Can ChatGPT Overcome Behavioral Biases in the Financial Sector? Classify-and-Rethink: Multi-Step Zero-Shot Reasoning in the Gold Investment
Shuoling Liu, Gaoguo Jia, Yuhang Jiang, Liyuan Chen, Qiang Yang

TL;DR
This paper investigates ChatGPT's ability to improve financial reasoning and overcome behavioral biases in investment decisions using multi-step zero-shot reasoning and prompt engineering.
Contribution
It is the first to apply ChatGPT with Chain-of-Thought prompts to financial reasoning, demonstrating improved explainability and bias mitigation in gold investment analysis.
Findings
ChatGPT with CoT prompts offers more explainable predictions.
It can overcome behavioral biases in financial decision-making.
Achieves higher investment returns in gold investment tasks.
Abstract
Large Language Models (LLMs) have achieved remarkable success recently, displaying exceptional capabilities in creating understandable and organized text. These LLMs have been utilized in diverse fields, such as clinical research, where domain-specific models like Med-Palm have achieved human-level performance. Recently, researchers have employed advanced prompt engineering to enhance the general reasoning ability of LLMs. Despite the remarkable success of zero-shot Chain-of-Thoughts (CoT) in solving general reasoning tasks, the potential of these methods still remains paid limited attention in the financial reasoning task.To address this issue, we explore multiple prompt strategies and incorporated semantic news information to improve LLMs' performance on financial reasoning tasks.To the best of our knowledge, we are the first to explore this important issue by applying ChatGPT to the…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Explainable Artificial Intelligence (XAI)
MethodsSoftmax · Attention Is All You Need · Focus
