joshua-xia

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.

Algorithm_Interview_Notes-Chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

algorithmic-trading-with-python

Source code for Algorithmic Trading with Python (2020) by Chris Conlan

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

awesome-quant-1

中国的Quant相关资源索引

backtrader

Python Backtesting library for trading strategies

btgym

Scalable, event-driven, deep-learning-friendly backtesting library

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。

LTSF-Linear

This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"

joshua-xia/LTSF-Linear

This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"

joshua-xia/AI-Strategies-StockMarket

App to test strategies based on artificial intelligence for investing in the stock market.

joshua-xia/Algo-Trading-with-Genetic-Algorithm

Algo trading with strategy customization, genetic algorithm for hyper params optimizing, and backtesting.

joshua-xia/algorithmic-trading-with-python

Source code for Algorithmic Trading with Python (2020) by Chris Conlan

joshua-xia/backtrader

Python Backtesting library for trading strategies

joshua-xia/btgym

Scalable, event-driven, deep-learning-friendly backtesting library

joshua-xia/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。

joshua-xia/DEAP-learning

🧬learn DEAP, python lib for GA (not deep learning)

joshua-xia/deep_rl_trader

Trading Environment(OpenAI Gym) + DDQN (Keras-RL)

joshua-xia/DeepLearning

深度学习入门教程, 优秀文章, Deep Learning Tutorial

joshua-xia/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！🚀🚀🚀

joshua-xia/finance_ml

Advances in Financial Machine Learning

joshua-xia/gym-anytrading

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

joshua-xia/HMMs_Stock_Market

Contains all code related to using HMMs to predict stock market prices.

joshua-xia/Kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

joshua-xia/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

joshua-xia/M2

joshua-xia/machine-learning-for-trading

Code for Machine Learning for Algorithmic Trading, 2nd edition.

joshua-xia/macos-web

joshua-xia/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.

joshua-xia/MLFINLAB-1

public version of MLFINLAB from Hudson-Thames

joshua-xia/pycaret

An open-source, low-code machine learning library in Python

joshua-xia/PyPortfolioOpt

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

joshua-xia/rl-hyperparameter-tuning

Code I wrote while trying out hyperparameter tuning in reinforcement learning

joshua-xia/RLTrader

A cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym

joshua-xia/Stock-Prediction-Models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

joshua-xia/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.

joshua-xia/Time-Series-Analysis

code and data for the time series analysis vids on my YouTube channel

joshua-xia/Time-Series-Forecasting-and-Deep-Learning

Resources about time series forecasting and deep learning.

joshua-xia/zipline_bundle

Create custom Zipline data bundles from Binance API