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

The purpose of this paper is to study the volatility comparison and volatility spillover effects in India and major global indices. The study uses 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), the impact of conditional volatility on conditional returns (M-GARCH) and volatility spillover (GARCH (1, 1) with exogenous variable) for the period of 2005 to 2020. The estimates show 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 global indices and vice-versa. The T-GARCH estimates show the existence of a significant asymmetric effect in conditional volatility. The results of the E-GARCH estimates show the existence of volatility persistence in conditional volatility and the M-GARCH estimates indicated that there was no significant impact of conditional volatility on conditional returns of the sample indices. These findings have substantial insinuations and outcomes for portfolio managers, analysts, and investors for investment assessments and decisions regarding asset allocations. Higher volatility will lead to a higher level of fretfulness among market participants and investors, which will push them to be more risk-averse. The results of the study are also relevant for policymakers with respect to the Indian as well as global markets. This study will try to add a new dimension to the existing literature by studying how the Indian index has an impact on global indices like Brazil, USA, Russia, China, Japan, Hong Kong, and South Korea.