; Commodity Price Benchmarks | Conferences | AgRisk Library


Conference Name Commodity Price Benchmarks

Cory Walters, Kate Brooks, and Fabio Mattos


Price expectations for the upcoming year can be generated using Forward looking futures markets. However, futures markets initially only provide the price expectation for the contract of interest. Information about the probabilities where prices may end up when the contract will expire, which is very important to the risk manager, takes a few more calculations. We calculate price risk, or standard deviation, through commodity market option prices within the Black-Scholes-Merton model of futures market behavior. This approach incorporates what the commodity market views as price risk and is a reason why commodity markets exist, to provide the best information to help make predictions about where prices will end up at contract expiration. We will calculate these values for a variety of crops and livestock markets. A discussion how to calculate price risk will also take place.
The calculation of price risk probabilities will improve benefits of risk management decision making. Understanding more about the potential cost of not hedging provides a clearer picture of the risks producers face. Additionally, these probabilities can be linked to other risk management decision making, namely crop insurance. A crop insurance Revenue Protection (RP) policy insures prices using December futures for corn. Our framework will allow producers to calculate the probability of December futures prices dropping below crop insurance price guarantees at different coverage levels. Knowing more about perceived benefits (the probabilities) improves the risk management decision environment. We will do the same for cattle prices and Livestock Risk Protection (LRP). Results will be discussed.