Volatility Spillover from the Fear Index to Developed and Emerging Markets

Abstract

This paper examines the volatility linkages among the fear index (VIX), the developed stock market volatility index (VXEFA), and the emerging stock market volatility index (VXEEM). We find significant cross-market dependencies in first as well as in second moments of volatilities. The fear index has leading role and has information content for both developed and emerging markets. A volatility shock to the fear index spillovers to the developed and emerging markets and able to explain about 57.07% and 63.77% of their unexpected volatility shocks, respectively; the effect of the shock persists for about 7 days. We further analyse the cross-market dependencies in second moments of volatilities and find that the correlations among the markets are time-varying not constant. Both developed and emerging markets are highly correlated with the fear index, and the fear index drives the correlation dynamics of the emerging markets. The dynamic correlations increase in turbulent periods and decreases in tranquil periods. Our findings have important implications for the international portfolio diversification, hedging and risk management.

Role of Economic Policy Uncertainty in the Connectedness of Cross-Country Stock Market Volatilities

“…Similarly, Tsai [19] investigated the spillover network of implied volatility among the US, the UK, Germany, Japan, and France, finding that information transmission between these stock markets increases considerably after 1998, with Germany and the US being the main stock markets conveying information to other international markets. Badshah [6] examines cross-market volatility linkages among implied volatility indices of the US, the developed-markets, and the emerging-markets, confirming the dominant role of the US index. Chen [20] analysed fear spillover network among implied volatility indices of Canada, Japan, Germany, and the US.…”

“…In this vein, the seminal work of Pastor and Veronesi [5] laid out theoretical foundations for the potential effects of economic policy uncertainty (hereafter EPU) on stock returns and volatility. Subsequently, a growing number of scholars began to investigate the transmission of fear across the country or regional stock markets [6,7]. However, the literature on the driving potential of EPU connectedness for fear connectedness remains scant.…”

Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective

“…We also choose to employ the ADCC-GARCH model developed by Cappiello et al ( 2006 ). The selection of such model is motivated by the findings of some researchers such as Zhou and Nicholson ( 2015 ) and Badshah ( 2018 ). These findings indicate that modeling covariance asymmetry between based on the ADCC model indicates that conditional volatility and correlations between returns increase more after negative return shocks than after positive shocks with the same scale.…”

Evidence of Fear in Fixed Income and Bourses: A Study on Certain G-7 Economies

“…In a study of lag between S&P 500, Credit Default Swap Index and VIX, VIX and CDX showed a positive relationship and VIX and S&P 500 showed a negative relationship (Winberg & Rugas, 2015). Badshah (2018) throws light on the idea of "volatility spillover from the fear index to developed and emerging markets" and shows how developed and emerging markets are highly correlated with the fear index, and hence, shows how the fear index acts as a driver of correlation dynamics in the emerging markets. During the period 1999-2009, it was observed that during stable market regimes, VIX overestimated the S&P index volatility and during high volatility period, it underestimated S&P 500 (Vodenska & Chambers, 2013).…”