A two-state Markov-switching distinctive conditional variance application for tanker freight returns

Abstract

The few papers that explore different ways to measure shipping freight dynamics have differed in their interpretation of the most suitable measure for conditional freight volatility and consequently for the most appropriate freight risk measure. Furthermore, recent empirical work in maritime studies suggests the possibility of conditional freight volatility switching between different regime states that are dynamically distinct. This paper attributes these dissimilarities in findings within maritime literature to the possibility of freight returns switching between distinctive volatility structures. Therefore, it proposes a two-state Markov-switching distinctive conditional variance model by matching the two-state conditional freight variance to the most suitable GARCH specification. This provides for the first time a distinctive empirical insight into the dynamics of tanker freight rates by explaining the dissimilarities within the maritime literature in measuring freight risk that improves our understanding of the changes in volatility dynamics of the freight supply curve. Thus, this study postulates that the dynamics of freight rates are distinct and conditional on the freight volatility regime-state that prevails at the time. Empirical findings postulate that volatilities within tanker freight returns are better modelled by a framework that is capable of capturing volatility dynamics within the tanker freight market. This study attempts to explain the dissimilarities within the maritime literature in measuring freight risk by improving our understanding of the changes in volatility dynamics of the freight supply curve.