This repository provides a curated collection of resources for individuals looking to enter the field of quantitative finance. It offers an open-source tutorial based on a multi-factor stock quantitative investment research framework, alongside a compilation of academic and industry-relevant materials.

How It Works

The project is structured around a multi-factor stock quantitative investment research framework, with plans to open-source research content from the Hunan University Financial Technology Association's Quant Group. The repository also compiles various resources including technical indicator backtesting code, sell-side quantitative research reports, papers on investor sentiment and behavioral finance, and notes from quantitative research internships.

Quick Start & Requirements

• Install/Run: No specific installation or run commands are provided in the README. The content appears to be primarily informational and resource-based.
• Prerequisites: Access to academic papers (arXiv, SSRN), potentially Python for backtesting code, and familiarity with quantitative finance concepts.
• Resources: Links to external resources like Datawhale's quantitative open-source courses and various quantitative forums are provided.

Highlighted Details

• Includes an open-source tutorial based on a multi-factor stock quantitative investment research framework.
• Compiles resources on data sources, alternative data, factor mining, portfolio optimization, and risk control.
• Features links to domestic and international quantitative forums and learning platforms.
• Covers topics from academic papers on Asset Pricing, Behavioral Finance, and LLMs in Quant.

Maintenance & Community

The project welcomes contributions and suggestions via the Discussions tab. Contact information (email, WeChat) is provided for direct communication. The project aims for weekly updates on arXiv and SSRN papers.

Licensing & Compatibility

The licensing is not explicitly stated in the README. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The compiled resources may be incomplete, and users are encouraged to provide suggestions. The project is a personal compilation and may not represent a fully structured or production-ready framework.