fynance 1.3.1

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

• Documentation: http://fynance.readthedocs.io/en/latest/index.html

• Source code: http://github.com/ArthurBernard/Fynance

Fynance is Python (and Cython) package, it provides machine learning, econometric and statistical tools designed for financial analysis and backtest of trading strategy. The documentation is available with some examples of the use of functions and objects.

The fynance.features and fynance.algorithms.allocation subpackages are stable. Other subpackages (fynance.models, fynance.backtest) are actively developed and may evolve.

Presentation

The fynance package contains currently five subpackages:

• Algorithms (fynance.algorithms) contains:

  • Portfolio allocations (e.g. ERC, HRP, IVP, MDP, MVP, etc.).

  • Rolling objects for algorithms (e.g. rolling_allocation, etc.).

• Backtesting objects (fynance.backtest) contains:

  • Module to plot profit and loss, and measure of performance.

• Feature tools (fynance.features) contains:

  • Financial indicators (e.g. bollinger_band, cci, hma, macd_hist, macd_line, rsi, etc.).

  • Statistical momentums (e.g. sma, ema, wma, smstd, emstd wmstd, etc.).

  • Metrics (e.g. annual_return, annual_volatility, calmar, diversified_ratio, mdd, sharpe, z_score, etc.).

  • Scale (e.g. Scale object, normalize, standardize, roll_normalize, roll_standardize, etc.).

  • Rolling functions (e.g. roll_min, roll_max).

• Time-series models (fynance.models) contains:

  • Econometric models (e.g. MA, ARMA, ARMA_GARCH and ARMAX_GARCH, etc.).

  • Neural network models with PyTorch (e.g. MultiLayerPerceptron, etc.).

  • Rolling objects for models, currently work only with neural network models (e.g. _RollingBasis, RollMultiLayerPerceptron, etc.).

Please refer you to the documentation to see more details on different tools available in fynance package. Documentation contains some descriptions and examples for functions, classes and methods.

Installation

From PyPI

$ pip install fynance

From source (GitHub)

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

Demo

• Backtest (performance, drawdown and rolling sharpe ratio) of a trading strategy did with a rolling neural network (see Notebooks/Exemple_Rolling_NeuralNetwork.ipynb for more details):

• Loss functions and performances (trading strategy) of five rolling neural networks on the training and testing period (see Notebooks/Exemple_Rolling_NeuralNetwork.ipynb for more details):

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Package not achieved, always in progress. All advice is welcome.