Researcher ORCID Identifier

0009-0005-3808-542X

Graduation Year

2026

Date of Submission

4-2026

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Economics

Reader 1

Peter Kelly

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2026 Shaan H Malik

Abstract

This thesis examines whether insider trading behavior at artificial intelligence (AI) firms provides evidence about potential mispricing in the AI sector. Because corporate insiders possess superior information about firm performance, their trading decisions may reveal whether AI stock prices reflect fundamentals or excessive optimism. Using a sample of 120 publicly traded U.S. firms from 2019 to 2024, including 62 AI firms and 60 non-AI firms, this study compares insider purchase and sale behavior across the two groups. Insider trading data from SEC Form 4 filings is combined with return data from CRSP and financial data from Compustat to test whether insider trades at AI firms differ in frequency, timing, and informational content. The results show that insiders at AI firms purchase stock less frequently than insiders at non-AI firms and tend to buy after stronger prior price appreciation. Surprise insider buying does not significantly predict future returns, suggesting limited informational content in AI insider purchases. In contrast, insider selling at AI firms is followed by significantly weaker future returns, indicating that these sales contain meaningful negative information. Additional analysis around the launch of ChatGPT shows that insider purchases declined during the AI boom rather than increasing. Overall, the evidence is more consistent with AI insiders selling into strong valuations than buying undervalued shares, supporting the view that AI stock prices may have been elevated relative to fundamentals during this period.

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