The value of foresight in the drybulk freight market

Abstract

We analyze the value of foresight in the drybulk freight market when repositioning a vessel through space and time. In order to do that, we apply an optimization model on a network with dynamic regional freight rate differences and stochastic travel times. We evaluate the value of the geographical switching option for three cases: the upper bound based on having perfect foresight, the baseline set by a random strategy, and the case of perfect foresight but only for a limited time horizon. By combining a neural network with optimization, we can assess the impact of varying foresight horizons on economic performance. In a simple but realistic two-region case, we evaluate empirically that the upper bound for large vessels can be as high as 25% cumulative outperformance, and that a significant portion of this theoretical value can be captured with limited foresight of a few weeks. Our research sheds light on the important issue of spatial efficiency in global ocean freight markets and provides a useful upper bound for the value of investing in predictive analysis.