This study using the ARFIMA-FIGARCH models found no significant long-memory process among Green ETFs. However, there is a presence of long memory attributes in the volatilities for Non-Green ETFs. For most of the results, this research failed to reject the efficient market hypothesis, and...

This paper applies the Autoregressive Moving Average-Exponential General Autoregressive Conditional Heteroskedasticity (ARMA-EGARCH) in studying the spillover and leverage effects of returns and volatilities of China's Shanghai Stock Exchange (SSE) index, India's Bombay Stock Exchange index...