Do Instabilities in National Macroeconomic Factors Contribute to Channeling Volatility Spillover from the Global to the Islamic Equity Market?

This study investigates the impact of macroeconomic instabilities on returns volatility spillover that is transmitted from the global to the Islamic equity market. The economic factors examined are the exchange rate, inflation rate, interest rate, and production growth. To achieve the purpose of the study, we utilize three analysis tools: a GARCH(p,q) model to derive values of volatility for all variables; an asymmetry dynamic conditional correlation (ADCC) model to produce a measure of volatility spillover as the dependent variable; and a panel data regression technique to assess the causality significance of macroeconomic factors to volatility spillover. This study is the first which expands such approaches. We observe monthly data of world and Islamic market indices, exchange rates, consumer price indices, interest rates, and industrial production indices. The data, which range from May 2002 to February 2019, are taken from the world market, and twenty-three economies, which consist of fourteen developed and nine emerging markets that have Islamic stock indices. In several sections, we provide important additional analysis for five stock markets in Central European economies, which are compared to the others. The finding suggests that the presence of volatility spillover on the Islamic markets that originates from the global market is affected by the internal instabilities of macroeconomic factors, except for industrial production instability for developed markets, including Central European markets. An implication of the study is that regulators should anticipate and prevent adverse consequences of volatility spillover by arranging their internal economic policy to control inflation rates, interest rates, and industrial production growth, as well as exchange rate flexibility. Moreover, market practitioners should include both global market volatility and macroeconomic instabilities in their prediction to create minimum risk