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
Date Written: September 12, 2023
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.
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