Analyzing Structural Breaks and Volatility Spillover due to Infectious Disease in Japan: Using Spillover Networks

Abstract

In this paper, we investigate structural breaks and volatility spillover effects on the Japanese stock market. To detect structural breaks, we use an iterated cumulative sum of squares (ICSS) algorithm, which can identify multiple change points. To measure the volatility spillover effect, we apply the BEKK-GARCH model. As a result, many sectors have structural breaks that occurred after the novel coronavirus disease 2019 (COVID-19) shock after January 2020. Furthermore, we find that the transportation sector is heavily affected by volatility spillover during years of infectious disease outbreaks and a pure economic shock affects the financial sector.