Event Date Details:
Refreshments served at 3:15 p.m
- South Hall 5607F
Jeffrey Pai — UCSB
Title: Pricing Temperature Derivatives and Hedging Crop Yield
Abstract: The application of weather derivatives in hedging crop yield risk is gaining more interest. However, the further development of weather derivatives - particularly exchange-traded in the agricultural sector has been impeded by concerns over their hedging performance. In this paper, we develop a new framework to derive the optimal hedging strategy and evaluate hedging effectiveness. This framework incorporates a stochastic temperature model, a crop yield model, a risk-neutral pricing method, and a profit optimization procedure. Based on a large number of simulated scenarios, we study crop yield hedge for a future year. We allow the hedger to choose from different types of exchange-traded weather derivatives, and examine the impact of various factors on the optimal hedging strategy.
Our analysis shows that hedging objective, pricing method and geographical location of the hedged exposure all play important roles in choosing the best hedging strategy and assessing hedging effectiveness. This framework is forward-looking, because it focuses on the crop yield hedge for a future year rather than on the historical hedging effectiveness often studied in literature. It utilizes the most up-to-date information related to temperature and crop yield, and hence produces a hedging strategy which is more relevant to the year under consideration.
Keywords: Weather derivative, Crop yield, Filtered historical simulation, Hedging effectiveness, Geographical basis risk, Spatial aggregation effect