Artificial Intelligence Asset Pricing Models

Bryan T. Kelly, Boris Kuznetsov, Semyon Malamud and Teng Andrea Xu

No 33351, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: The core statistical technology in artificial intelligence is the large-scale transformer network. We propose a new asset pricing model that implants a transformer in the stochastic discount factor. This structure leverages conditional pricing information via cross-asset information sharing and nonlinearity. We also develop a linear transformer that serves as a simplified surrogate from which we derive an intuitive decomposition of the transformer’s asset pricing mechanisms. We find large reductions in pricing errors from our artificial intelligence pricing model (AIPM) relative to previous machine learning models and dissect the sources of these gains.

JEL-codes: C45 G10 G11 G14 G17 (search for similar items in EconPapers)
Date: 2025-01
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp, nep-fmk and nep-ict
Note: AP
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Citations: View citations in EconPapers (7)

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Working Paper: Artificial Intelligence Asset Pricing Models (2025)
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