The Role of Price Spreads and Reoptimization in the Real Option Management of Commodity Storage Assets

The real option management of commodity storage assets is an important practical problem. Practitioners approach the resulting stochastic optimization model using heuristic policies that rely on sequential reoptimization of linear programs. Used in conjunction with Monte Carlo simulation, these policies typically yield near optimal lower bound estimates on the value of storage. This paper reveals that a simple one stage lookahead policy is optimal for a fast storage asset without frictions. Thus, in this (not entirely realistic) case the problem is easy and the reoptimization policies are unnecessary, albeit optimal. In contrast, this paper provides numerical and structural justification for the use of these policies in the general case. Further, the use of price spreads simplifies the estimation of near tight dual upper bounds on the value of storage. This approach relies on using the fast and frictionless asset optimal value function to estimate dual upper bounds in the general case. Monte Carlo simulation and linear programming thus appear adequate for the near optimal valuation and management of commodity storage assets.