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Quant \ Trading \ Momentum Strategy

Firstly, multiple effective factors are discovered through IC value, IR value, and correlation analysis and back-testing. Then, XGBoost classification model is adopted to predict whether the stock is profitable in the next month, and the positions are adjusted monthly. The idea of mean-variance a... Read more

tbg-Quant strategies examples

Open-source GUI-based quantitative backtesting platform for strategy development, market visualization, and collaborative quant research.

chameleonQuant was born as an open-source Java framework to help enthusiast quants to implement system trading strategies and dynamic portfolio trading systems using advanced optimization techniques, machine learning, and deep learning techniques.

pTrade Quant strategy

A humble repository for academic quant strategies

This project uses Python to create an optimally weighted stock portfolio by combining 7 common technical indicators, generating trading signals, backtesting the strategy, and aiming to outperform the standard buy-and-hold strategy of the SPY ETF.

Quant finance Portal based on project BearAlpha. This project contains strategy back test framework with backtrader, database construct with BearAlpha, factor analyze based on BearAlpha, and financial researches on paper or report with research

Webull OpenAPI aims to provide quantitative trading investors with convenient, fast and secure services. Webull aims to help every quant traders achieve flexible and changeable trading or market strategies.