Unveiling the Potential of Sentiment: Can Large Language Models Predict Chinese Stock Price Movements?

arXiv:2306.14222v2 Announce Type: replace
Abstract: The rapid advancement of Large Language Models (LLMs) has spurred discussions about their potential to enhance quantitative trading strategies. LLMs excel in analyzing sentiments about listed companies from financial news, providing critical insights for trading decisions. However, the performance of LLMs in this task varies substantially due to their inherent characteristics. This paper introduces a standardized experimental procedure for comprehensive evaluations. We detail the methodology using three distinct LLMs, each embodying a unique approach to …

abstract advancement arxiv chinese companies cs.ai cs.cl decisions discussions excel financial however insights language language models large language large language models llms movements performance price q-fin.st quantitative sentiment stock stock price strategies trading type