Volatility Analysis and Volatility Spillover across Equity Markets between India and Selected Global Indices

Abstract

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The purpose of this paper is to study the volatility comparison and volatility spillover effects in India and major global indices. The analysis used a vector autoregression model with various GARCH models in order to measure conditional volatility (GARCH), asymmetric effect in the conditional volatility (T-GARCH), volatility persistence in conditional volatility (E-GARCH), impact of conditional volatility on conditional returns (M-GARCH), and volatility spillover (GARCH (1, 1) with exogenous variable) for the period 2005 to 2018. The major results regarding volatility spillover posit that the Indian stock market had a strong impact on selected global indices. Volatility spillover was found to be in existence from the Indian stock market to the global indices, and vice-versa. These findings have substantial inferences and repercussions for portfolio managers, analysts, and investors for investment assessments and decisions regarding asset allocations. Higher volatility will lead to higher level of fretfulness among market participants and investors, which will push them to be more risk-averse. The results of the study also have pertinent effects for policy makers with respect to the Indian stock market and the global countries. This paper would support the existing literature by studying how the Indian index has an impact on global indices like the USA, Brazil, Japan, Russia, China, Hong Kong, South Korea, France, Germany, the United Kingdom, and Eurozone. The author considers that these results would magnify the volatility comparisons and volatility spillovers between the Indian index and global indices.

Keywords: Volatility Spillover, GARCH, Co-Integration, E-GARCH, Asymmetric Volatility

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