Optimal crop planting schedules and financial hedging strategies under ENSO-based climate forecasts

This paper investigates the impact of ENSO-based climate forecasts on optimal planting schedules and financial yield-hedging strategies in a framework focused on downside risk. In our context, insurance and futures contracts are available to hedge against yield and price risks, respectively. Furthermore, we adopt the Conditional-Value-at-Risk (CVaR) measure to assess downside risk, and Gaussian copula to simulate scenarios of correlated non-normal random yields and prices. The resulting optimization problem is a mixed 0–1 integer programming formulation that is solved efficiently through a two-step procedure, first through an equivalent linear form by disjunctive constraints, followed by decomposition into sub-problems identified by hedging strategies. With data for a representative cotton producer in the Southeastern United States, we conduct a study that considers a wide variety of optimal planting schedules and hedging strategies under alternative risk profiles for each of the three ENSO phases (Niña, Niño, and Neutral.) We find that the Neutral phase generates the highest expected profit with the lowest downside risk. In contrast, the Niña phase is associated with the lowest expected profit and the highest downside risk. Additionally, F. AitSahlia ( ) · C.-J. Wang · S. Uryasev Risk Management and Financial Engineering (RMFE) Lab., Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611-9565, USA e-mail: [email protected] url: http://www.ise.ufl.edu/farid C.-J. Wang e-mail: [email protected] S. Uryasev e-mail: [email protected] url: http://www.ise.ufl.edu/uryasev V.E. Cabrera Department of Dairy Science, University of Wisconsin-Madison, Madison, WI 53706-1284, USA e-mail: [email protected] C.W. Fraisse Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611-0570, USA e-mail: [email protected] url: http://www.agclimate.org/fraisse