LLMs copy biased analyst ratings in investment decisions but a new detection method encourages independent reasoning and can improve stock return predictions beyond human levels.
Instruct-FinGPT: Financial sentiment analysis by instruction tuning of general-purpose large language models.arXiv preprint arXiv:2306.12659
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A survey proposing a taxonomy of Injective, Bridging, and Internal Alignment paradigms to evolve TSA into user-driven Time Series Question Answering with LLMs.
HRT is a bi-level RL framework with a sparse high-level controller for asset direction selection from signals and a risk-aware low-level controller for weight adjustments, reporting Sharpe 1.24 and turnover 0.090 on 2020-2023 Nasdaq data.
MadEvolve uses LLMs for evolutionary optimization of trading strategies and reports significant backtest improvements on Bitcoin tasks including signal feature evolution and joint strategy optimization.
A survey synthesizing recent LLM research and assessing its applicability to financial data analysis.
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From Time Series Analysis to Question Answering: A Survey in the LLM Era
A survey proposing a taxonomy of Injective, Bridging, and Internal Alignment paradigms to evolve TSA into user-driven Time Series Question Answering with LLMs.