The Modified Grandmill Method

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The Concept of the Right Price for Grain Futures

Much akin to a super market shopper, grain traders need to know when the price of a is "cheap" compared to supply and use, or if the price is "dear" relative to supply and use, and should be sold. The key to this right price for grain prices is the relationship between the Total Supply of a particular grain and its Total Use (demand).

The Total Supply of a grain underlying a particular grain futures market is the Beginning Stocks, plus Production, and Imports. When Total Supply is large, grain prices tend to fall under the weight of this excess, as end users put off buying the grain they need until later in the season when the current year’s production is available as well.  When Total Supply is tight, grain prices tend to rally very strongly from planting to pollination as end users scramble to fulfill needs ahead of schedule when faced with probable higher prices.

Total Use is the amount of grain consumed or processed in any given marketing year. This includes domestic consumption (crushing), seed use, feed and residual use, exports, and other measures of disappearance. When Use is running at a strong pace, consumers tend to be aggressive in their purchases, while producers tend to withhold supply, causing early season rallies to be strong. However, when Use is slow, consumers tend to put off purchases, to avoid higher storage costs and increased chances of having their stocks spoil or become damaged. This tends to cause prices to break, especially during periods when the risk to supply is diminished (around pollination) or when supply is plentiful (harvest).

So even though in plenty of years, grain prices do tend to rally from planting to pollination and break from pollination to harvest, in many years they do not because of the current Supply and Use situation. But, if one can understand when prices are "cheap" or "expensive" relative to Supply and Use, then this "right price" can be used in conjunction with the seasonal nature of grain prices to make more accurate price forecasts.

Finding the "Right Price"

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The author Wm. Grandmill's greatest contribution to grain futures trading was his work with comparing Ending Stocks to Total Use. Grandmill hypothesized (we believe correctly) that the relationship between supply as a percentage of Total Use can correctly forecast the general trend of grain futures prices months into the future.

Ending Stocks are used because Ending Stocks represent the amount of grain left over from this crop year "carried over" into next crop year. Ending Stocks is simply the surplus left over at the end of the year.

Total Supply - Total Use = Ending Stocks

By using Ending Stocks as the measure of supply, one can see in a nutshell when Supply is growing relative to Use, and vice versa.  Because Ending Stocks can vary greatly from year to year, and the absolute size has increased dramatically in the past decade, this figure can not be used alone. Just using ending stocks is like saying that a person who weighs 200 pounds, is fat. If this person is 6' 6" tall, then a 200 pound person would be quite thin, while a 200 pound 5' tall person, may be quite portly. Just as doctors look at height relative to weight, the commodity trader must judge Ending Stocks relative to Total Use, to get an accurate forecast of the relationship between Supply and Use.

What Grandmill did was to compare all the Ending Stocks to Use ratios (Ending Stocks / Total Use) to the price of the particular commodity. What he found was that the higher the Ending Stocks to Use ratio was, the lower prices tended to be around harvest. Lower Ending Stocks to Use ratios generated higher prices, as supply was tight.

Modified Grandmill Method

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The same basic principles of the relationship between supply and demand are kept intact with our modifications, however we have broken down supply to use into 5 categories and we use relative changes in prices (% change) instead of absolute price levels.

We examined the last 19 years of Ending Stocks to Use ratios and separated them into five descriptive classifications for both domestic and world data sets:  Excessive, Plentiful, Normal, Tight, and Extremely Tight.  For each of these classifications, we have calculated a typical market behavior for the percentage change to the seasonal high and low, and the percentage change from a start date to the end of the month prior to delivery of the futures contract being analyzed.

Sample Table for July Corn Futures

Note: for July contract: % high refers to the average % change from the November 30^th settle to highest price between December and June 30^th.  % Low refers to the average % change from the November 30^th settle to the lowest price between December and June 30^th.  % Settle refers to the average % change from the November 30^th settle to the June 30^th Settle.  December and November Contracts: same as above except the June settlement is used instead of the November settlement, and the November (October for Soybeans) settle is used instead of June.  Past performance is not necessarily indicative of future results.

