tjevgerres

agents

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

ai_quant_trade

(Eng. Incl.) 股票AI操盘手：包含股票知识、策略实例、机器学习、深度学习、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易

altair

Declarative statistical visualization library for Python

autoreset_rl

Official TensorFlow implementation of the paper "Automating Reinforcement Learning with Example-based Resets"

awesome-data

Awesome-data shows most interesting data-source around the financial world!

Awesome_AI4Finance

A collection of practical resources by the AI4Finance Foundation

backtrader

chanvis

基于TradingView本地SDK的可视化前后端代码，适用于缠论量化研究，和其他的基于几何交易的量化研究。 缠论量化 摩尔缠论 缠论可视化 TradingView TV-SDK

ChZhShCh

部分缠论技术的程序化实践

code_demo

源码解析小班课

ElegantRL

Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

FinRL

FinRL: Financial Reinforcement Learning Framework. Please star. 🔥

FinRL-Meta

FinRL­-Meta: A Universe for Data­-Driven Financial Reinforcement Learning. 🔥

FinRL-Tutorials

Tutorials for FinRL and FinRL-Meta. Please star.

High-Frequency-Trading-Model-with-IB

A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python

machine-learning-for-trading

Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading

mplfinance

Financial Markets Data Visualization using Matplotlib

QuantResearch

Quantitative analysis, strategies and backtests

quanttrader

Backtest and live trading in Python

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

rl-book-1

Source codes for the book "Reinforcement Learning: Theory and Python Implementation"

rlalgorithms-tf2

Packaged deep reinforcement learning algorithms in tensorflow 2.x

simple-czsc

Simple缠论量化工具集

stock-1

股票行情数据 东方财富交易接口 股票自动交易

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.

StockSharp

Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).

Tensorflow-2-Reinforcement-Learning-Cookbook

Tensorflow 2 Reinforcement Learning Cookbook, published by Packt

TensorLayerX

TensorLayerX: A Unified Deep Learning and Reinforcement Learning Framework for All Hardwares, Backends and OS.

vnpy_mt5

vn.py框架的MT5交易接口

www

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