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 co...

Full description

Saved in:
Bibliographic Details
Published in:Energy economics 2011, Vol.33 (1), p.88-98
Main Authors: Engelen, Steve, Norouzzadeh, Payam, Dullaert, Wout, Rahmani, Bahareh
Format: Article
Language:English
Subjects:
Accumulation
Applied sciences
Correlation
Data analysis
Economic data
Economic models
Economics
Efficient markets
Energy
Energy economics
Exact sciences and technology
Fluctuation
Fossil fuels and derived products
Freight
Freight rates
Gas
General, economic and professional studies
Ground, air and sea transportation, marine construction
Hurst exponent
LPG
Marine and water way transportation and traffic
Markets
Mathematical models
Methodology. Modelling
MF-DFA
MF-DFA R
Natural gas
Nonlinear dynamics
Nonlinearity
Pricing
R/S
S LPG Freight rates Hurst exponent
Shipping
Shipping industry
Statistical analysis
Stochastic processes
Studies
Volatility
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0140-9883
1873-6181
DOI:10.1016/j.eneco.2010.05.009