Commodity procurement risk management with futures contracts: a dynamic stack-and-roll approach

Abstract

Procuring material from commodity spot markets can flexibly fulfil a forward production demand, but increase the risk of high procurement cost due to spot price volatility. In this paper, a dynamic stack-and-roll hedging approach using futures contracts is proposed. The approach aims at mitigating the procurement cost risk and optimising the terminal revenue received from the procurement and hedging activities. It separates the procurement planning horizon into multiple stages, along with varying hedging positions in the nearby futures contracts. Hedging positions are adjusted in response to commodity price behaviour and contemporary perceived information about forward production demand. Guided by the mean-variance criteria over the terminal revenue, dynamic programming is applied to derive a closed-form solution for optimal hedging positions in a discrete-time Markovian setting. Numerical experiments are carried out to assess the proposed approach with explicit solution in a realistic stochastic environment. The price processes are modelled by a fractal nonlinear regression model using real price data of China’s commodity market, while demand information process is modelled by Bayesian formula. The results show that the proposed approach outperforms naive hedging strategy, and effectively mitigates the procurement cost risk.