Template-Type: ReDIF-Article 1.0
Author-Name: Marc LoGrasso
Author-Email: lograssm@canisius.edu
Title: Could ChatGPT have earned abnormal returns? A retrospective test from the U.S. stock market
Abstract: This paper attempts to assess the ability of OpenAI’s ChatGPT to provide high-quality recommendations for a casual investor looking to beat the market. Going back to 1985 and instructing the GPT-4 model to restrict its knowledge to only what could have been known at the time of stock selection, the GPT-4 model was able to average alphas of approximately 1% per month for two-year holding periods beginning July 1 every year from 1985 to 2021. These abnormal returns persisted after controlling for size, book-to-market, profitability robustness, investment approach, and intermediate- and long-term prior returns. Individual portfolio alphas are only positive and significant about one out of four years but are never negative and significant. This paper also illustrates some of the precision needed to induce the GPT-4 model to provide any recommendations and briefly assesses the asset allocation strategy it appears to pursue.
Keywords: Portfolio choice, Artificial Intelligence, Market efficiency, ChatGPT, Fintech
Journal: Modern Finance
Pages: 112-132
Volume: 3
Issue: 3
Year: 2025
Subtitle : 
File-URL: https://mf-journal.com/article/view/327
File-Format: text/xml
Handle: RePEc:bdy:modfin:v:3:y:2025:i:3:p:112-132:id:327