Two Are Better Than One: Volatility Forecasting Using Multiplicative Component GARCH-MIDAS Models

Journal of Applied Econometrics, Forthcoming

68 Pages Posted: 21 Mar 2016 Last revised: 21 Aug 2019

See all articles by Christian Conrad

Christian Conrad

Heidelberg University - Alfred Weber Institute for Economics; ETH Zürich - KOF Swiss Economic Institute

Onno Kleen

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE)

Date Written: August 14, 2019

Abstract

We examine the properties and forecast performance of multiplicative volatility specifications that belong to the class of GARCH-MIDAS models suggested in Engle et al. (2013). In those models volatility is decomposed into a short-term GARCH component and a long-term component that is driven by an explanatory variable. We derive the kurtosis of returns, the autocorrelation function of squared returns, and the R^2 of a Mincer-Zarnowitz regression and evaluate these models in a Monte-Carlo simulation. For S&P 500 data, we compare the forecast performance of GARCH-MIDAS models with a wide range of competitor models such as HAR, Realized GARCH, HEAVY and Markov-Switching GARCH. Our results show that the GARCH-MIDAS based on housing starts as an explanatory variable significantly outperforms all competitor models at forecast horizons of two and three months ahead.

Keywords: Forecast Evaluation, GARCH-MIDAS, Mincer-Zarnowitz Regression, Volatility Persistence, Volatility Component Model, Long-Term Volatility, Model Confidence Set

JEL Classification: C53, C58, G12

Suggested Citation

Conrad, Christian and Kleen, Onno, Two Are Better Than One: Volatility Forecasting Using Multiplicative Component GARCH-MIDAS Models (August 14, 2019). Journal of Applied Econometrics, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2752354 or http://dx.doi.org/10.2139/ssrn.2752354

Christian Conrad (Contact Author)

Heidelberg University - Alfred Weber Institute for Economics ( email )

Grabengasse 14
Heidelberg, D-69117
Germany
+49 (06)221 543173 (Phone)

HOME PAGE: http://www.uni-heidelberg.de/conrad

ETH Zürich - KOF Swiss Economic Institute ( email )

Zurich
Switzerland

Onno Kleen

Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE) ( email )

P.O. Box 1738
3000 DR Rotterdam, NL 3062 PA
Netherlands

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