Backtest and live trading in Python
A dockerized Jupyter quant research environment.
Python package that enables access to the entire Darwinex Data Offering (DARWIN, FX, Stock, Commodity, Index and Cryptocurrency assets) from one Wrapper Library.
Quant \ Trading \ Momentum Strategy
A quantitative trading strategy backtester with an interactive dashboard. Enables users to implement, test, and visualise trading strategies using historical market data, featuring customisable parameters and key performance metrics. Developed with Python and Polars.
Equities Pair Trading/Statistical Arbitrage and Multi-Variable Index Regression
Quant Trading with Microsoft Qlib (https://github.com/microsoft/qlib)
A multi-exchange, multi-symbol grid trading bot for crypto futures. Supports Binance & OKX & Gate.io, dual-side hedging, risk control, and Docker deployment.
Best GitHub Repo from Algorithm Trader, where Quant is applied in Financial Data. This will include multiple segments and different technolgy to get the outcome
Nautilus_Trader_Jerry_fall_2023 is a customized verision of Nautilus trader by Zhuoran "Jerry" Li on Fall 2023
Welcome
A set of personal trading and quant research projects in the crypto markets.
Backtesting framework for the London Open Breakout strategy with signal filters, MT5 integration, and result analysis.
💎 Live trading crypto on DeFi exchanges. Data analytics using the Deribit API and Dune Analytics.
Pot 50 & 200 days Simple moving average (SMA). Created class SMApython and used in TestOne
Quantitative Backtester for algo-trading strategies
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