ChatGPT's Stock Return Biases with Clifton Green | Markus Academy | Ep. 156

Click here for the full summary: https://markusacademy.substack.com/p/... Link to sign up for the webinar series: https://markusacademy.substack.com/ On Thursday, January 8, T. Clifton Green joined Markus’ Academy for a conversation on ChatGPT’s Stock Return Biases. Clifton Green is the John W. McIntyre Professor of Finance at Emory University. A Summary in four bullets: In the talk Green presented his recent paper (Chen et al., 2025), which shows that LLMs exhibit the same behavioral biases documented in humans (optimism, overconfidence, extrapolation, and framing effects), despite demonstrably “knowing” the behavioral finance concepts studied When asked to rank stocks by expected returns, models strongly extrapolate from past returns, with prompt engineering only modestly reducing the bias LLMs are overly optimistic about expected returns, while pessimistic about upside (90th percentile) returns LLMs are more optimistic in predicting returns when historical information is provided as return charts rather than price charts Timestamps: [02:42] Literature and overview [22:20] Extrapolation in stock returns and market sentiment [42:43] Optimism in the distribution of stock return forecasts [54:23] Framing effects [59:09] Implications for using LLMs in finance