A conditional value-at-risk based methodology to intermediate-term planning of crude oil tanker fleet

Abstract

Abstract Crude oil suppliers usually meet intercontinental demand through a fleet of ocean tankers, which not only have very high fixed and operating costs but also carry considerable financial risks because of the volatilities in oil demand and spot freight rate markets. Hence, most oil suppliers maintain an under-capacity fleet, and manage additional requirements through periodically adjusting a mix of various charter contracts and/or their purchase options. For this periodic fleet adjustment problem, we propose a conditional value-at-risk based methodology to hedge against extreme losses. More specifically we develop a mixed integer nonlinear programming model, where parameters are estimated via Monte-Carlo simulation, to minimize both the chartering costs and the associated financial risks. The proposed methodology was applied to a number of problem instances, generated using the marine transportation network of a major oil supplier, and it was observed that: full use of a mix of charter contracts and its purchase options significantly reduce spot charter market related risks, while substantially increase the firm or oil demand-specific risks—a key relationship driving optimal fleet decisions; and, firm-specific (tanker under-utilization) risks become increasingly irrelevant during higher oil demand periods, and that the market risks show sensitivity to the starting spot charter prices as well as the scale of delivery operations.