Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Develop high-frequency trading strategies using machine learning on order book data.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeProviding the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
SGX-Full-OrderBook-Tick-Data-Trading-Strategy has 2.3k stars on GitHub. It has been forked 695 times. SGX-Full-OrderBook-Tick-Data-Trading-Strategy is written mainly in Jupyter Notebook. It has been in active development since 2016. Its main topics are algorithmic-trading, backtesting-trading-strategies, feature-engineering, feature-selection.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
SGX-Full-OrderBook-Tick-Data-Trading-Strategy is an open-source project.
Yes. SGX-Full-OrderBook-Tick-Data-Trading-Strategy is free and open source — you can use, modify and self-host it.
SGX-Full-OrderBook-Tick-Data-Trading-Strategy is written mainly in Jupyter Notebook.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/rorysroes-sgx-full-orderbook-tick-data-trading-strategy.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.