A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges
By Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren
Rating
869
Battle Count: 197
Relevance
9/10
The paper provides extensive insights into how LLMs can be applied to various aspects of quantitative trading, including sentiment analysis, market prediction, and strategy development.
Implementation Complexity
7/10
While the paper itself doesn't provide implementation details, applying LLMs to financial tasks as described can be complex due to data requirements, model fine-tuning, and domain-specific adaptations.
Reproducibility
4/5
The paper provides a comprehensive overview of existing research, making it relatively reproducible for future studies.
About this paper
Methodology: Survey. Problem types: Natural Language Processing, Time Series Forecasting, Classification, Regression, Sentiment Analysis.
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