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...

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 utilizes parametric shared-frailty model to examine nine developed countries' expansion periods. Trade factors and monetary variables, at different time horizons, are seen to have significant effects on an economy's reoccurring recovery time. Consistent with previous literatures,...

This study employs the grey relational analysis model and provides robust identification of the S&P 500 stock index as having the greatest influence on exchange-traded funds (ETFs). The subsequent influencing factors are the volatility index (VIX), commodity research bureau (CRB) index, Brent...

Several characterizations of multivariate stable distribution are given based on identically distributed random vectors and conditional multivariate stable distribution.

We present extensive evidence that "risk premium" is strongly correlated with tail-risk skewness but very little with volatility. We introduce a new, intuitive definition of skewness and elicit a linear relation between the Sharpe ratio of various risk premium strategies (Equity, Fama-French, FX...