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Introducing shrinkage in heavy-tailed state space models to predict equity excess returns

Author

Listed:
  • Florian Huber

    (University of Salzburg)

  • Gregor Kastner

    (University of Klagenfurt)

  • Michael Pfarrhofer

    (University of Vienna & WU Vienna)

Abstract

We forecast excess returns of the S &P 500 index using a flexible Bayesian econometric state space model with non-Gaussian features at several levels. More precisely, we control for overparameterization via global–local shrinkage priors on the state innovation variances as well as the time-invariant part of the state space model. The shrinkage priors are complemented by heavy tailed state innovations that cater for potential large breaks in the latent states, even if the degree of shrinkage introduced is high. Moreover, we allow for leptokurtic stochastic volatility in the observation equation. The empirical findings indicate that several variants of the proposed approach outperform typical competitors frequently used in the literature, both in terms of point and density forecasts.

Suggested Citation

  • Florian Huber & Gregor Kastner & Michael Pfarrhofer, 2025. "Introducing shrinkage in heavy-tailed state space models to predict equity excess returns," Empirical Economics, Springer, vol. 68(2), pages 535-553, February.
  • Handle: RePEc:spr:empeco:v:68:y:2025:i:2:d:10.1007_s00181-023-02437-3
    DOI: 10.1007/s00181-023-02437-3
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    More about this item

    Keywords

    S $$&~$$ & P 500; Fundamental factors; Dynamic regression; Stochastic volatility; Non-Gaussian models;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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