sampling |
Sequential bootstrapping, sample weights, fractional differentiation |
pymlfinance.features |
Structural breaks, entropy, microstructure, HRP, denoising |
pymlfinance.modeling |
Bet sizing, cross-validation, feature importance |
pymlfinance.backtesting |
Backtest statistics, overfitting detection, strategy risk |
Polars Plugin
import polars as pl
import pymlfinance # registers .ml namespace
df = pl.DataFrame({"price": [100.0, 101.5, 99.8, 102.3, 101.0]})
df.with_columns(pl.col("price").ml.ewma(span=3).alias("smoothed"))
Documentation
Disclaimer
This software is provided for educational and research purposes only. It does not constitute financial advice. Use of this code for trading or investment decisions is entirely at your own risk. The authors accept no liability for any financial losses incurred.
License
BUSL-1.1 — see LICENSE.
1 maintainer
Metadata
1 maintainer
Release files for pymlfinance 0.1.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| pymlfinance-0.1.1.tar.gz | 11.0 MB | Without provenance | Details |
Built distributions (wheels)
Total release size: 114.0 MB
Release files / pymlfinance-0.1.1.tar.gz
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