  This paper introduces StockGPT, an autoregressive ``number'' model trained
and tested on 70 million daily U.S. stock returns over nearly 100 years.
Treating each return series as a sequence of tokens, StockGPT automatically
learns the hidden patterns predictive of future returns via its attention
mechanism. On a held-out test sample from 2001 to 2023, a daily rebalanced
long-short portfolio formed from StockGPT predictions earns an annual return of
119% with a Sharpe ratio of 6.5. The StockGPT-based portfolio completely spans
momentum and long-/short-term reversals, eliminating the need for manually
crafted price-based strategies, and also encompasses most leading stock market
factors. This highlights the immense promise of generative AI in surpassing
human in making complex financial investment decisions.
