Long memory and asymmetric time varying spillover effects in dry bulk freight markets

Abstract

This study employs two versions of bivariate asymmetric mixed normal GARCH models to capture the skewness and kurtosis detected in both the conditional and unconditional return distributions of dry bulk freight rates. The empirical results, incorporating the long memory effect on the returns, not only provide better descriptions of the dynamic behaviors of the freight market prices, but also play a significant role in improving the understandings of return dynamics. In addition, mixed normal models for time-varying volatility provide a better fit to the conditional densities than the usual GARCH specification and have the important advantage that the conditional higher moments are time-varying. This implies that the volatility skews implied by mixed normal models are more likely to exhibit the features of risk and that the direction of the information flow is regime-dependent. The findings of this study contain useful information for such diverse purposes as vessel allocation, portfolio management and risk management.