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Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models

arXiv 2304.07619 ↗First posted 15 Apr 2023q-fin.ST cs.CLcited by 129

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Abstract (arXiv)

We document the capability of large language models (LLMs) like ChatGPT to predict stock market reactions from news headlines without direct financial training. Using post-knowledge-cutoff headlines, GPT-4 captures initial market responses, achieving approximately 90% portfolio-day hit rates for the non-tradable initial reaction. GPT-4 scores also significantly predict the subsequent drift, especially for small stocks and negative news. Forecasting ability generally increases with model size, suggesting that financial reasoning is an emerging capacity of complex LLMs. Strategy returns decline as LLM adoption rises, consistent with improved price efficiency. To rationalize these findings, we develop a theoretical model that incorporates LLM technology, information-processing capacity constraints, underreaction, and limits to arbitrage.

Key facts. Cited by 129 papers in the map (data through 14 Oct 2026). Builds on 3 of its 79 references that are in the map. First posted on arXiv 15 Apr 2023.

Builds on

3 of 79 references.

References · 3

  1. 2017Attention Is All You Needcited by 60,361
  2. 2023BloombergGPT: A Large Language Model for Financecited by 939
  3. 2023The Wall Street Neophyte: A Zero-Shot Analysis of ChatGPT Over MultiModal Stock Movement Prediction Challengescited by 59

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 29; 2024: 32; 2025: 27; 2026: 41.

129 papers.

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  1. 2023A Survey on Evaluation of Large Language Modelscited by 1,242
  2. 2023PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Financecited by 222
  3. 2024TradingAgents: Multi-Agents LLM Financial Trading Frameworkcited by 188
  4. 2023Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Surveycited by 135
  5. 2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 110
  6. 2024Revolutionizing Finance with LLMs: An Overview of Applications and Insightscited by 90
  7. 2024A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challengescited by 90
  8. 2024Empowering Time Series Analysis with Large Language Models: A Surveycited by 60
  9. 2024Large Language Model Agent in Financial Trading: A Surveycited by 60
  10. 2024GraphArena: Evaluating and Exploring Large Language Models on Graph Computationcited by 49
  11. 2024Position: What Can Large Language Models Tell Us about Time Series Analysiscited by 47
  12. 2025R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimizationcited by 43
38 more
  1. 2023ChatGPT Informed Graph Neural Network for Stock Movement Predictioncited by 41
  2. 2023Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysiscited by 31
  3. 2024Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selectioncited by 29
  4. 2024AI for social science and social science of AI: A Surveycited by 29
  5. 2024Simulating Financial Market via Large Language Model based Agentscited by 25
  6. 2023Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Modelscited by 24
  7. 2024Empowering Time Series Analysis with Foundation Models: A Comprehensive Surveycited by 23
  8. 2025LLM-Powered AI Agent Systems and Their Applications in Industrycited by 22
  9. 2024Towards Modeling Learner Performance with Large Language Modelscited by 21
  10. 2023An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applicationscited by 20
  11. 2025Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?cited by 20
  12. 2024An overview of domain-specific foundation model: key technologies, applications and challengescited by 19
  13. 2024Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oraclecited by 19
  14. 2025BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modelingcited by 19
  15. 2023AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrievalcited by 18
  16. 2023Integrating Stock Features and Global Information via Large Language Models for Enhanced Stock Return Predictioncited by 17
  17. 2023Unveiling the Potential of Sentiment: Can Large Language Models Predict Chinese Stock Price Movements?cited by 15
  18. 2025Visual Structures Helps Visual Reasoning: Addressing the Binding Problem in VLMscited by 15
  19. 2025Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learningcited by 15
  20. 2023ChatGPT vs. Google: A Comparative Study of Search Performance and User Experiencecited by 12
  21. 2023GPT-InvestAR: Enhancing Stock Investment Strategies through Annual Report Analysis with Large Language Modelscited by 12
  22. 2024TradExpert: Revolutionizing Trading with Mixture of Expert LLMscited by 12
  23. 2025A Survey on Mathematical Reasoning and Optimization with Large Language Modelscited by 12
  24. 2024StockGPT: A GenAI Model for Stock Prediction and Tradingcited by 11
  25. 2023ChatGPT in the Age of Generative AI and Large Language Models: A Concise Surveycited by 10
  26. 2023A Comprehensive Review on Financial Explainable AIcited by 10
  27. 2024AI in Investment Analysis: LLMs for Equity Stock Ratingscited by 10
  28. 2024Auto-Regressive Moving Diffusion Models for Time Series Forecastingcited by 10
  29. 2024Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Modelscited by 9
  30. 2023A Preliminary Analysis on the Code Generation Capabilities of GPT-3.5 and Bard AI Models for Java Functionscited by 8
  31. 2023Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecastingcited by 8
  32. 2023ChatGPT-based Investment Portfolio Selectioncited by 8
  33. 2023Ask Again, Then Fail: Large Language Models' Vacillations in Judgmentcited by 8
  34. 2025OptiChat: Bridging Optimization Models and Practitioners with Large Language Modelscited by 8
  35. 2025A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysiscited by 8
  36. 2025ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanismcited by 8
  37. 2023Several categories of Large Language Models (LLMs): A Short Surveycited by 7
  38. 2023GPT has become financially literate: Insights from financial literacy tests of GPT and a preliminary test of how people use it as a source of advicecited by 7

50 most cited of 129 All 129 (JSON)