Recently, my colleague Kate Fuller and I developed a new online tool that’s intended to assist wheat producers in accessing price and basis information that can help make more informed marketing decisions. To better introduce our readers to this tool, Kate and I have put together a two-part series of posts that will (1) introduce the economic concepts and insights that historical price and basis information can provide (this post) and (2) will offer some instructions and hints for using the online tool (stay tuned).
What information does www.montana.edu/basis provide?
What is basis and why is historical basis a useful indicator of market?
Basis is defined as the difference between a cash price offered for a commodity at a specific location and a futures contract price for that commodity:
Basis = (Local Spot Price – Futures Price)
This difference occurs because futures markets, which capture global conditions and expectations, do not fully reflect the conditions in any particular local market. These discrepancies may be due to local variability in a commodity’s quality level, local demand and supply, and transportation modes, among numerous other factors. If none of these factors affected prices in a local market, then the basis would be zero, because the local price would be the same as the futures price.
Because basis is a combination of local and futures market information, it is a much more stable indicator of relative market conditions than the local spot or futures contract price alone. For example, while spot or futures prices may change drastically between years (or even days), basis is subject to much smaller movements. As such, basis can be a better indicator of how favorable or unfavorable current markets are relative to historical average.
What can I learn from examining basis levels and historical trends of basis?
I’ve seen other online tools that provide historical wheat basis in other states. Why can’t I simply use that information for Montana?
What is “nearby basis” and “harvest period basis,” and why do they provide different market information?
Basis can be calculated using prices of futures contracts that expire at different time periods. The most commonly reported basis value is the “nearby basis,” which is calculated as
Nearby Basis = (Local Spot Price – Nearby Futures Price)
The nearby futures price refers to the price of the futures contract that is closest to its expiration month. For example, in the Kansas City (KCBT) hard red winter wheat futures market, there is no futures contract that expires in January. The closest (or nearby) contract is the March futures, which expires in March. Therefore, the nearby basis may be a more informational tool for understanding current marketing conditions.
The “harvest-period basis” is calculated as
Harvest Basis = (Local Spot Price – Harvest Month Futures Price)
The harvest month futures price refers to the price of the futures contract for which the expiration date is closest to the month during which a crop is harvested. For hard red winter wheat, this is the July Kansas City (KCBT) HRW futures contract. For hard red spring wheat, this is the September Minneapolis (MGEX) HRS futures contract. Therefore, the harvest period basis may be a more useful informational tool for understanding what market conditions are currently being anticipated at the time that producers are harvesting and delivering a large proportion of their crop.
Why should I use different basis for wheat that has different levels of protein content?
What can I learn by examining basis volatility?
Volatility describes the stability of a measure over time. Larger basis volatility (i.e., large increases and decreases of basis within a period of time) can indicate uncertainty in the market about the pricing of a particular product. Lower basis volatility (i.e., small increases and decreases of basis within a period of time) can indicate a relatively stable market in which both the buyers and sellers of grain agree on the valuation of a specific product.
The www.montana.edu/basis tool calculates volatility as the coefficient of variation (CV), which is the ratio of the standard deviation of basis within a certain time period and the average of basis during that same time period. Calculating volatility using the CV allows for standardized comparisons of basis volatility across different years and within different times of a marketing year.
The online tool provides basis volatility measures based on one week, one month, six months, one year, and three years of basis data. This provides an opportunity to assess relative basis volatility within a short-run, medium-run, and long-run horizons.
How can I use historical basis information to help inform me about what local cash prices might be in the future?
There has been an extensive literature in agricultural economics related to developing commodity price forecasting models. The consensus is that a model that can first predict basis (and then use this prediction to forecast prices) leads to much better price predictions.
Consider the following: If someone asked you to predict the price of wheat in your local market three months from today, what would be your response? One reasonable strategy might be to determine the local price last year or take an average of several previous years. However, you would be using only information about what already occurred, without incorporating expectations of what will occur in three months. A second approach could be to look at the price of a futures contract expiring three months from today and assume that to be the most likely price. However, although the futures price accounts for local, regional, national, and international expectations about future wheat prices, directly using futures prices to characterize local market conditions and prices will almost always lead to errors. Both approaches, therefore, are likely to contain inaccuracies.
The solution: using the combination of basis (historical information) and futures prices (rational expectations). Historically, basis tends to be more stable than either the local or futures prices alone. This is because the volatility in prices caused by market fundamentals tends to affect both local and futures prices in the same direction. That is, when futures prices rise, local prices generally also increase. Similarly, decreases in local prices are associated with lower futures prices. Therefore, the difference between the local and futures prices, basis, is not likely to change by the same magnitude as prices themselves. The stability of basis over time makes it useful for predicting local cash prices for a given commodity and point in time.
While the www.montana.edu/basis tool does not directly predict basis or price levels, you can use historical basis information to understand historical market conditions for specific products at certain locations and time periods. You can then combine that information with futures contract prices to obtain additional insights about potential future market conditions.