本页是 / 的中文版本。专有名词和代码标识保持英文，以便和包 API 对齐。
BagelQuant 是什么？
BagelQuant is a knowledge base, open-source software ecosystem, and future research platform for quantitative equity portfolio management.
The goal is practical: understand how investment ideas become signals, how signals become forecasts, and how forecasts become portfolios that can be tested honestly. The site connects financial theory, statistics, machine learning, optimization, and research engineering around that workflow.
量化股票研究工作流
数据 → 因子 → 预测 → 组合 → 回测
This simple sequence is the spine of BagelQuant. Each step has its own questions: point-in-time data quality, signal design, predictive modeling, portfolio constraints, turnover, transaction costs, and reproducibility.
从这里开始
- 快速开始 gives newcomers a short guided introduction.
- 学习 is the deeper knowledge base for math, finance, models, and techniques.
- 研究 follows the practitioner workflow from data to backtesting.
项目与文档
- 项目 collects research outputs, reproductions, factor experiments, and portfolio cases.
- 文档 explains the BagelQuant open-source ecosystem, starting with
bagelquant-core.
未来应用
The future BagelQuant 应用 will provide a graph-based interface for building factors, prediction models, portfolio strategies, and backtests through reusable research pipelines.
关于我
BagelQuant is maintained by Yanzhong (Eric) Huang, a systematic investment researcher focused on equity alpha research and portfolio construction.