Seasonal Price Patterns for Crops
EB-61,
December 2000
George Flaskerud, Extension Crops Economist and Professor
Department of Agribusiness and Applied Economics
Demcey Johnson,
Associate Professor
Department of Agribusiness and Applied Economics
Introduction
Motive for Seasonal Analysis
Analytical Techniques
Moving Average
Annual Average
Classification
Data and Computations
Behavior of Indexes
Hard Red Spring Wheat
Hard Amber Durum
Corn
Feed Barley
Malting Barley
Oats
Soybeans
Oil Sunflowers
Implications for Marketing Plans
Price Forecasting
Using the Moving Average Index
Using the Annual Average Index
References
Appendix A
Seasonal Price Patterns
For Crops
Agricultural commodities have historically exhibited
seasonal price movements that are tied to the annual nature
of the crop cycle. Crop prices in the cash and futures
markets are usually the lowest near harvest due to supply
pressure. Conversely, they are usually the highest near the end of
the marketing year when supplies are less abundant.
Seasonal price movements will vary, however,
depending on supply and demand fundamentals. In
particular, deviations of actual from expected supplies can have
a pronounced impact on seasonal price patterns.
During a "small" crop year, the new crop supply
falls significantly below what the market expected at the time
of planting. During a "large" crop year, the new crop
exceeds earlier market expectations. Different seasonal indexes
are relevant in these different situations.
The purpose of this publication is to present
seasonal price patterns for calendar years with different levels of
new crop supplies. New crop refers to the new marketing
year, which begins June 1 for wheat, barley and oats and
September 1 for corn, soybeans and sunflowers.
Motive for Seasonal Analysis
Seasonal price patterns can be used as a guide
for developing a marketing plan when they are examined
along with supply and demand information and other
marketing concepts. Plans can be made about selling a portion of
the crop in the cash market or the futures market.
Development of a marketing plan begins early. It is
one of the first considerations in developing a production
plan. Some beliefs about potential market prices are needed
to determine the profitability of alternative enterprises.
Marketing plans are generally constructed before a
producer has any notion about whether new crop supplies
will be "small" or "large." Within this framework of
uncertainty, price objectives must be established. Time deadlines
for selling must also be established in the event that the
price objectives are not reached.
Several steps may be followed to formulate price
objectives. Supply and demand fundamentals can be used
to determine an expected seasonal average price. With
the help of a seasonal price index representing average
price movements over all years, a distribution of prices during
the marketing year can be forecast. Price objectives can
then be determined, keeping storage costs in mind. In
effect, seasonal changes in price must be at least as great
as storage costs to justify storage. Additional information
about the storage decision can be found in NDSU
Extension Service publication EC-1011, Basis For Selected
North Dakota Crops.
The seasonal price pattern can also be used to
establish the time deadline for selling a portion of the crop.
Those times of the year when prices are usually the highest can
be used as a time deadline for selling a percentage of the
crop. Again, storage costs must be considered when
selecting the time deadlines for selling.
The marketing plan needs to be updated as the
growing season unfolds. Price objectives and time deadlines
for selling may need to be modified when more is known
about new crop supplies. A different seasonal price pattern
may be relevant for making a decision at this time, depending
on whether forecasts of new crop supplies are being
revised downward or upward.
The marketing tool used for selling a portion of
production will depend on the anticipated seasonal price
pattern. The pattern will depend considerably on the potential
size of new crop supplies.
If forecasts of new crop supplies are pushed lower
(due to bad weather conditions), prices are likely to peak
during the growing season. In this case, a hedge using a
cash forward contract, futures hedge or option may be justified
on a portion of anticipated production. Storage is not
usually economically feasible.
If forecasts of new crop supplies remain stable
through the growing season (or are revised upward), prices
are likely to reach bottom near harvest when supply
pressures are the greatest. In this case too, a hedge using a
cash forward contract, futures hedge or option may be justified
on a portion of anticipated production.
Storage may be economically justifiable in this
situation. However, additional information on futures prices, the
relationship between futures and cash prices (basis) and
storage costs are needed to analyze the storage
decision. Basis information and methods for analyzing storage
can be found in EC-1011.
Seasonal price patterns are usually described by
means of an index. Alternative analytical techniques are
available for calculating seasonal price indexes. The moving
average and the annual average are alternatives. In addition,
a technique is needed for classifying years, since
seasonal patterns are likely to vary depending on supply
conditions. To reflect seasonal patterns in a "small" or "large" crop
year, the price index should be based on years with
similar fundamentals.
The moving average is the most commonly used
technique for calculating a seasonal price index (Purcell).
It isolates the seasonal pattern by removing the influence
of cyclical price movements and long-term trends.
