Artificial Intelligence Asset Pricing Models

Bryan T. Kelly, Boris Kuznetsov, Semyon Malamud and Teng Andrea Xu
Additional contact information
Bryan T. Kelly: Yale SOM; AQR Capital Management, LLC; National Bureau of Economic Research (NBER)
Boris Kuznetsov: Swiss Finance Institute
Semyon Malamud: Ecole Polytechnique Federale de Lausanne; Centre for Economic Policy Research (CEPR); Swiss Finance Institute
Teng Andrea Xu: École Polytechnique Fédérale de Lausanne (EPFL)

No 25-08, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

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.

Pages: 73 pages
Date: 2025-01
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp, nep-fmk and nep-ict
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