Summary of Tradexpert: Revolutionizing Trading with Mixture Of Expert Llms, by Qianggang Ding et al.
TradExpert: Revolutionizing Trading with Mixture of Expert LLMs
by Qianggang Ding, Haochen Shi, Bang Liu
First submitted to arxiv on: 16 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Statistical Finance (q-fin.ST)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This AI-powered trading framework, called TradeExpert, leverages four specialized Large Language Models (LLMs) to analyze diverse financial data sources, including news articles, market data, alpha factors, and fundamental data. These LLMs are combined using a mix of experts approach, with insights synthesized by a General Expert LLM to make predictions or decisions. The framework can be switched between prediction mode for stock movement forecasting and ranking mode for quantitative trading. TradeExpert outperforms existing methods across various trading scenarios. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary TradeExpert is a new way to use AI in finance. It looks at lots of different types of data, like news articles and market trends, to make smart decisions about buying and selling stocks. The system uses special language models that are trained on different kinds of information, and then combines their insights to make the best choice. This can help people who trade stocks or invest money to make more informed decisions. |
