Multifractal features of spot rates in the Liquid Petroleum Gas shipping market

We investigate for the first time the spot rate dynamics of Very Large Gas Carriers (VLGCs) by means of multifractal detrended fluctuation analysis (MF-DFA) and rescaled range (R/S) analysis. Both non-parametric methods allow for a rigorous statistical analysis of the freight process by detecting correlation, scaling and fluctuation behavior regardless of nonlinearity issues. By applying different data-frequencies and a temporal framework, the Hurst exponents indicate that freight rates exhibit trend-reinforcement and persistence subject to limited time-dependency and controlled volatility. The found long-range dependence corroborates that a predictive freight model can be built undermining the efficient market hypothesis. Memory effects seem to each time build up until they are interrupted by seasonal transitions, stochastic events or cycles which all spark a sudden loss in correlations or increase in nonlinearities. The surrogate and shuffling data procedures demonstrate that, dependent on the data-frequency used, memory effects and fat-tail distributions should be contained differently in freight rate models.