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Generalized Autoregressive Conditional Betas: A New Multivariate Score-Driven Filter

Author

Listed:
  • Blazsek Szabolcs

    (138563 Stetson-Hatcher School of Business, Mercer University , 1511-1565 College Street, Macon, GA 31207, USA)

  • Jörding August

    (138563 Stetson-Hatcher School of Business, Mercer University , 1511-1565 College Street, Macon, GA 31207, USA)

  • Rai Simran

    (138563 Stetson-Hatcher School of Business, Mercer University , 1511-1565 College Street, Macon, GA 31207, USA)

Abstract

In this paper, we extend the recent Gaussian autoregressive conditional beta (Gaussian-ACB) model from the literature on score-driven models. In the new asset pricing model, named the t generalized ACB (t-GACB) model, a multivariate score-driven filter for the t-distribution drives dynamic interaction effects among the beta coefficients. We present the econometric formulation and statistical inference for the t-GACB model, which we apply to 15 stocks from the United States (US) from 1999 to 2022. In our empirical application, we use the three Fama–French factors as asset pricing factors, and we also use the Volatility Index, TED Spread, and ICE BofA US High Yield Index Option-Adjusted Spread as exogenous explanatory variables that influence the beta coefficients. We compare the statistical and realized tracking error performances of the Gaussian-ACB, t-ACB, and t-GACB models, and we find that the t-GACB model improves the Gaussian-ACB model.

Suggested Citation

  • Blazsek Szabolcs & Jörding August & Rai Simran, 2025. "Generalized Autoregressive Conditional Betas: A New Multivariate Score-Driven Filter," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(1), pages 95-128.
    • Handle: RePEc:bpj:sndecm:v:29:y:2025:i:1:p:95-128:n:1005
    DOI: 10.1515/snde-2023-0019
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    More about this item

    Keywords

    systematic risk; dynamic conditional score (DCS); generalized autoregressive score (GAS); autoregressive conditional beta (ACB); score-driven volatility; maximum likelihood (ML) estimation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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