Predicting stock prices with ChatGPT-annotated Reddit sentiment

TL;DR

This study evaluates whether Reddit sentiment can predict stock prices, finding weak correlation with sentiment but stronger signals from comment volume and search trends, highlighting the complexity of retail investor influence.

Contribution

Introduces a ChatGPT-annotated sentiment analysis model and compares its effectiveness with existing methods in predicting stock movements from social media data.

Findings

Social media sentiment has weak correlation with stock prices.

Comment volume and search trends are better predictors than sentiment.

Traditional sentiment analysis may not fully capture online market influence.

Abstract

The surge of retail investor activity on social media, exemplified by the 2021 GameStop short squeeze, raised questions about the influence of online sentiment on stock prices. This paper explores whether sentiment derived from social media discussions can meaningfully predict stock market movements. We focus on Reddit's r/wallstreetbets and analyze sentiment related to two companies: GameStop (GME) and AMC Entertainment (AMC). To assess sentiment's role, we employ two existing text-based sentiment analysis methods and introduce a third, a ChatGPT-annotated and fine-tuned RoBERTa-based model designed to better interpret the informal language and emojis prevalent in social media discussions. We use correlation and causality metrics to determine these models' predictive power. Surprisingly, our findings suggest that social media sentiment has only a weak correlation with stock prices. At the same time, simpler metrics, such as the volume of comments and Google search trends, exhibit stronger predictive signals. These results highlight the complexity of retail investor behavior and suggest that traditional sentiment analysis may not fully capture the nuances of market-moving online discussions.