4 citations · 4 across the 1 of their papers we have counts for
2 papers
q-fin.GN2024
The Promise and Peril of Generative AI: Evidence from GPT as Sell-Side Analysts
Edward Li, Min Shen, Zhiyuan Tu +1
Large language models (LLMs) promise to democratize financial analysis by reducing information-processing costs. Yet equal access does not ensure equal outcomes, as the locus of fr…
q-fin.GN2024★ 4 cited
What Does ChatGPT Make of Historical Stock Returns? Extrapolation and Miscalibration in LLM Stock Return Forecasts
Shuaiyu Chen, T. Clifton Green, Huseyin Gulen +1
We examine how large language models (LLMs) interpret historical stock returns and compare their forecasts with estimates from a crowd-sourced platform for ranking stocks. While st…