During recent years, more U.S. hog producers and meat packers are involved in marketing contracts to enhance net revenue and to limit downside price risk. This research explores new ways to efficiently price a subset of these contracts, window contracts, and to evaluate the effectiveness of these contracts to help producers and packers enter contracts that more effectively satisfy their preferences.
A Monte Carlo simulation model in which thousands of paths for hog, corn and soybean meal prices are simulated is developed. These commodity prices are assumed following a random walk with drift. Futures prices are used to calibrate the means of the expected joint distribution of these three spot prices. To calibrate volatility of prices, the forecasting power of several frequently used volatility forecasting methods are examined; implied volatility is used to forecast volatility for near term and historical volatility is used for longer term horizons. Historical correlation is introduced to capture the co-movement of the three price series. Alternative basis forecasting approaches are also compared. The futures spread model performs best for short-term while a five-year historical average is best for long-term forecasting.
The window contracts are decomposed into a portfolio of long Asian-Basket put and short Asian-Basket call options. A projected breakeven price is used to determine the floor price, and then the Monte Carlo simulation method is applied to price both a moving and a fixed window contract. These methods provide unbiased pricing of fixed and moving window contracts of one-year duration. A moving window contract may be preferred by contract issuers who value volatility reduction and due to cumulative performance issues.
This same Monte Carlo method is also used to forecast net revenue for hog producers. Based on this forecasting model and the assumption of a mean-variance utility function, the prospective evaluation, which utilizes the Monte Carlo simulation methods described above, is compared with retrospective evaluation, which uses only past performance of the risk management strategy, for a net revenue and a utility maximizing producer. Prospective evaluation is marginally better than retrospective evaluation in terms of net revenue enhancement and risk reduction.
|School:||The Ohio State University|
|Department:||Agricultural Economics and Rural Sociology|
|School Location:||United States -- Ohio|
|Source:||DAI-A 79/09(E), Dissertation Abstracts International|
|Keywords:||Contracts, Hog, Net revenue, Price, Volatility, Window contracts|
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