tsxgithub01

tsxgithub01's Stars

• StockSharp/StockSharp

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

  Language:C#7.3k5391691.8k

• scrtlabs/catalyst

  An Algorithmic Trading Library for Crypto-Assets in Python

  Language:Python2.5k168482725

• myhhub/stock

  stock股票.获取股票数据,计算股票指标,识别股票形态,综合选股,选股策略,股票验证回测,股票自动交易,支持PC及移动设备。

  Language:Python1.8k7978443

• PacktPublishing/Mastering-Python-for-Finance-Second-Edition

  Mastering Python for Finance – Second Edition, published by Packt

  Language:Jupyter Notebook452267209

• bones-ai/rust-snake-ai-ratatui

  Neural network learns to play snake in a terminal, built in Rust with Ratatui

  Language:Rust3953043

• Bohr1005/xcrypto

  quant,trading system,crypto,async

  Language:Rust33671395

• chenditc/investment_data

  Scripts and doc for https://www.dolthub.com/repositories/chenditc/investment_data

  Language:Python29074455

• tobiasbrodd/backtester

  An event-driven backtester

  Language:Python9410128

• ShiliangZhang-nku/HS300_index_enhance

  沪深300指数增强模型

  Language:Python755048

• google/xarray-tensorstore

  Language:Python51522

• DavidCico/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.

  Language:Python493318

• zsrl/bt-qmt-store

  Backtrader QMT Store

  Language:Python462020

• onebula/ONquant

  基于Matlab的事件驱动量化回测框架

  Language:MATLAB33608

• Macosh/Order_Book

  Simulator of a basic order book flow and order execution

  Language:Python178

• LHanLi/FreeBack

  高性能并行、事件驱动量化回测框架 high performance backtest，factor investing, portfiolio analysis

  Language:Jupyter Notebook10104

• domodo2012/quandomo2020

  an event-driver quantative trading platform.

  Language:Python7104

• mai1346/Epiphron

  一个基于事件驱动框架的回测平台

  Language:HTML4106

• RD-44/Pairstrading

  A high-frequency trading algorithm implemented in python. We use the NSGA-II (Non dominated sorting genetic algorithm) for multi-objective optimisation to find optimal pairs to trade. We attempt to use objective functions including the Augmented Dickey-Fuller test statistic, standard deviation, number of zeroes crossed and the norm of the spread.

  Language:Jupyter Notebook4100

• boluo999/xx_quant

  Language:Python31

• jonasdepaolis/market-replay

  Simple market replay engine running on L2 LOB data.

  Language:Python3100

• RGermain97/Trend-Scanning-Labelling

  Trend scanning labelling as documented by quantitative hedge fund manager. Dr. Lopez De Prado

  310

• bluebell136/backtest-lib

  HFT backtest-engine for LOB data.

  Language:Python20017

• porcelaincode/trading

  High performance high frequency trading server that runs monte carlo simulations for trading options, written in python

  Language:Python2102

• AdityaPulyapudi/Backtesting-on-LOB-models

  This repo is in relation with LOB deep learning models and shows the methods used to apply backtesting on LOB deep learning model using historical data

  Language:Jupyter Notebook1100

• AI-rcl/tick_backtest

  Language:Jupyter Notebook10

• fanyiyang/How-and-When-are-High-Frequency-Stock-Returns-Predictable

  How and When are High-Frequency Stock Returns Predictable?

  Language:Python1101

• muhammad2702/High-Frequency-Market-Making-System

  Language:C++110

• pmullin33/DQN_HFT

  Deep Q Learning for High Frequency Trading

  Language:Python1100

• tf83f/Algorithmic_and_High_Frequency_Trading

  Language:Jupyter Notebook110

• Usman4D/High-Frequency-Trading-Price-Prediction

  Language:Jupyter Notebook110