Hedging ship price risk using freight derivatives in the drybulk market

We show that a fixed-maturity time-weighted Forward Freight Agreement (FFA) portfolio should be used to proxy the expected future earnings of a vessel. We investigate the corresponding hedging efficiency when using a portfolio of FFA prices to hedge ship price risk of both static hedge ratios calculated using Ordinary Least Squares estimation and the dynamic hedge ratios generated from a dynamic conditional correlation GARCH (1,1) model. We find that the hedging efficiency is greater for newer vessels than older vessels and that the static hedge ratio outperforms the dynamic hedge ratio. Our work is an extension of earlier empirical work which has only considered the hedging efficiency of varying-maturity calendar FFA contracts for a single vessel age.publishedVersio

Identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action

We study identification and estimation of finite-horizon dynamic discrete choice models with a terminal action. We first demonstrate a new set of conditions for the identification of agents’ time preferences. Then we prove conditions under which the per-period utilities are identified for all actions in the agent’s choice-set, without having to normalize the utility for one of the actions. Finally, we develop a computationally tractable semiparametric estimator. The estimator uses a two-step approach that does not use either backward induction or forward simulation. Our methodology can be implemented using standard statistical packages without the need to write specialized computational routines, as it involves linear (or nonlinear) projections only. Monte Carlo studies demonstrate the superior performance of our estimator compared with existing two-step estimation methods. Monte Carlo studies further demonstrate that the ability to identify the per-period utilities for all actions is crucial for counterfactual predictions. As an empirical illustration, we apply the estimator to the optimal default behavior of subprime mortgage borrowers, and the results show that the ability to identify the discount factor, rather than assuming an arbitrary number as typically done in the literature, is also crucial for obtaining correct counterfactual predictions. These findings highlight the empirical relevance of key identification results of the paper