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K. Obaid and K. Pukthuanthong: Distortion in Financial Narratives: A ChatGPT Approach

June 17, 2024

We examine how financial news is distorted as it spreads across different news outlets, akin to the “telephone game”. Using a sample of exclusive articles from the Wall Street Journal, we use ChatGPT-4 to quantify the distortion introduced in the information environment as competing news outlets retell these stories. We find strong evidence that retelling articles tend to be more opinionated and negative and less factual and appealing compared to the original story. Less specialized news outlets, the more time-lapse between the original story and its retelling, and the presence of competing narratives from other news outlets contribute to the distortion. Media distortion negatively predicts the following month’s abnormal returns, suggesting that distortion creates a more pessimistic public perception of the original story. Media distortion mostly influences retail traders, and leads to heightened disagreement among sophisticated and unsophisticated traders.

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