Work

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

Year: 2023

Type: article

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.

Source: Empirical Economics

DOI: 10.1007/s00181-023-02437-3

Authors: Florian Huber, Gregor Kastner, Michael Pfarrhofer

Institutions: University of Salzburg, Vienna University of Economics and Business, University of Klagenfurt, University of Vienna

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,090

Funder: Austrian Science Fund