DCC-GARCH Using Histogram Valued Time Series in Asian Countries

Our research focuses on investigating the dynamic correlation between the ASEAN-5 stock markets (Thailand, Malaysia, Philippines, Singapore, and Indonesia) during the period from 01/01/2018 to 18/07/2023. The study aims to explore dynamic correlations in the aftermath of the COVID-19 pandemic and the Russia-Ukraine conflict. Our analysis reveals non-normality in the data and identifies the HVTS-DCC-SGARCH(1, 1) model with a normal distribution as the most suitable for assessing volatility and correlation. This model exhibits superior performance, making it an excellent alternative for evaluating volatility and correlation among the five Asian stocks. This study also uncovers significant and persistent high volatility in the markets over time, with varying degrees of impact from the pandemic and the geopolitical conflict. Interestingly, the war’s impact on volatility is relatively lower than that of the epidemic. Furthermore, the dynamic correlation between countries exhibits a notable increase during the early phase of the COVID-19 pandemic, indicating stronger interdependence among financial markets. However, as time progresses, the correlation decreases, suggesting a shift in financial market interdependencies. Surprisingly, there is no significant change in correlations since the start of the Russia-Ukraine conflict, indicating that other factors may have played a more significant role in influencing financial market dynamics during this period.