Tanker Freight Market

The aim of this study is to determine the causality between oil production and freight rates in the seaborne oil transportation in the world. The causality with oil prices has been studied more in the literature, but the studies that examine the causality with oil production have been limited. However, the effect of the crude oil production amount on the market is also great. The methods that can detect delayed causality have been utilized unlike the existing literature. While the Baltic Dirty Tanker Index (BDTI) and Baltic Clean Tanker Index (BCTI) variables are used as the measurement for the tanker freight rates, the Bloomberg oil production index variable is used as the production measurement. The data set used in the study consists of 239 monthly observations covering between August 1998 and June 2018. Standard causality analysis developed by Granger (1969) is used for linear causality, and nonparametric tests developed by Hiemstra and Jones (1996) and Diks and Panchenko (2006) are used for nonlinear causality analysis. While linear causality cannot be spotted in the obtained results, nonlinear causality is determined. As a result of the four lagged nonlinear causality analyzes made, the causality is found from the second to the fourth lag for BDTI and from the first to the fourth lag for BCTI. According to these results, while the effect of changes in production is directly reflected in the product tanker market, it is reflected on the dirty tanker market with a delay. It is hoped that these results may be beneficial to developing business strategies and reducing risks for shipowners and charterers in the tanker market.

In this study, the average speeds of container, dry bulk and crude oil
fleets, which are the main market types in maritime transportation, are estimated and analyzed by using external factors such as freight rate, bunker price, fleet size and interest rate. Freight and interest rates affect the average speeds positively, while bunker price and fleet size negatively affect in accordance with the theoretical justifications. The freight rate mostly affects the average speed of the container fleet, while bunker price, fleet size and interest rate mostly affect the average speed of the crude oil fleet; the average speed of the dry bulk fleet is least affected by the fuel price and fleet size; and the average speed of the container fleet is least affected by the interest rate. In general, when the coefficient sizes between the factors are considered, the most effective factor in average speeds of the three market is their fleet size. Thus, new dimensions have been added to the empirical literature stuck in the framework of freight rate and bunker price.