Managing storable commodity risks: The role of inventory and financial hedge

Panos Kouvelis, Rong Li, Qing Ding

Research output: Contribution to journalArticlepeer-review

55 Scopus citations


We study how to manage commodity risks (price and consumption volume) via physical inventory and financial hedge in a multiperiod problem (with an interperiod utility function) for a risk-averse firm procuring a storable commodity from a spot market at a random price and a long-term supplier at a fixed price. The firm also has access to financial contracts written on the commodity price, such as futures contracts and call and put options. We examine different cases of financial hedging, for example, single-contract and multicontract hedges. For each case, we dynamically maximize the mean-variance utility of the firm's cash flow and characterize an optimal integrated policy of inventory and hedging, which is easy to compute and implement. We find that as long as futures are used in each period, alone or not, the optimal inventory policy is myopic. The optimal hedging policy, however, is never myopic, but depends on all the future optimal decisions. This is contrary to findings of the literature using intraperiod utility functions, which finds myopic hedging to be optimal. Moreover, we find that hedging may lead to inventory reduction in multiperiod problems. Thus the insights from the single-period studies in the literature-hedging leads to inventory increase-do not apply. Finally, insights are offered on the role and impact of inventory and financial hedge on profitability, variance control, and service level, using both analytical and numerical results.

Original languageEnglish (US)
Pages (from-to)507-521
Number of pages15
JournalManufacturing and Service Operations Management
Issue number3
StatePublished - Jun 1 2013
Externally publishedYes


  • Commodity markets
  • Futures
  • Hedging
  • Options
  • Risk aversion
  • Risk management
  • Stochastic inventory

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research


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