Internet Appendix for Deep Learning in Asset Pricing

51 Pages Posted: 11 Jun 2020 Last revised: 11 Sep 2020

See all articles by Luyang Chen

Luyang Chen

Stanford University - Institute for Computational and Mathematical Engineering

Markus Pelger

Stanford University - Department of Management Science & Engineering

Jason Zhu

Stanford University - Management Science & Engineering

Date Written: September 10, 2020

Abstract

The Internet Appendix collects multiple results that support the results in the main text. Among others it includes implementation details, the results for the benchmark approaches, additional robustness results and a detailed description of the data.

Keywords: Conditional asset pricing model, no-arbitrage, stock returns, non-linear factor model, cross-section of expected returns, machine learning, deep learning, big data, hidden states, GMM

JEL Classification: C14, C38, C55, G12

Suggested Citation

Chen, Luyang and Pelger, Markus and Zhu, Jason, Internet Appendix for Deep Learning in Asset Pricing (September 10, 2020). Available at SSRN: https://ssrn.com/abstract=3600206 or http://dx.doi.org/10.2139/ssrn.3600206

Luyang Chen

Stanford University - Institute for Computational and Mathematical Engineering ( email )

Huang Building, 475 Via Ortega
Suite 060 (Bottom level)
Stanford, CA 94305-4042
United States

Markus Pelger (Contact Author)

Stanford University - Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

Jason Zhu

Stanford University - Management Science & Engineering ( email )

314L Huang Engineering Center
475 Via Ortega
Stanford, CA 94305
United States

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