Joshua Xia's repositories
LTSF-Linear
This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"
AI-Strategies-StockMarket
App to test strategies based on artificial intelligence for investing in the stock market.
Algo-Trading-with-Genetic-Algorithm
Algo trading with strategy customization, genetic algorithm for hyper params optimizing, and backtesting.
algorithmic-trading-with-python
Source code for Algorithmic Trading with Python (2020) by Chris Conlan
backtrader
Python Backtesting library for trading strategies
d2l-zh
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被55个国家的300所大学用于教学。
DEAP-learning
🧬learn DEAP, python lib for GA (not deep learning)
deep_rl_trader
Trading Environment(OpenAI Gym) + DDQN (Keras-RL)
DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
efinance
efinance 是一个可以快速获取基金、股票、债券、期货数据的 Python 库,回测以及量化交易的好帮手!🚀🚀🚀
finance_ml
Advances in Financial Machine Learning
gym-anytrading
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
HMMs_Stock_Market
Contains all code related to using HMMs to predict stock market prices.
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-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
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.
MLFINLAB-1
public version of MLFINLAB from Hudson-Thames
pycaret
An open-source, low-code machine learning library in Python
PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
rl-hyperparameter-tuning
Code I wrote while trying out hyperparameter tuning in reinforcement learning
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
Time-Series-Analysis
code and data for the time series analysis vids on my YouTube channel
Time-Series-Forecasting-and-Deep-Learning
Resources about time series forecasting and deep learning.
zipline_bundle
Create custom Zipline data bundles from Binance API