Potential of ChatGPT in predicting stock market trends based on Twitter Sentiment Analysis

ArXiv ID: 2311.06273 “View on arXiv”

Authors: Unknown

Abstract

The rise of ChatGPT has brought a notable shift to the AI sector, with its exceptional conversational skills and deep grasp of language. Recognizing its value across different areas, our study investigates ChatGPT’s capacity to predict stock market movements using only social media tweets and sentiment analysis. We aim to see if ChatGPT can tap into the vast sentiment data on platforms like Twitter to offer insightful predictions about stock trends. We focus on determining if a tweet has a positive, negative, or neutral effect on two big tech giants Microsoft and Google’s stock value. Our findings highlight a positive link between ChatGPT’s evaluations and the following days stock results for both tech companies. This research enriches our view on ChatGPT’s adaptability and emphasizes the growing importance of AI in shaping financial market forecasts.

Keywords: Sentiment Analysis, Large Language Models, Social Media Data, Stock Market Prediction, Natural Language Processing, Equities

Complexity vs Empirical Score

• Math Complexity: 3.0/10
• Empirical Rigor: 4.0/10
• Quadrant: Philosophers
• Why: The paper relies on prompt engineering and sentiment analysis using a pre-trained model (ChatGPT) with minimal custom mathematical modeling or statistical derivations. The empirical rigor is limited due to the use of a small, non-curated dataset, lack of robust backtesting, and minimal control for noise and market microstructure.

  flowchart TD
    A["Research Goal: Can ChatGPT predict<br>stock trends using Twitter sentiment?"]
    A --> B["Data Input:<br>Twitter Tweets"]
    B --> C["Computational Process:<br>ChatGPT Sentiment Analysis"]
    C --> D["Target: Microsoft & Google Stocks"]
    D --> E["Key Finding: Positive Correlation<br>between Sentiment & Next-Day Returns"]