What is BagelQuant?
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.
The Quant Equity Workflow
Data → Factor → Prediction → Portfolio → Backtest
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.
Start Here
- Quick Start gives newcomers a short guided introduction.
- Learn is the deeper knowledge base for math, finance, models, and techniques.
- Research follows the practitioner workflow from data to backtesting.
Projects and Docs
- Projects collects research outputs, reproductions, factor experiments, and portfolio cases.
- Docs explains the BagelQuant open-source ecosystem, starting with
bagelquant-core.
Future App
The future BagelQuant App will provide a graph-based interface for building factors, prediction models, portfolio strategies, and backtests through reusable research pipelines.
About Me
BagelQuant is maintained by Yanzhong (Eric) Huang, a systematic investment researcher focused on equity alpha research and portfolio construction.