Revisiting Financial Volatility in the Indian and Chinese Islamic Stock Markets: A GARCH–MIDAS Approach

This study investigates the influence of macroeconomic variables on the volatility of Islamic stock indices in India (Nifty 50 Shariah) and China (FTSE Shariah China) using the generalised autoregressive conditional heteroskedasticity–mixed data sampling (GARCH–MIDAS) model. We analyse monthly data from July 2010 to December 2023, focusing on the impact of inflation (consumer price index [CPI]) and short-term interest rates (91-day T-bill rate for India and the interbank rate for China) on the long-term volatility component. Utilising the GARCH–MIDAS model, this research seeks to identify how macroeconomic variables affect the instability of Islamic stock indices within India’s Nifty 50 Shariah and China’s FTSE Shariah China. We examine monthly data between July 2010 and December 2023, focusing on the effect of inflation (CPI) and short-term interest rates (91-day T-bill rate for India and interbank rate for China) on long-run volatility component. We have found out that there is a strong positive correlation between short-term interest rates and long-term volatility in both markets, which means that perhaps Muslim investors are using conventional interest rates to determine their Islamic investments. But the effect of CPI differs between them, as it has an insignificant effect in India and a marginally significant but negative impact in China. This difference shows how essential it is to look at national factors when studying the volatility of Islamic stock exchanges. It is noted here that in both locations there is evidence of the leverage effect, so that bad news greatly influences volatility compared to good news. Also, we did not find any regular pattern when comparing Islamic stock returns and traditional interest rates while conducting a benchmark study. The above findings have important implications for those who invest or manage funds or make policies in these new economies—showing them how they should adapt their investment and risk management plans to specific situations. JEL Codes: C58, E44, G15, G17