Abstract
This study aims to investigate the features of the dry bulk freight rates when there is a long memory effect. We employed GPH test, GSP test, the Rescaled Range Tests of Mandelbrot (1972) and Lo (1991), FIGARCH, HYGARCH and FIAPARCH models for the long memory test and estimation. Our results suggest that precise estimates of dry bulk freight rates may be acquired from a long memory in volatility models with skewed Student-t distribution. Such models might improve the long-term volatility forecast and more precise pricing of dry bulk freight contracts. We could extend these findings to the risk management in the dry bulk freight markets. Moreover, for appropriate risk evaluation of dry bulk freight rates, the degree of persistence should be examined and appropriate modelling that includes volatility clustering, asymmetry, leptokurtosis and long range dependence should be taken into consideration. We could extend this implication to the connection of the dry bulk freight market management.
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