Stock Markets Linkages Before, During and After Subprimes Crisis: Bivariate BEKK GARCH (1, 1) and DCC Models

Abstract

The purpose of this paper is to apply the Bivariate BEKK-GARCH (1, 1) and DCC-GARCH models in evaluating volatility spillovers and dynamic conditional correlation between stock indices. In this paper, the causal relation between stock markets (Nasdaq and each of these indices:

The effects of volatility and changes in conditional correlations in the stock markets of Russia and developed countries

“…The correlations of the markets of Germany, the UK, and France have not decreased, the fluctuations are in a rather narrow range, and the connection between the German and French markets is at a very high level. This result is consistent with the estimates of other studies (Guesmi et al, 2014;Abdelkefi, 2015).…”

“…A large number of empirical applications of volatility modelling are found in both developed (Kutlar & Torun, 2014;Guesmi et al, 2014;Abdelkefi, 2015) and emerging stock markets (Kutlar & Torun, 2014;Guesmi et al, 2014;Salmanov, Babina, Bashirova, Samoshkina, & Bashirov, 2016;Salmanov, Lopatina, Drachena, Vikulina, & Zaernjuk, 2016;Seth & Singhania, 2019;Abdelkefi, 2015). For example, Kutlar and Torun (2014) use BEKK-GARCH and CCC-GARCH analysis, examine the volatility dynamics between the stock markets of developed and emerging market economies.…”

“…However, internal shocks and volatility in the previous period affect volatility in the current period. Abdelkefi (2015) considers the use of the BEKK-GARCH (1,1) and DCC-GARCH models in assessing the secondary effects of volatility and dynamic conditional correlation between stock indices. She investigates the causal relationship between the stock markets (the Nasdaq and the CAC 40, DAX 30, FTSE 100, Global Dow, Hang Seng, Nikkei 225, Russell 2000, Shanghai, S&P 500, and STOXX 600) using the Granger causality test.…”

“…Various interdependencies are revealed. Abdelkefi (2015) demonstrates the existence of unilateral and bilateral relations between the US stock market and other developed markets; Panda and Nanda (2018) establish that emerging markets are less related to developed market in terms of profitability; Kutlar and Torun (2014) show that while the markets of developed countries show a strong spread of volatility, in developed countries there is a weak spread of volatility to developing countries; Seth and Singhania (2019) show that selective border markets are intertwined with developed markets; Guesmi et al (2014) show that most European stock markets are closely related to the US market; Ahmed et al (2018) use correlation analysis to show a significant positive correlation between developed markets but a relatively insignificant correlation between developing and developed markets; Wang et al(2018) highlight the presence of a strong VOLATILITY AND CORRELATIONS BETWEEN STOCK MARKETS spread of volatility from the USA to five major stock markets; Serletis and Azad (2018) reveal statistically significant secondary effects of volatility from emerging economies on the United States; Hung (2019) demonstrates that the correlation between Central European markets is especially significant; and Mitra et al (2015) find that the transfer of volatility between stock markets is predictable because they follow a certain pattern, and therefore they were modelled using appropriate theoretical distributions. The above articles establish that the process of the spread of volatility affects the flow of financial assets between countries and has led to significant changes in terms of stock market returns, the volume of transactions, and market value.…”