Mingcong Song's starred repositories
paper-reading
深度学习经典、新论文逐段精读
awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
tf-quant-finance
High-performance TensorFlow library for quantitative finance.
PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
pyalgotrade
Python Algorithmic Trading Library
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.
awesome-tensor-compilers
A list of awesome compiler projects and papers for tensor computation and deep learning.
Real-time-stock-market-prediction
In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model architecture, and Kafka for real-time data streaming and pipelining.
tickgrinder
Low-latency algorithmic trading platform written in Rust
fsi-samples
A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.
Enhanced-Event-Driven-Backtester
In this repository, an event-driven backtester is implemented based on QuantStart articles. The backtester is programmed in Python featuring numerous improvements, in terms of coding structure, data handling, and simple trading strategies.
rl-trader
This MLOps project productionizes a Deep Reinforcement Learning agent with a scalable, distributed data streaming infrastructure using Kafka and Ray. A thorough walkthrough of the code is described in this article on medium: https://ryanraymartin.medium.com/deep-reinforcement-learning-for-stock-trading-with-kafka-and-rllib-d738b9634675