![](https://fastly.jsdelivr.net/gh/bucketio/img11@main/2024/10/21/1729466068183-23134fce-3131-4262-b18c-f378d71af4f6.gif)

# 财通中信逐鹿研报精选

![](https://fastly.jsdelivr.net/gh/bucketio/img9@main/2024/10/20/1729465031968-b3c8959e-1d37-4b8a-91b1-b0b0dfe25143.png)

## 系列简介

本系列收录了财通中信逐鹿相关的研究报告。

## 研报目录

### 财通中信-逐鹿系列

- [AlphaZero，基于AutoML_Zero的](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A12%EF%BC%9AAlphaZero%EF%BC%8C%E5%9F%BA%E4%BA%8EAutoML_Zero%E7%9A%84.pdf)
- [基于南向资金的选股择时策略](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A4%EF%BC%9A%E5%9F%BA%E4%BA%8E%E5%8D%97%E5%90%91%E8%B5%84%E9%87%91%E7%9A%84%E9%80%89%E8%82%A1%E6%8B%A9%E6%97%B6%E7%AD%96%E7%95%A5.pdf)
- [基本面因子与量价因子融合模型](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A14%EF%BC%9A%E5%9F%BA%E6%9C%AC%E9%9D%A2%E5%9B%A0%E5%AD%90%E4%B8%8E%E9%87%8F%E4%BB%B7%E5%9B%A0%E5%AD%90%E8%9E%8D%E5%90%88%E6%A8%A1%E5%9E%8B.pdf)
- [基于TiDE及其改进的因子融合模型](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A17%EF%BC%9A%E5%9F%BA%E4%BA%8ETiDE%E5%8F%8A%E5%85%B6%E6%94%B9%E8%BF%9B%E7%9A%84%E5%9B%A0%E5%AD%90%E8%9E%8D%E5%90%88%E6%A8%A1%E5%9E%8B.pdf)
- [基于领域知识生成的基本面因子挖掘框架](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A15%EF%BC%9A%E5%9F%BA%E4%BA%8E%E9%A2%86%E5%9F%9F%E7%9F%A5%E8%AF%86%E7%94%9F%E6%88%90%E7%9A%84%E5%9F%BA%E6%9C%AC%E9%9D%A2%E5%9B%A0%E5%AD%90%E6%8C%96%E6%8E%98%E6%A1%86%E6%9E%B6.pdf)
- [聪明的资金流向数据](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A3%EF%BC%9A%E8%81%AA%E6%98%8E%E7%9A%84%E8%B5%84%E9%87%91%E6%B5%81%E5%90%91%E6%95%B0%E6%8D%AE.pdf)
- [杠杆因子和盈利收益因子的风格轮动](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A5%EF%BC%9A%E6%9D%A0%E6%9D%86%E5%9B%A0%E5%AD%90%E5%92%8C%E7%9B%88%E5%88%A9%E6%94%B6%E7%9B%8A%E5%9B%A0%E5%AD%90%E7%9A%84%E9%A3%8E%E6%A0%BC%E8%BD%AE%E5%8A%A8.pdf)
- [基于限价订单簿数据的](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A11%EF%BC%9A%E5%9F%BA%E4%BA%8E%E9%99%90%E4%BB%B7%E8%AE%A2%E5%8D%95%E7%B0%BF%E6%95%B0%E6%8D%AE%E7%9A%84.pdf)
- [光伏行业因子投资框架，如何构建光伏行业指数增强策略](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A10%EF%BC%9A%E5%85%89%E4%BC%8F%E8%A1%8C%E4%B8%9A%E5%9B%A0%E5%AD%90%E6%8A%95%E8%B5%84%E6%A1%86%E6%9E%B6%EF%BC%8C%E5%A6%82%E4%BD%95%E6%9E%84%E5%BB%BA%E5%85%89%E4%BC%8F%E8%A1%8C%E4%B8%9A%E6%8C%87%E6%95%B0%E5%A2%9E%E5%BC%BA%E7%AD%96%E7%95%A5.pdf)
- [q-factor在A股实证及改进](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A2%EF%BC%9Aq-factor%E5%9C%A8A%E8%82%A1%E5%AE%9E%E8%AF%81%E5%8F%8A%E6%94%B9%E8%BF%9B.pdf)
- [北向机构持仓深入挖掘](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A8%EF%BC%9A%E5%8C%97%E5%90%91%E6%9C%BA%E6%9E%84%E6%8C%81%E4%BB%93%E6%B7%B1%E5%85%A5%E6%8C%96%E6%8E%98.pdf)
- [基于Graph Embedding的行业因子向量化](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A16%EF%BC%9A%E5%9F%BA%E4%BA%8EGraph%20Embedding%E7%9A%84%E8%A1%8C%E4%B8%9A%E5%9B%A0%E5%AD%90%E5%90%91%E9%87%8F%E5%8C%96.pdf)
- [基于超预期的事件驱动策略](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A7%EF%BC%9A%E5%9F%BA%E4%BA%8E%E8%B6%85%E9%A2%84%E6%9C%9F%E7%9A%84%E4%BA%8B%E4%BB%B6%E9%A9%B1%E5%8A%A8%E7%AD%96%E7%95%A5.pdf)
- [Model Zoo](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A18%EF%BC%9AModel%20Zoo.pdf)
- [基于QLIBALPHA360的Temporal_FusionTransformer选股模型](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A9%EF%BC%9A%E5%9F%BA%E4%BA%8EQLIBALPHA360%E7%9A%84Temporal_FusionTransformer%E9%80%89%E8%82%A1%E6%A8%A1%E5%9E%8B.pdf)
- [不同类型策略过去表现](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A%E5%B7%A1%E7%A4%BC%EF%BC%9A%E4%B8%8D%E5%90%8C%E7%B1%BB%E5%9E%8B%E7%AD%96%E7%95%A5%E8%BF%87%E5%8E%BB%E8%A1%A8%E7%8E%B0.pdf)
- [基于北向机构持仓的选股分析](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A6%EF%BC%9A%E5%9F%BA%E4%BA%8E%E5%8C%97%E5%90%91%E6%9C%BA%E6%9E%84%E6%8C%81%E4%BB%93%E7%9A%84%E9%80%89%E8%82%A1%E5%88%86%E6%9E%90.pdf)
- [基于openFE的](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A13%EF%BC%9A%E5%9F%BA%E4%BA%8EopenFE%E7%9A%84.pdf)
- [一致预期因子深度挖掘](https://asset.quant-wiki.com/pdf/%E9%80%90%E9%B9%BFAlpha%E4%B8%93%E9%A2%98%E6%8A%A5%E5%91%8A1%EF%BC%9A%E4%B8%80%E8%87%B4%E9%A2%84%E6%9C%9F%E5%9B%A0%E5%AD%90%E6%B7%B1%E5%BA%A6%E6%8C%96%E6%8E%98.pdf)

## 关于LLMQuant

LLMQuant是由一群来自世界顶尖高校和量化金融从业人员组成的前沿社区，致力于探索人工智能（AI）与量化（Quant）领域的无限可能。我们的团队成员来自剑桥大学、牛津大学、哈佛大学、苏黎世联邦理工学院、北京大学、中科大等世界知名高校，外部顾问来自Microsoft、HSBC、Citadel、Man Group、Citi、Jump Trading、国内顶尖私募等一流企业。