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


Affiliations
1 Assistant Professor, B. K. School of Business Management, Gujarat University, Ahmedabad, Gujarat, India
2 Associate Professor, Shanti Business School, Ahmedabad, Gujarat, India
     

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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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  • Anoruo, E., Ramchander, S., & Thiewes, H. (2003). Return dynamics across the Asian equity markets. Managerial Finance, 29(4), 1-23.
  • Arshanapalli, B., Doukas, J., & Lang, L. H. P. (1995). Pre- and post-October 1987 stock market linkages between US and Asian markets. Pacific Basin Finance Journal, 3(1), 57-73.
  • Asgharian, H., Hess, W., & Liu, L. (2013). A spatial analysis of international stock market linkages. Journal of Banking & Finance, 37(1), 4738-4754.
  • Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158-171. doi:10.1111/j.14680297.2008.02208.x
  • Goudarzi, H., & Ramanarayanan, C. S. (2010). Modeling and estimation of volatility in the Indian stock market. International Journal of Business and Management, 5(2), 85-98.
  • Gupta, R. K., Jindal, N., Bamba, M., & Gupta, A. (2013). Asymmetric volatility and performance of Indian equity market: Comparison of SENSEX and NIFTY. International Journal of 360o Management Review, 1(2), 1-12.
  • Hamao, Y., Masulis, R. W., & Ng, V. (1990). Correlations in price changes and volatility across international stock markets. The Review of Financial Studies, 3(2), 281-307.
  • Jebran, K., Chen, S., Ullah, I., & Mirza, S. S. (2017). Does volatility spillover among stock markets varies from normal to turbulent periods? Evidence from emerging markets of Asia. The Journal of Finance and Data Science, 3(1/4), 20-30.
  • Karmakar, M. (2005). Modelling conditional volatility of the Indian stock markets. Vikalpa - The Journal of Decision Makers, (30), 21-37.
  • Kizys, R., & Pierdzioch, C. (2011). Changes in the international co-movement of stock returns and asymmetric macroeconomic shocks. Journal of International Financial Markets, Institutions, and Money, 19, 289-305.
  • Koutmos, G., & Booth, G. G. (1995). Asymmetric volatility transmission in international stock markets. Journal of International Money and Finance, 14(6), 747-762.
  • Kumar, R., & Dhankar, R. S. (2009). Asymmetric volatility and cross correlations in stock returns under risk and uncertainty. Vikalpa - The Journal of Decision Makers, (34), 25-36.
  • Kumar A., & Khanna S. (2018). GARCH – BEKK Approach to volatility behavior and spillover: Evidence from India, China, Hong Kong, and Japan. Indian Journal of Finance, 12(4), 7-19, doi:http://dx.doi.org/10.17010/ijf%2F2018%2Fv12i4%2F122791
  • Li, Y., & Giles, D. E. (2015). Modelling volatility spillover effects between developed stock markets and Asian emerging stock markets. International Journal of Finance and Economics, 20(2), 155-177.
  • MacDonald, R., Sogiakas, V., & Tsopanakis, A. (2018). Volatility co-movements and spillover effects within the Eurozone economies: A multivariate GARCH approach using the financial stress index. Journal of International Financial Markets, Institutions and Money, 52, 17-36.
  • Mohammadi, H., & Tan, Y. (2015). Return and volatility spillovers across equity markets in mainland China, Hong Kong and the United States. Econometrics, 3(2), 215-232.
  • Nath, M. K., & Mishra, R. K. (2010). Stock market integration and volatility spillover: India and its major Asian Counterparts. Research in International Business and Finance, 24(2), 235-251.
  • Ngo, T. H. (2019). Return and volatility spillover across equity markets between China and Southeast Asian countries. Journal of Economics, Finance and Administrative Science. doi:https://doi.org/10.1108/JEFAS-10-2018-0106
  • Nishimura, Y., & Men, M. (2010). The paradox of china’s international stock market co-movement: Evidence from volatility spillover effects between China and G5 stock markets. Journal of Chinese Economic and Foreign Trade Studies, 3(3), 235-253.
  • Singhal S., & Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models. Resources Policy, (50), 276-288. doi:https://doi.org/10.1016/j.resourpol.2016.10.001
  • Uyaebo, S. O., Atoi, V. N., & Usman, F. (2015). Nigeria stock market volatility in comparison with some countries: Application of asymmetric GARCH models. CBN Journal of Applied Statistics, 6(2), 133-160.
  • Wang, P., & Wang, P. (2010). Price and volatility spillover between the greater China markets and the developed markets of US and Japan. Global Finance Journal, 21, 304-317.
  • Xuan Vinh, V., & Ellis, C. (2018). International financial integration: Stock return linkage and volatility transmission between Vietnam and other advanced countries. Emerging Markets Review, 36, 19-27. doi.org/10.1016/j.ememar.2018.03.007
  • Yilmaz, K. (2010). Return and volatility spillovers among the East Asian equity markets. Journal of Asian Economics, 21(3), 304-313.

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

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Authors

Jay M. Desai
Assistant Professor, B. K. School of Business Management, Gujarat University, Ahmedabad, Gujarat, India
Nisarg A. Joshi
Associate Professor, Shanti Business School, Ahmedabad, Gujarat, India

Abstract


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

References