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Stars
Watches files and records, or triggers actions, when they change.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
高频量化交易平台 C++ Trade Platform for quant developer 【浮生着甚苦奔忙,量化之路阻且长。 行行代码凝心血,十年辛苦不寻常】
python implement for WorldQuant-Alpha101
A Detailed Cplusplus Concurrency Tutorial 《C++ 并发编程指南》
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube
Momentum following strategies and optimal execution cost upon Implement Shortfall algorithm
A curated list of awesome algorithmic trading frameworks, libraries, software and resources
Code for Machine Learning for Algorithmic Trading, 2nd edition.
TFM: Aplicaciones de Aprendizaje Automático para la mejora de estrategias de ejecución algorítmica
Volume Weighted Average Price Optimal Execution
quantitative trading with Javascript, Python, C++, PineScript, Blockly, MyLanguage(麦语言)
Seamless operability between C++11 and Python
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
All Algorithms implemented in Python
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
Various machine learning models are used to predict the VWAP(Volume Weighted Average Price) from the NIFTY datasets, analysis and prediction of financial data of MNCs provided by Ratnabali Group
Hidden Markov Models in Python, with scikit-learn like API
Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory
Stock Price Prediction using Machine Learning Techniques
scikit-learn: machine learning in Python
The "Python Machine Learning (1st edition)" book code repository and info resource
💬 A better WeChat on macOS and Linux. Built with Electron by Zhongyi Tong.
Modeling high-frequency limit order book dynamics with support vector machines