A moving average over 12 months is usually used
for calculating an index for crops. That is the length of
a marketing year, and the length of time required to
complete a seasonal pattern.
The index is derived by expressing the average price
for each month in a series as a percentage of the
moving average. An average of the monthly percentages
provides monthly numbers for the seasonal index.
An example in Table 1 illustrates the procedure
for calculating monthly percentages using the 12-month
moving average. The example uses to-arrive cash prices on
the Minneapolis Grain Exchange (MGE) for hard red
spring (HRS) wheat with 14 percent protein.
Table 1. Procedure for calculating monthly
prices as a percentage of the 12-month
moving average.
----------------------------------------------
12-Month 12-Month Price
Moving Moving Divided
Year Month Price Total Average by Avg.
----------------------------------------------
(cts) (cts) (cts) (pct)
1978 Jan 293
Feb 288
Mar 301
Apr 313
May 321
Jun 314
Jul 304 3777 314 96.6
Aug 318 3808 317 100.2
Sep 325 3847 320 101.4
Oct 338 3871 322 104.8
Nov 338
Dec 324
1979 Jan 324
Feb 327
Mar 325
----------------------------------------------
The 12-month moving total for July is the sum of
January-December prices, the 12-month moving total for August
is the sum of February-January prices, and so on. Dividing
the totals by 12 gives the averages. Dividing the prices by
the averages gives the monthly percentages.
Monthly numbers for the seasonal index are derived
by averaging the monthly percentages. The January
number is derived by averaging all the January percentages, and
so on. The result is a seasonal price index for wheat,
as presented in Table 2.
Table 2.Seasonal price and
variability indexes for
14 percent protein Hard Red
Spring Wheat on the Minneapolis
Grain Exchange, based on the
moving average, 1978-1999
to-arrive prices
-------------------------------
Variability
Month Price Index Index
-------------------------------
Jan 99.5 8.5
Feb 99.3 10.7
Mar 99.7 11.4
Apr 102.1 13.7
May 103.1 15.4
Jun 102.3 14.6
Jul 99.7 13.6
Aug 96.5 11.5
Sep 97.4 11.5
Oct 99.7 10.2
Nov 100.6 10.4
Dec 100.1 8.4
-------------------------------
The seasonal price index in Table 2 shows the
average seasonal price for 14 percent protein HRS wheat over
the period 1978-1999. The lowest seasonal price
occurred during August and the highest during May.
The May price index in Table 2 is 103.1. This means
that the price in May is expected to be 103.1 percent of
the seasonal average price. For a seasonal average price
of $3.00, the price in May is expected to be about $3.09.
The reliability of the price index is determined by
the index of variability, which is also presented in Table 2.
It indicates the range where the index could be expected
to fall with 95 percent probability.1 Lower limit defines the
low end of the range, and upper limit defines the high end.
The larger the variability index, the less reliable
the monthly price index. In Table 2, the month of
highest variability is May and the lowest is December.
The variability index in Table 2 is 15.4 for May. For
a $3.00 seasonal average price, the index indicates that
there is a 95 percent chance that the price will fall within the
range of 87.6 percent to 118.5 percent of the $3.00 price, which
is $2.63 to $3.55.
1The range presented is a prediction interval, which is different than a confidence interval around the mean. During a given year, the prediction interval is the range within which the price is expected to fall with specified probability. The confidence interval around the mean is smaller, but does not reflect the inherent variance of an individual observation.
A seasonal pattern for select years (corresponding
to "small" or "large" new crop supplies) can be
calculated using the annual average. Insufficient data would be
available for calculating the moving average; further,
cyclical moves and trend are of lesser concern for short, select
time periods.
This seasonal price index is derived by calculating
the annual average price, and then by expressing the price
for each month during the year as a percent of the
annual average. The monthly indexes over the years are
averaged to derive a price index that represents those years.
An example of the technique is presented in Table 3
for 14 percent protein HRS wheat to-arrive cash prices on
the MGE. The index is calculated for those years with
smaller-than-expected new crop supplies.
The seasonal price index presented in Table 3
suggests that the highest monthly price may occur during June.
It could be 104.2 percent of the calendar year average
price. May and December were the next closest high months.
Table 3.Seasonal price index for 14 percent protein
Hard Red Spring Wheat on the Minneapolis Grain
Exchange, based on the annual average for those
years with smaller than expected new crop supplies.
