fynance 1.3.4

Python and Cython scripts of machine learning, econometrics and statistical features for financial analysis

Fynance

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Python and Cython package providing machine learning, econometric and statistical tools for financial analysis and backtesting of trading strategies.

Installation

pip install fynance

From source:

git clone https://github.com/ArthurBernard/Fynance.git
cd Fynance
pip install -e ".[dev]"
python setup.py build_ext --inplace

Subpackages

Algorithms fynance.algorithms
Portfolio allocation methods (ERC, HRP, IVP, MDP, MVP) and rolling walk-forward wrappers.

Backtest fynance.backtest
Profit-and-loss plotting and performance measurement.

Estimator fynance.estimator
Cython ARMA / GARCH parameter estimation.

Features fynance.features
Kalman filter, financial indicators (Bollinger, RSI, MACD, …), statistical momentums (SMA, EMA, WMA, …), metrics (Sharpe, Sortino, Calmar, drawdown, …), scaling, and rolling functions.

Models fynance.models
Econometric models (MA, ARMA, ARMA-GARCH), neural networks with PyTorch (MLP, RNN, GRU, LSTM, MultiHeadAttention), differentiable loss functions (SharpeLoss, SortinoLoss, DirectionalAccuracyLoss), and walk-forward rolling evaluation.

Quick start

import numpy as np
import fynance as fy

# Sharpe ratio
returns = np.random.randn(252) * 0.01
print(fy.sharpe(returns))

# ERC portfolio allocation
cov = np.cov(np.random.randn(5, 252))
weights = fy.ERC(cov)()
print(weights)

Rolling walk-forward training with a neural network:

from fynance.models.rolling import RollMultiLayerPerceptron

model = RollMultiLayerPerceptron(X, y, layers=[64, 32])
model(n=252, s=21, r=21)   # 252-day train, 21-day test, 21-day roll step
for eval_result in model:
    print(eval_result)

Links

• PyPI: https://pypi.org/project/fynance/
• Documentation: https://fynance.readthedocs.io/en/latest/
• Source: https://github.com/ArthurBernard/Fynance
• Changelog: https://github.com/ArthurBernard/Fynance/blob/master/CHANGELOG.md