Flexible Time‐Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold

Balcilar M, Demirer R, Bekun FV. Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold. Mathematics. 2021; 9(8):915. https://doi.org/10.3390/math9080915

21 Pages Posted: 21 Apr 2021

See all articles by Mehmet Balcilar

Mehmet Balcilar

University of New Haven

Riza Demirer

Southern Illinois University Edwardsville - Department of Economics & Finance; Economic Research Forum (ERF)

Festus Bekun

Istanbul Gelisim University - Faculty of Economics Administrative and Social Sciences

Date Written: April 20, 2021

Abstract

This paper introduces a new methodology to estimate time‐varying alphas and betas in conditional factor models, which allows substantial flexibility in a time‐varying framework. To circumvent problems associated with the previous approaches, we introduce a Bayesian time‐varying parameter model where innovations of the state equation have a spike‐and‐slab mixture distribution. The mixture distribution specifies two states with a specific probability. In the first state, the innovation variance is set close to zero with a certain probability and parameters stay relatively constant. In the second state, the innovation variance is large and the change in parameters is normally distributed with mean zero and a given variance. The latent state is specified with a threshold that governs the state change. We allow a separate threshold for each parameter; thus, the parame‐ ters may shift in an unsynchronized manner such that the model moves from one state to another when the change in the parameter exceeds the threshold and vice versa. This approach offers great flexibility and nests a plethora of other time‐varying model specifications, allowing us to assess whether the betas of conditional factor models evolve gradually over time or display infrequent, but large, shifts. We apply the proposed methodology to industry portfolios within a five‐factor model setting and show that the threshold Capital Asset Pricing Model (CAPM) provides robust beta estimates coupled with smaller pricing errors compared to the alternative approaches. The results have significant implications for the implementation of smart beta strategies that rely heavily on the accuracy and stability of factor betas and yields.

Keywords: ime‐varying beta, risk premium, asset pricing, bayesian estimation, thresholds

JEL Classification: C11, C32, G11, G12, G14

Suggested Citation

Balcilar, Mehmet and Demirer, Riza and Bekun, Festus, Flexible Time‐Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold (April 20, 2021). Balcilar M, Demirer R, Bekun FV. Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold. Mathematics. 2021; 9(8):915. https://doi.org/10.3390/math9080915, Available at SSRN: https://ssrn.com/abstract=3830728

Mehmet Balcilar (Contact Author)

University of New Haven ( email )

300 Boston Post Road
West Haven, CT 06516
United States

HOME PAGE: http://www.mbalcilar.net

Riza Demirer

Southern Illinois University Edwardsville - Department of Economics & Finance ( email )

Department of Economics & Finance
Alumni Hall 3145
Edwardsville, IL 62026-1102
United States
(618) 650-2939 (Phone)
(618) 650-3047 (Fax)

HOME PAGE: http://www.siue.edu/~rdemire/

Economic Research Forum (ERF) ( email )

21 Al-Sad Al-Aaly St.
(P.O. Box: 12311)
Cairo, Cairo
Egypt

HOME PAGE: http://erf.org.eg/affiliates/riza-demirer-3/

Festus Bekun

Istanbul Gelisim University - Faculty of Economics Administrative and Social Sciences ( email )

Turkey

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
45
Abstract Views
338
PlumX Metrics