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Alpha Grains

Farmers don't really get a lot of choice about which commodity markets they have exposure to. The geography and the climate of their farm's location will generally limit them to a few major choices, and then the logistics of selling products to some reasonably nearby delivery point will limit them further. I'm not an agronomist, but I assume it would be possible to grow sunflowers in, say, southern Ohio, but nobody wants to truck them 1,000 miles to a processing plant in Enderlin, North Dakota.

No, for a lot of farmers in the United States, the practical choices are restricted to corn, soybeans or wheat. That's a choice that gets a lot of press during these winter and spring months when seed-buying and acreage-planting decisions are being made, but it's nothing compared to the wealth of alternatives that stock investors get to choose from.

Consider that there are thousands of individual companies selling shares on public stock markets. (Dozens of thousands? Maybe hundreds of thousands, if we consider all the foreign stock markets?) Any investor can choose to buy a few or buy several of these and have exposure to a whole portfolio of markets.

The stock investing industry, therefore, has developed tools to compare the relative performances of individual assets. The commodity-producing industry might consider borrowing those tools to compare the prices of one crop to another.

Investors' most common way to assess one asset's returns is to calculate that asset's "alpha," a measure of its own idiosyncratic performance above and beyond an overall market benchmark. The entire stock market may rise or fall together, depending on widespread economic conditions, but if one company is doing something truly special, it can generate gains that outperform the others in its class. They all should outperform the risk-free interest rate (the theoretical returns of an asset with zero risk, with the current T bill rate generally standing in for that theoretical number).

The official formula for calculating alpha includes statistical terms to adjust for the asset's volatility. If an asset can bring in a lot of return above and beyond the rest of the market but can only do so by swinging wildly about, its alpha will reflect that.

But in its simplest terms, alpha is equal to the asset's returns minus the market's returns (adjusted for overall risk and idiosyncratic risk). If Company A's stock rose 10% during the month of February while the S&P 500 rose "only" 4% during that month, then Company A would have a positive alpha of 6 during that timeframe (more or less, depending on its volatility characteristics). We would assume some of its gains came from a systemically favorable environment for stocks, but most of its gains came from something that the one specific company was doing well.

Already, we can identify some shortcomings of using alpha to compare the relative merits of commodity investment opportunities, or commodity production opportunities. It's an inherently backward-looking metric, and just because an asset has done exceptionally well in the past, doesn't mean it will do well in the future.

Also, studying a commodity's price over a long length of time is more problematic than studying a stock's price over time. A long series of commodity futures prices can be strung together by always using the front-month futures contract's price, but for one thing, that ignores the practical costs of rolling that position forward.

For another thing, it's not a great way to analyze new-crop planting opportunities between corn, soybeans and wheat. The soybean-to-corn price ratio is presently a whopping 2.80-to-1 if we look at the nearby contracts, but a more normal 2.57-to-1 if we look at the actual new-crop futures prices. The reference prices used for crop insurance contracts will come out to $3.96 per bushel for 2017 corn, $10.19 for soybeans, and $5.65 for spring wheat, now that all the trading sessions from the month of February have been averaged together.

But let's look at the grain and oilseed markets' alpha, anyway, compared against the overall market for commodities, as represented by the S&P Goldman Sachs Commodity Index. The S&P GSCI is a very broad benchmark that includes a lot of easily-tradeable commodity futures assets, anything from zinc on the London Metals Exchange to lean hogs on the CME to NYMEX heating oil contracts to, of course, wheat, corn and soybean futures themselves. So how have those grains done compared to their peers?

It's a little difficult to pick an arbitrary timeframe to look at, but let's only consider how the markets have fared since the start of 2015 -- a timeframe of general economic recovery in global raw materials demand. The S&P GSCI has gained a paltry 1.5% during the past 26 months, which frankly doesn't even outperform T bills, on an annualized basis.

The grains have been even worse, although their recent lack of volatility at least hasn't harmed their alpha. Corn's alpha is a negative 8 compared to the S&P GSCI, and Minneapolis spring wheat's alpha is a dismal negative 11. Only soybeans have tried to keep up with the global commodity markets -- the market has lost 2.8% over the past 26 months, with an alpha that calculates out to negative 3.4.

None of that really matters, because again, most grain producers aren't in a position to choose which commodity market to enter based on this little mathematical formula. If I said that zinc futures had a positive alpha of 10 (they don't), farmers wouldn't suddenly choose to produce zinc this spring.

But the conventional wisdom has been to focus on the relatively bullish success of the soybean market, and to guess at how these new-crop futures prices above $10 may radically alter U.S. farmers' planting intentions. The alpha calculation does show us something important in that context -- it says that the current soybean prices may be nothing special after all. They haven't even kept up with the overall market for global commodities.

But their failure to keep up has been less abject than the failure of the cereal grains, so I guess that's some idiosyncratic alpha that the oilseeds market can take credit for, all on its own.

© Copyright 2017 DTN/The Progressive Farmer. All rights reserved.

Elaine Kub is the author of Mastering the Grain Markets: How Profits Are Really Made - 
a 360-degree look at all aspects of grain trading, which draws on her experiences as a futures broker, market analyst, grain merchandiser, and farmer. Before earning an engineering degree from the University of Nebraska - Lincoln and a Masters of Business Administration from the University of California San Diego, Kub grew up on a family farm in South Dakota, where she is still active in grain and livestock production. 


As well as sharing her ag market insights on television and various farm radio programs, Kub also focuses on quantitative analysis in a regular column for DTN The Progressive Farmer.

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