Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India

Abstract

The basic thrust of this article is to examine how shocks and volatility are transmitted across sector indices. This article employs the autoregressive asymmetric BEKK-GARCH model. The study is based on daily data from the National Stock Exchange (NSE) of India from January 2004 to January 2014. Volatility spillover was found to be bidirectional among the two pro-cyclical sectors: Finance and IT. But, there was a unidirectional shock and volatility spillover from the non-cyclical FMCG sector to both the pro-cyclical sectors. The FMCG sector has remained almost unaffected by the spillover from the other sectors. Moreover, the evidence of asymmetric spillover has been found to be present in most of the case. Second, correlations between the sectors were found to be higher during the period of global financial crisis. But no such evidence was found in the context of the Euro zone debt crisis. Understanding the dynamics of shocks and volatility transmission is necessary for risk management in general and for optimal portfolio allocation and hedging strategy in particular. To the best of our knowledge, this is the first study on Indian stock market which has analysed the dynamics of shock and volatility transmission across sector indices.

Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies

“…Kroner and Ng (1998) extend the BEKK model to incorporate asymmetric effects of shocks. Empirical applications of the asymmetric BEKK model include Grier et al (2004), Li and Majerowska (2008), Efimova and Serletis (2014), Wen et al (2014) and Majumder and Nag (2017), among others.…”

Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation

“…In addition, the few studies that consider emerging markets (Wang et al 2005;Iqbal et al 2012) tend to consider each pair of markets in isolation without recognising that volatility spillovers from several markets may affect the conditional variance of returns in one country. 4 Some studies on spillover effects use MGARCH models to examine the interaction between the return and volatility of several countries (Chou et al 1999;Scheicher 2001;Worthington and Higgs 2004;Conrad et al 2011;MacDonald et al 2018) and internal linkages among various sectors (Harris and Pisedtasalasai 2006;Hassan and Malik 2007;Majumder and Nag 2018;Alomari et al 2018) or among stock markets within an economy (Weber and Zhang 2012). For example, Chou et al (1999) uncover evidence of both return and volatility spillovers from the US market to the Taiwanese market during 1991-1994.…”

Analyzing the Spillover Effects from Parental Markets to Cross-listed IPOs on Mean returns and Price Volatility

“…Financial globalization generally means integration of stock exchanges, which further fuels synchronization of financial synergies (Kalemli-Ozcan, Papaioannou, & Peydro, 2013), transmission of risk and vulnerabilities (Majumder & Nag, 2018), co-movement of exchanges (Patel, 2016) and mean and volatility spillover (Natarajan et al, 2014) among exchanges across the globe. This paradigm shift creates a high level of mutual dependency among exchanges.…”

“…These finding are important findings for investors; they imply that whereas financial market synchronization moves in bilateral directions volatility and risks are transmitted only from developed markets to regional markets. Majumder and Nag (2018) investigated shock and volatility transmission in various sectors listed on National Stock Exchange (NSE) of India during the period of 2004 to 2014.They applied the autoregressive asymmetric BEKK-GARCH model. They found bidirectional mean and volatility spills over between Finance and IT and unidirectional from Fast-moving consumer goods (FMCG) to those sectors.…”