宣传一下：我自用的对qlib模型推理结果做的多agent策略分析
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 48.7k
- Forks
- 7.7k
- PR merge metrics
- No merged PRs in 30d
Description
qlib是一个非常好的项目，为散户做量化提供了路径，但是当前模型推理得到topk之后，一方面，散户往往没有足够的资金量购买所有topk股票；另一方面，topk里面可能包含一些较差的股票，为了降低风险，所以需要一套适用于散户的投资策略。
基于qlib的结果，我开发了一套基于LLM的多agent策略来帮助决策，包括更多的数据源，以及用于分析资料的八个员工：宏观分析师、行业政策分析师、 估值分析师、基本面分析师、技术分析师、舆情分析师、风险经理、独立监察员，根据个人风格，可以选取不同的大师（本杰明·格雷厄姆、沃伦·巴菲特、菲利普·费雪、彼得·林奇、约翰·邓普顿...）来帮助分析得到最终的决策，项目地址：https://github.com/freenowill/stock-fish
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue describes an external project at github.com/freenowill/stock-fish and does not name any Qlib files, tests, or entry points. Start by reviewing the linked project and its relationship to Qlib; there is no concrete change or completion criterion stated in this issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, fintech-quant, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100