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Junyi's Projects

afml-exercises icon afml-exercises

All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.

alphagen icon alphagen

Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning.

arbitragelab icon arbitragelab

ArbitrageLab is a python library that enables traders who want to exploit mean-reverting portfolios by providing a complete set of algorithms from the best academic journals.

causality-benchmark-data icon causality-benchmark-data

Showcasing Causality Group's benchmark data through a data loading library and a signal backtesting example.

geneticalgorithmpython icon geneticalgorithmpython

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

ipca icon ipca

Instrumented Principal Components Analysis

meta-labeling icon meta-labeling

Code base for the meta-labeling papers published with the Journal of Financial Data Science

mtl-comb icon mtl-comb

Optimizing accuracy and diversity: a multi-task approach to forecast combinations

pykalman icon pykalman

Kalman Filter, Smoother, and EM Algorithm for Python

quantgans icon quantgans

Codes for my thesis project: replicating and modifying quant GANs.

research_notebooks icon research_notebooks

Analysis on systematic trading strategies (e.g., trend-following, carry and mean-reversion). The result is regularly updated.

slow-momentum-fast-reversion icon slow-momentum-fast-reversion

This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (https://arxiv.org/pdf/2105.13727.pdf).

stat-learning icon stat-learning

Notes and exercise attempts for "An Introduction to Statistical Learning"

stock-market-data icon stock-market-data

Contains various data for the stock market and stocks including news, price and fundamentals (ratios)

trading-momentum-transformer icon trading-momentum-transformer

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

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