Sparse Modeling Under Grouped Heterogeneity with an Application to Asset Pricing

48 Pages Posted: 24 Jul 2023 Last revised: 6 Sep 2023

See all articles by Lin William Cong

Lin William Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management; National Bureau of Economic Research (NBER)

Guanhao Feng

City University of Hong Kong (CityU)

Jingyu He

City University of Hong Kong (CityU)

Junye Li

Fudan University - School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: July 22, 2023

Abstract

Sparse models, though long preferred and pursued by economists, appear ineffective/unstable relative to large models (Giannone et al., 2021). To achieve sparsity for interpretation while effectively exploiting big data for superior empirical performance, we introduce a general framework jointly clustering observations and selecting variables for modeling panel data. We derive analytical marginal likelihoods in our Bayesian Clustering Model (BCM), to incorporate economic guidance, address parameter/model uncertainties, and prevent overfitting. We apply BCM to estimating uncommon- factor-asset-pricing models for data-driven asset clusters and macroeconomic regimes. We find (i) cross-sectional heterogeneity linked to (interactions of) return volatility, size, and value, (ii) structural changes in factor relevance predicted by market volatility and valuation, and (iii) MK- TRF and SMB as common factors and multiple uncommon factors across characteristics-managed-market-timed clusters. BCM helps explain volatility- or size-related anomalies, validate within-group tests, and mitigates the “factor zoo” problem, while outperforming benchmark common-factor models in investments and pricing equities.

Keywords: Asset Pricing, Bayesian Estimation, Clustering Tree, Factors, Heterogeneity, Panel Data, Sparsity, Spike-and-Slab, Structural Breaks

JEL Classification: C11, C38, G11, G12.

Suggested Citation

Cong, Lin and Feng, Guanhao and He, Jingyu and Li, Junye, Sparse Modeling Under Grouped Heterogeneity with an Application to Asset Pricing (July 22, 2023). Available at SSRN: https://ssrn.com/abstract=4511953 or http://dx.doi.org/10.2139/ssrn.4511953

Lin Cong (Contact Author)

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.linwilliamcong.com/

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Guanhao Feng

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Hong Kong

Jingyu He

City University of Hong Kong (CityU) ( email )

83 Tat Chee Avenue
Hong Kong
Hong Kong

Junye Li

Fudan University - School of Management ( email )

No. 670, Guoshun Road
No.670 Guoshun Road
Shanghai, 200433
China

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