This methodology is intended to be used as a guide for identifying extreme pricing situations.  These forecasts are not intended to predict absolute highs or lows, but are intended to identify periods where historically prices are “cheap” or “dear” relative to the known supply and usage situation.  Pricing irregularities can and often do last for longer than usually can be expected, and prices can go to extremely irrational levels, well beyond what is predicted by this model.  None of this discounts this method, as its purpose is to identify extreme valuation.  It is our belief that this technique can assist participants in the grain futures markets to identify periods of irrational pricing, thus hopefully allowing grain traders to place the situation in its proper context and act accordingly.  Obviously, past performance does not guarantee future results.

Using the Grandmill method, one can put the relationship between supply and usage into perspective.  Each month, around the 12^th, the USDA/NASS issues the necessary information to make a “guesstimate” of price.

For example, on June 12^th, 2002, the USDA/NASS Supply and Demand Report reported the following for Soybeans:

                                    Total Supply                         3,114 million bushels

                                    Total Use                              2,849 million bushels

                                    Ending Stocks                         633 million bushels

On June 30^th, the last trading day in June, November ’02 Soybeans settled at 506 ¾ .  With a Stocks to Use Ratio (Ending Stocks/Total Use) of 9.3%, we check the tables for the November contract.  A 9.3% Stocks to Use ratio is classified as “VERY TIGHT” and yields the following: % Low of –6.0% and a % High of 26.0%, we can expect that November ’02 Soybeans will have a range of 476 to 633 between June 1^st, 2002, and October 31^st, 2002, and a October 31^st, 2002, settlement of 550 basis the November ’02 Soybean contract.  These figures were arrived at in the following fashion:

Low Price from 6/1 to 10/30   = November settle * (1+% Low)

                                                   = 506 3/4 * (1-.06) or 506.75*.94 = 476

High Price from 6/1 to 10/30   = November Settle * (1+% High)

                                                    = 506 3/4 * (1+.26) or 506.75 *1.26 = 633

October 31^st settlement price = November Settle * (1+% settle)

                                                    = 506 3/4 * (1+.085) or 506.75 * 1.085= 550

This will yield a “guesstimate” to use as a guide to pricing grain.  The tables and classifications are based on historical averages, and therefore will yield expected ranges.  Some years, trading is very rational and prices stay within these ranges.  However, in other years – like 2001 – the grain markets can be driven by other outside factors and market psychology which drives prices far beyond these extremes.  However, in some years, like 2002, the guides can be fairly accurate.  From June 1^st through October 31^st, the range was 467 ¼ and 591, and November ’02 Soybeans settled on October 31^st, 2002 at 565 ¼.    Though these guestimates did not hit the highs, lows, and settlement value exactly, hey were fairly close.  The same method used on Corn lead to an estimated range for December ’02 Corn of 215 to 278, while the actual contract traded between 219 and 296, and appears to be set to settle very near the estimated settlement guestimate of 232 ½.

Because these guestimates are not always exactly accurate, and nothing is, it is advised that market participants use this methodology as a guide, understanding that it will yield results based on historical averages.  In other words, just because a grain market is “under valued” or “over valued” does not mean it can not continue to go lower or higher.  What this method does is present a historical standard, and it is not meant as a guide for buying or selling, but as a means of representing value.

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DISCLOSURE OF RISK: THE RISK OF LOSS IN TRADING FUTURES AND OPTIONS CAN BE SUBSTANTIAL; THEREFORE, ONLY GENUINE RISK FUNDS SHOULD BE USED. FUTURES AND OPTIONS MAY NOT BE SUITABLE INVESTMENTS FOR ALL INDIVIDUALS, AND INDIVIDUALS SHOULD CAREFULLY CONSIDER THEIR FINANCIAL CONDITION IN DECIDING WHETHER TO TRADE. OPTION TRADERS SHOULD BE AWARE THAT THE EXERCISE OF A LONG OPTION WOULD RESULT IN A FUTURES POSITION.

HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH ARE DESCRIBED BELOW. 

NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL, OR IS LIKELY TO, ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM. 

ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM, IN SPITE OF TRADING LOSSES, ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS, IN GENERAL, OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.