A Multiplicative Factor Multi Frequency Exponential GARCH Model

• Activity Number: 519 - Innovations in Time Series Modeling
• Type: Contributed
• Date/Time: Thursday, August 11, 2022 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Anjana Bandara Yatawara* and V. A. Samaranayake
• Companies: Missouri University of Science and Technology and Missouri University of Science and Technology
• Keywords: Long and short-term volatility; Volatility component models; Mixed frequency; Asymmetry

Abstract

The multiplicative factor multi-frequency component (MF)2 GARCH process proposed by Conrad and Engle in 2021, considers conditional variance as the product of a short-term volatility component modeled as a GJR-GARCH process and a long-term component expressed by a multiplicative error model (MEM) for the past forecast errors of the GARCH component. In this paper, we propose an exponential GARCH version of the (MF)2 formulation, which models the short-term volatility component as a less restrictive EGARCH process and the long-term component as a MEM. Further, the long-term model is formulated to account for a differential effect of the long-term accumulation of positive and negative shocks. Small sample properties of the parameter estimates are studied using a Monte-Carlo simulation and the utility of the proposed model is illustrated using a real-life data set.