Hedging in an Asymmetrical Freight Market

This paper develops a bivariate asymmetric non-linear smooth-transition Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (BANST-GARCH) model to hedge the risk in the shipping freight rate market. Our dataset consists of 1,768 daily spot and forward freight agreement (FFA) prices of two tanker routesTD3 and TD5with the latter showing an asymmetric pattern. The empirical results of hedging effectiveness strongly support the concept that the BANST-GARCH model outperforms other models in both in- sample and out-of-sample periods with the largest variance reduction. Thus, our model is able to capture the asymmetric pattern in the tanker freight market. This study contributes to the literature by providing a new overview of the interaction between tanker spot and FFA markets, discovering the asymmetric effect of shocks in the shipping market, developing an advanced econometric model to capture the asymmetrical effect, and constructing a better hedge strategy on the basis of our BANST-GARCH model.