Regularized GMM for Time-Varying Models with Applications to Asset Pricing

International Economic Review, Forthcoming

50 Pages Posted: 8 Apr 2021 Last revised: 25 Oct 2023

See all articles by Liyuan Cui

Liyuan Cui

City University of Hong Kong

Guanhao Feng

City University of Hong Kong (CityU)

Yongmiao Hong

Cornell University - Department of Economics

Date Written: September 12, 2023

Abstract

We propose a regularized GMM approach to estimating time-varying coefficient models via a ridge fusion penalty with a high-dimensional set of moment conditions. RegGMM only requires a mild condition on the oscillations between consecutive parameter values, accommodating abrupt structural breaks and smooth changes throughout the sample period. RegGMM offers an alternative solution for estimating the time-varying stochastic discount factor model when pricing U.S. equity cross-sectional returns. Our time-varying estimate paths for factor risk prices capture changing performance across multiple risk factors and depict potential regime-switching scenarios. Finally, RegGMM demonstrates superior asset pricing and investment performance gains compared to alternative methods.

Keywords: GMM, ridge fusion penalty, stochastic discount factor, time-varying coefficient model.

JEL Classification: C14, C58, G11, G12.

Suggested Citation

Cui, Liyuan and Feng, Guanhao and Hong, Yongmiao, Regularized GMM for Time-Varying Models with Applications to Asset Pricing (September 12, 2023). International Economic Review, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3814520 or http://dx.doi.org/10.2139/ssrn.3814520

Liyuan Cui (Contact Author)

City University of Hong Kong ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

Guanhao Feng

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Hong Kong

Yongmiao Hong

Cornell University - Department of Economics ( email )

Department of Statistical Science
414 Uris Hall
Ithaca, NY 14853-7601
United States
607-255-5130 (Phone)
607-255-2818 (Fax)

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