Projects list:
bagel-tushare
Github link: bagel-tushare
A Python wrapper for Tushare, a Chinese financial data provider. The project provides a simple and easy-to-use automation tool for downloading financial data from Tushare, and storing the data in a local mysql database.
bagel-mean-variance
Github link: bagel-mean-variance
bagel-mean-variance is a Python package designed to calculate optimal portfolio weights using the mean-variance optimization method. The package is implemented using pure matrix operations, avoiding the use of optimization libraries. It is simple, efficient, and flexible, making it ideal for financial analysis and portfolio management tasks. calculation method please refer to Mean-Variance analysis
bagel-factor
Github link: bagel-factor
bagel-factor is a universal, high-performance Python library for evaluating quantitative factor performance in equity trading. It’s flexible and efficient, built on pandas/numpy, and ships with a modular API for research and production.
Key Features
- Universality: price, fundamental, alternative data; daily or intraday.
- Performance: vectorized operations; minimal copying.
- Extensibility: plug in custom metrics and workflows.
- Usability: clear, typed API and ready-to-use plots.
Factor Model in China Stock Market
This project aims to build a stock scoring and backtesting system based on classical factor investing techniques. The goal is to start simple, generate interpretable results, and gradually expand into more sophisticated methods.