The paper develops two Dynamic Conditional Correlation (DCC) models, namely the Wishart DCC (WDCC) model and the Matrix-Exponential Conditional Correlation (MECC) model. The paper applies the WDCC approach to the exponential GARCH (EGARCH) and GJR models to propose asymmetric DCC models. We use the standardized multivariate t-distribution to accommodate heavy-tailed errors. The paper presents a...

The paper develops two Dynamic Conditional Correlation (DCC) models, namely the Wishart DCC (WDCC) model and the Matrix-Exponential Conditional Correlation (MECC) model. The paper applies the WDCC approach to the exponential GARCH (EGARCH) and GJR models to propose asymmetric DCC models. We use the standardized multivariate t-distribution to accommodate heavy-tailed errors. The paper presents a...

This paper focuses on oil as a key determinant in US-GCC stock market interdependence. The analysis uses monthly data over the period from January 2003 to December 2019. interdependence between US and GCC is established using Asymmetric Dynamic Conditional Correlation model. We then investigate impact of both range macroeconomic variables nature correlation. Our results find that returns volati...

To assess the time-varying dynamics in value-at-risk (VaR) estimation, this study has employed an integrated approach of dynamic conditional correlation (DCC) and generalized autoregressive heteroscedasticity (GARCH) models on daily stock return emerging markets. A log-returns three leading indices such as KSE100, KSE30, KSE-ALL from Pakistan Stock Exchange SSE180, SSE50 SSE-Composite Shanghai ...

One of the features of a financial market, the stock market, in particular, is the market sentiment which is the overall attitude of investors toward a particular security or financial market. Investors always seek to create a portfolio with minimum risk while maintaining the expected return level. Therefore, perceiving the relationship between the stock returns and markets returns can be helpf...

This study focuses on the relation between fluctuation of international oil prices and China’s energy stock market during COVID-19 pandemic, using a dynamic conditional correlation generalized autoregressive heteroskedasticity model. We confirm spillover effect volatility price returns determine that leadership has been heavily influenced pandemic.