Volatility Spillovers among Global Stock Markets: Measuring Total and Directional Effects
In this study we construct volatility spillover indexes for some of the major stock market indexes in the world. We use a DCC-GARCH framework for modelling the multivariate relationships of volatility among markets. Extending the framework of Diebold and Yilmaz  we compute spillover indexes directly from the series of returns considering the time-variant structure of their covariance matrices. Our spillover indexes use daily stock market data of Australia, Canada, China, Germany, Japan, the United Kingdom, and the United States, for the period January 2001 to August 2016. We obtain several relevant results. First, total spillovers exhibit substantial time-series variation, being higher in moments of market turbulence. Second, the net position of each country (transmitter or receiver) does not change during the sample period.
However, their intensities exhibit important time-variation. Finally, transmission originates in the most developed markets, as expected. Of special relevance, even though the Chinese stock market has grown importantly over time, it is still a net receiver of volatility spillovers.
This document has been translated into English for informational purposes. Upon any query regarding its interpretation or enforceability, the Spanish version shall be deemed official, and will prevail over the English version.
Este documento ha sido traducido al inglés para fines informativos. En caso de cualquier duda sobre su interpretación y aplicación, se entenderá que la versión en español es la versión oficial y prevalecerá sobre aquella escrita en inglés.
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