In the January 24 Grainews issue, I explained the feeder cattle futures market and the simple mechanics of hedging feeder cattle. In this column, I want to take one step further and discuss the financial risk associated with backgrounding or selling feeder cattle.
First it is important to know risk is something that can be measured by analyzing historical data. For example, we can analyze previous financial returns over a set time. A factor that is unknown is simply an unknown factor. For example, I’ve had many questions from producers regarding the new U.S. president’s policies on the cattle trade. This is an unknown factor because we do not know the future.
I mentioned in the previous article cow-calf producers can use the futures market to forecast an expected price when selling their feeder cattle, however, there is also a variation around this expected price. Basis levels can change depending on the market dynamics of the changing supply and demand both at a macro level and also local region. The feeder cattle market has experienced unprecedented volatility over the past couple of years so producers need to know what type of financial risk they’re facing.
I’ve studied cattle markets for more than 20 years and conducted countless studies while I was in university. Recently, I once again poured over various sets of data and particularly analyzed the financial risk and rewards of a backgrounding operation in Manitoba. While the data may not be exact for Saskatchewan, Alberta and British Colombia producers, the risk reward is similar in each province given the nature of trade flows and pure competitive markets as in the case of feeder cattle.
I believe that everyone understands what the average represents. The standard deviation is the quantity calculated to indicate the extent of deviation for the group as a whole. One standard deviation is approximately 68.2 per cent of the data. To reiterate from my previous column, basis is the futures minus the cash price and converted (as necessary) to Canadian dollars. From Jan. 1, 2007 to Dec. 31, 2016 the basis was as follows using monthly data for Manitoba.
Using the Manitoba example for 850 lb. steers, at the time of writing this article, the August feeder cattle futures were at US$128 and exchange was US$0.75/Cdn. A producer can expect a price of US$128 divide by US$0.75/Cdn. equals $170.
Using an average basis, the producer can expect a price of $150. Using a standard deviation of 10, the variation around this average could be $140 to $160 approximately 68.2 per cent of the time. On the flip side, 31.8 per cent of the time the variation will be larger. From a financial perspective, a producer can say $140 will be the worst case scenario 68.2 per cent of the time.
Looking at monthly cash prices from 2007 through the end of 2016, I made the following analysis. If a backgrounding operation in Manitoba bought 550 pound steers and sold them at 850 pounds every month, what is the risk reward over the past 10 years? For simplicity, I used an average of $0.80 cost per pound gain. The average monthly return was approximately $24 per head with a standard deviation of $158. This standard deviation is quite large. Using this standard deviation, a producer can expect the financial returns per head to be negative $134/head or positive $182/head — the average plus or minus the standard deviation. Given this information, the producer knows the risk parameters without any hedging strategy.
Producers need to consider a few points. The standard deviation widened considerably in 2015 and 2016 because of the price volatility. More importantly, using various futures and options strategies will lower the average return but can considerably lower the standard deviation.
Lowering the standard deviation is the main objective of a hedging program. For example, buying put options on the feeder cattle futures at the lower end of the expected price range would limit the downside, but leave the upside open. However, I’ll pick this up in the next issue. In my experience, combining the hedging strategy with market analysis can usually enhance the financial return while lowering the risk. GN