SGX-Full-OrderBook-Tick-Data-Trading-Strategy

Order Book Analyzer

Develops a framework to analyze high-frequency limit order book data and predict market outcomes using machine learning algorithms.

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

GitHub

2k stars
100 watching
667 forks
Language: Jupyter Notebook
last commit: about 2 years ago
Linked from 2 awesome lists

algorithmic-tradingbacktesting-trading-strategiesfeature-engineeringfeature-selectionhigh-frequency-tradinginvestmentlimit-order-bookmachine-learningmarket-makermarket-makingmarket-microstructuremodel-selectionorderbookorderbook-tick-datapythonquantquantitative-tradingtradingtrading-strategies

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
crypto-toolbox/hft-orderbook An implementation of a limit order book data structure for high-frequency trading in C. 1,012
heerozh/spectre A high-performance, GPU-accelerated library for building quantitative trading strategies using factor analysis and backtesting 645
ghgr/hft_bitcoin An analysis tool for studying high frequency trading patterns on Bitcoin exchanges 151
0b01/tectonicdb A fast and efficient database for storing high-frequency trading order book data in binary format. 686
sravb/algorithmic-trading An algorithmic trading system using machine learning and historical stock data to predict price movements. 113
packtpublishing/hands-on-machine-learning-for-algorithmic-trading Teaches data analysts and developers to create smart investment strategies using machine learning algorithms 1,493
robcarver17/systematictradingexamples A collection of code examples focused on systematic trading strategies and related algorithms using Python. 370
edouardpoitras/nowtrade A Python library for creating and backtesting algorithmic trading strategies using machine learning and technical indicators. 104
nkaz001/hftbacktest A framework for simulating high-frequency trading and market-making strategies with realistic latency and order book simulations. 1,991
fasiondog/hikyuu An open-source framework providing a set of pre-built components and tools for building trading strategies and backtesting them on financial markets. 2,214
jrmeier/fast-trade A Python library for building and backtesting trading strategies using technical analysis indicators. 377
ram-ki/101_formulaic_alphas This project implements 101 algorithmic trading strategies using Python to generate superior returns relative to a benchmark. 15
letianzj/quantresearch A collection of notebooks and blogs on quantitative finance and trading strategies, including machine learning, deep reinforcement learning, and backtesting. 2,113
tradingstrategy-ai/getting-started A repository providing examples and tools for developing and backtesting algorithmic trading strategies in Python. 59
ha2emnomer/deep-trading This is an implementation of a trading algorithm using RNNs to predict stock return prices based on S&P 500 index movements. 32