A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics

48 Pages Posted: 25 Sep 2014

See all articles by Davide Pettenuzzo

Davide Pettenuzzo

Brandeis University - International Business School

Allan Timmermann

UCSD ; Centre for Economic Policy Research (CEPR)

Rossen I. Valkanov

University of California, San Diego (UCSD) - Rady School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: September 2014

Abstract

We propose a new approach to predictive density modeling that allows for MIDAS effects in both the first and second moments of the outcome and develop Gibbs sampling methods for Bayesian estimation in the presence of stochastic volatility dynamics. When applied to quarterly U.S. GDP growth data, we find strong evidence that models that feature MIDAS terms in the conditional volatility generate more accurate forecasts than conventional benchmarks. Finally, we find that forecast combination methods such as the optimal predictive pool of Geweke and Amisano (2011) produce consistent gains in out-of-sample predictive performance.

Keywords: Bayesian estimation, GDP growth, MIDAS regressions, out-of-sample forecasts, stochastic volatility

JEL Classification: C11, C32, C53, E37

Suggested Citation

Pettenuzzo, Davide and Timmermann, Allan and Valkanov, Rossen, A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics (September 2014). CEPR Discussion Paper No. DP10160. Available at SSRN: https://ssrn.com/abstract=2501643

Davide Pettenuzzo (Contact Author)

Brandeis University - International Business School ( email )

Mailstop 32
Waltham, MA 02454-9110
United States

Allan Timmermann

UCSD ( email )

9500 Gilman Drive
La Jolla, CA 92093-0553
United States
858-534-0894 (Phone)

HOME PAGE: http://rady.ucsd.edu/people/faculty/timmermann/

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Rossen Valkanov

University of California, San Diego (UCSD) - Rady School of Management ( email )

9500 Gilman Drive
Rady School of Management
La Jolla, CA 92093
United States
858-534-0898 (Phone)

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