chenhq's repositories
Data-Mining-on-BTC-Trading-Statistics
Develop about 200 alpha factors from securities report etc, Grid Search/Random Search/Particle Swarm Optimization to improve factors performance
etl-with-airflow
ETL best practices with airflow, with examples
ascii-transfer
Simple ascii transfer protocol for sending files to/from e.g., a robot. Think Kermit or Zmodem but super simple.
awesome-feature-engineering
A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
Barra-Model
An internship project: Implement Barra model to take risk or style factor attribution based on multi-factor model.
BitcoinExchangeFH
Cryptocurrency exchange market data feed handler
Deep-Trading
Algorithmic trading with deep learning experiments
deep_trader
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.
docker-stacks
Ready-to-run Docker images containing Jupyter applications
feature-engineering-and-feature-selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
FeatureSelectionGA
Feature Selection using Genetic Algorithm (DEAP Framework)
hadoop-docker
Docker container, distributed cluster based on Hadoop.
KalmanFilter
This project is the use of Kalman filter in estimating stock betas
LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
machine-learning-mindmap
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
machine-learning-yearning
Translation of <Machine Learning Yearning> by Andrew NG
Neural-Network-with-Financial-Time-Series-Data
This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow
SLURM
SLURM Example Scripts
Test-stock-prediction-algorithms
Use deep learning, genetic programming and other methods to predict stock and market movements