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.
citing papers explorer
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Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain
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.
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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.
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Hierarchical Reinforced Trader (HRT): A Bi-Level Approach for Optimizing Stock Selection and Execution
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.
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MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models
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.
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Bridging Language Models and Financial Analysis
A survey synthesizing recent LLM research and assessing its applicability to financial data analysis.