#python #algorithmic_trading #auto_quant #finance #investment #machine_learning #platform #quant #quant_dataset #quant_models #quantitative_finance #quantitative_trading #stock_data

https://github.com/microsoft/qlib

#python #algorithmic_trading #auto_quant #deep_learning #finance #fintech #investment #machine_learning #paper #platform #python #quant #quant_dataset #quant_models #quantitative_finance #quantitative_trading #research #research_paper #stock_data

Qlib is an open-source platform for quantitative investment that uses AI technologies. It supports various machine learning models and helps in finding valuable signals in financial data, adapting to market dynamics, and optimizing trading strategies. Here are the key benefits Qlib introduces RD-Agent, a tool that automates factor mining and model optimization, making it easier to develop quant investment strategies.
- **Diverse Machine Learning Models** It covers the entire chain of quantitative investment, including data processing, model training, backtesting, and order execution.
- **Customizable Workflows** Qlib's data server is optimized for performance, allowing fast data processing and retrieval, which is crucial for real-time trading decisions.

Overall, Qlib simplifies the process of building and optimizing quant investment strategies, making it a powerful tool for researchers and investors.

https://github.com/microsoft/qlib