Stars
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
FinRL®: Financial Reinforcement Learning. 🔥
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Automatic extraction of relevant features from time series:
tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials
Data Science Using Python
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Create delightful software with Jupyter Notebooks
Technical Analysis Library using Pandas and Numpy
A better notebook for Scala (and more)
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
Performance analysis of predictive (alpha) stock factors
Productivity Tools for Plotly + Pandas
TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning 🔥 ⚡ 🌈
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
零知识证明入门教程。Comprehensive Zero-Knowledge Proofs Tutorial. #zk #WIP
Environment for reinforcement-learning algorithmic trading models
Attempting to replicate "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" https://arxiv.org/abs/1706.10059 (and an openai gym environment)
This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-201…
Learning to trade under the reinforcement learning framework