Autoencoder Asset Pricing Models

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Jan 2019 English Publisher:Elsevier BVJournal:SSRN Electronic Journal (eissn: 1556-5068,

Copyright policy )

Authors: Gu, Shihao; Kelly, Bryan; Xiu, Dacheng;

doi: 10.2139/ssrn.3335536 , 10.1016/j.jeconom.2020.07.009

Autoencoder Asset Pricing Models

- Summary
- Subjects
- Metrics

Abstract

zbMATH Open Web Interface contents unavailable due to conflicting licenses.

Related Organizations

University of Chicago
United States
National Bureau of Economic Research
United States
Yale University
United States

Keywords

autoencoder, Factor analysis and principal components; correspondence analysis, neural networks, nonlinear factor model, Statistical aspects of big data and data science, machine learning, stock returns, big data, Applications of statistics to economics, conditional asset pricing model

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	321
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 0.1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 0.1%