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boon

Datasets and code for results presented in the BOON paper

causal_book

書籍「作りながら学ぶ! PyTorchによる因果推論・因果探索」の実装コードのリポジトリです

deep-learning-from-scratch

『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)

dgm

Solving High Dimensional Partial Differential Equations with Deep Neural Networks

dupirenn

Neural network local volatility with dupire formula

heston-normal-and-rough

European and Forward-start option pricing and implied volatility in the Heston and rough Heston model

hpinn

hPINN: Physics-informed neural networks with hard constraints

jaxpi

ldp-voloptions

Large Deviations for volatility options

market_simulator

Market simulator

mlfinlab

MlFinlab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

nn-stochvol-calibrations

We implement the paper: Deep Learning Volatility

presentations

Slide show presentations regarding data driven investing.

pyhessian

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

python_for_econometrics

「Pythonによる計量経済学入門」の正誤表とPythonコード

quantlib

The QuantLib C++ library

research

Notebooks based on financial machine learning.

rough-volatility-model--and--calibration

Implementation of the rough volatility model and its calibration

rough_heston

We implement the rough Heston model

rough_volatility

The pricing models and neural network representations used in part one of the paper "Empirical analysis of rough and classical stochastic volatility models to the SPX and VIX markets".

wavegrad

A fast, high-quality neural vocoder.