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Volatility Spillovers from The Vix to Global Equity Markets: Evidence from A Garch–Var Framework
Subject area: Management and Commerce · Area of research: Finance
DOI: 10.64388/IREV9I12-1718885
Abstract
The financial markets have become more interconnected in the global economy, and financial volatility shocks are spreading more quickly between countries. In this paper, we analyze volatility spillovers from the CBOE Volatility Index (VIX) to six major equity markets (S&P 500, FTSE 100, DAX 40, Nikkei 225, Nifty 50, and Hang Seng Index) during the daily period from January 2015 to December 2024. To estimate the conditional volatilities, the two-stage GARCH–VAR approach is used: First, the conditional volatilities are estimated using GARCH(1,1) models and then analysed in a VAR framework with impulse response functions (IRFs), forecast-error variance decomposition (FEVD) and spillover methodology developed by Diebold and Yilmaz (2012) assisted by Granger causality tests. The empirical results verify the VIX's status as a structurally dominant net transmitter of volatility in the global economy, and the presence of directional and asymmetric spillovers to all markets sampled. Developed European markets, in particular the FTSE 100 and DAX 40, exhibit stronger and more persistent responses than emerging Asian markets. Regime-wise analysis shows that during the COVID-19 crisis period, total system connectedness significantly rises to 58.96%, and then decreases in the post-pandemic phase to 21.47%, highlighting timevariation and regime sensitivity of international volatility transmission. The findings are relevant for the portfolio rebalancing channel as the main propagation mechanism, and offer policy implications for portfolio diversification, risk management, and macroprudential policy design.
Keywords
VIX, Volatility Spillovers, GARCH–VAR Framework, Global Equity Markets, Financial Contagion, Risk Transmission, Diebold–Yilmaz Spillover Index, Regime Analysis
References
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How to cite this paper
@article{1718885,
author = {Sivani P S, Dr. P. A. Manoj Kumar},
title = {Volatility Spillovers from The Vix to Global Equity Markets: Evidence from A Garch–Var Framework},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {12},
pages = {1591-1602},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1718885.pdf},
abstract = {The financial markets have become more interconnected in the global economy, and financial volatility shocks are spreading more quickly between countries. In this paper, we analyze volatility spillovers from the CBOE Volatility Index (VIX) to six major equity markets (S&P 500, FTSE 100, DAX 40, Nikkei 225, Nifty 50, and Hang Seng Index) during the daily period from January 2015 to December 2024. To estimate the conditional volatilities, the two-stage GARCH–VAR approach is used: First, the conditional volatilities are estimated using GARCH(1,1) models and then analysed in a VAR framework with impulse response functions (IRFs), forecast-error variance decomposition (FEVD) and spillover methodology developed by Diebold and Yilmaz (2012) assisted by Granger causality tests. The empirical results verify the VIX's status as a structurally dominant net transmitter of volatility in the global economy, and the presence of directional and asymmetric spillovers to all markets sampled. Developed European markets, in particular the FTSE 100 and DAX 40, exhibit stronger and more persistent responses than emerging Asian markets. Regime-wise analysis shows that during the COVID-19 crisis period, total system connectedness significantly rises to 58.96%, and then decreases in the post-pandemic phase to 21.47%, highlighting timevariation and regime sensitivity of international volatility transmission. The findings are relevant for the portfolio rebalancing channel as the main propagation mechanism, and offer policy implications for portfolio diversification, risk management, and macroprudential policy design.},
keywords = {VIX, Volatility Spillovers, GARCH–VAR Framework, Global Equity Markets, Financial Contagion, Risk Transmission, Diebold–Yilmaz Spillover Index, Regime Analysis},
month = {June},
doi = {https://doi.org/10.64388/IREV9I12-1718885}
}