Long memory and scaling behavior study of bulk freight rate volatility with structural breaks

Abstract

Due to the effect of credit crunch and slowdown in marine transportation, analysis of freight rate volatility characters under structural breaks is of great importance after year 2008. In this paper, the presence of structural break points in bulk freight rate index time series is investigated through the Iterated Cumulative Sum of Squares algorithm. Furthermore, long memory features of different vessel sizes, Supramax, Panamax and Capesize bulk carriers are also accomplished, and emperical results show that the daily returns of Baltic Supramax Index inclined to have stronger long-range correlation. Multifractal detrended fluctuation analysis (MF-DFA) method is applied with the influence of seasonality taken into consideration and the origin of multifractality is revealed. For policy-makers and investors with different trading horizons, structural break is an important indicator of different long memory characters of freight rate index time series in different time ranges. Hence, structural breaks in MF-DFA results are picked out and conclusions of long memory feature are achieved.