----------------------------------------------------
Prices
----------------------------------
Mth 1980 1988 1989 1991 1996 1997
----------------------------------------------------
--------------- (cts) -------------
Jan 402 316 439 274 537 434
Feb 403 320 430 279 551 423
Mar 396 308 446 296 554 446
Apr 394 327 442 303 626 454
May 426 335 451 305 686 438
Jun 428 422 435 300 642 423
Jul 464 417 433 286 572 410
Aug 427 424 414 304 516 437
Sep 451 423 406 321 450 422
Oct 472 430 412 352 440 410
Nov 485 421 405 366 436 411
Dec 479 422 412 393 437 405
Avg 436 380 427 315 537 426
----------------------------------------------------
----------------------------------------------------
Prices Divided by Average
----------------------------------------------------
Mth 1980 1988 1989 1991 1996 1997 Price Index
----------------------------------------------------
------------------ (pct) ----------------------
Jan 92 83 103 87 100 102 94.5
Feb 93 84 101 89 103 99 94.6
Mar 91 81 104 94 103 105 96.3
Apr 90 86 103 96 117 106 99.8
May 98 88 106 97 128 103 103.2
Jun 98 111 102 95 120 99 104.2
Jul 107 110 101 91 106 96 101.8
Aug 98 111 97 97 96 103 100.3
Sep 104 111 95 102 84 99 99.1
Oct 109 113 97 112 82 96 101.4
Nov 111 111 95 116 81 96 101.8
Dec 110 111 97 125 81 95 103.1
----------------------------------------------------
The perception of new crop supply as "small" or
"large" depends on the frame of reference. Prices
continuously adjust to new information about supply and demand
conditions, and it can be argued that the only relevant "news"
is that which conflicts with expectations. During the
growing season, what matters most to the market is how the
developing new crop compares to earlier supply expectations.
In this study, calendar years were classified according
to whether new crop supplies were smaller or larger
than expected at the time of planting. One standard deviation
of the differences between actual and expected supplies
was the guideline used in classifying the years.
Supply consists of carryover stocks plus production
plus imports. Expected production was based on actual
planted acres, the historical relationship between planted and
harvested acres, and the trend yield per harvested acre.
Actual carryover stocks were used as the expected. Large
carryover stocks would tend to reduce the effect of small yields
and accentuate the effect of large yields.
Data and Computations
The prices used to derive the seasonal price
patterns were obtained from several sources. To-arrive cash
prices at Minneapolis/Duluth were taken from USDA Grain
Market News. Cash prices for sunflowers were obtained
from National Sun Industries, Inc., Enderlin, North Dakota.
Cash prices for Minot were obtained from SunPrairie Grain
at Minot, North Dakota. Futures prices were obtained from
the Wall Street Journal and various internet sites.
Cash prices were obtained for Number 1 HRS wheat
with 14 percent protein, terminal quality hard amber
durum (HAD), number 2 corn, number 3 or better feed
barley, mellow malting barley, number 2 heavy oats, number
1 soybeans and sunflowers with 40 percent oil.
The moving average was used to calculate
seasonal indexes for cash prices over all the years considered in
this study. They were calculated over the 1986-1999 period
for sunflowers, over the 1989 - October 1999 for Minot, over
the 1978 - May 1996 period for MGE durum and over the
1978-1999 period for the other commodities and locations.
The annual average was used to calculate
seasonal indexes for cash prices during those years with smaller
and larger-than-expected supply deviations. This technique
was also used for select futures prices. The classification
of calendar years according to the size of new crop
supplies is presented in Table 4.
Table 4.Classification of calendar years by crop
according to the size of new crop supplies*.
-------------------------------------------------------------
New Crop Supplies
------------------------------------
Smaller than Larger than
Crop Expected Expected
-------------------------------------------------------------
Hard Red Spring Wheat 80,88,89,91,96,97 82,90,92,98
-------------------------------------------------------------
Hard Amber Durum 80,88 82,85,90,92
-------------------------------------------------------------
Corn 83,88,93 79,82,85,92,94
-------------------------------------------------------------
Barley 83,88,93 79,81,82,85,92,94
-------------------------------------------------------------
Oats 83,88,91,93 79,82,85,92,94
-------------------------------------------------------------
Soybeans 80,83,84,88,93 79,85,92,94
-------------------------------------------------------------
Sunflowers, Oil Type 88,89,93 86,87,98
-------------------------------------------------------------
*The years were classified according to deviations of actual
from expected new crop supplies with adjustments to reflect
situations in closely related markets. An italics or bold
appearance of a year identifies a supply situation in a closely
related market. A plain appearance of the year indicates the
supply situation existed for only the specified crop. For HRS
and HAD, an italics appearance indicates the supply situation
existed for both the specified crop and all wheat. A bold
appearance indicates the supply situation existed only for
all wheat. For malting barley, feed barley and oats, an italics
appearance indicates the supply situation existed for both the
specified crop and corn. A bold appearance indicates the supply
situation existed only for corn. For sunflowers, an italics
appearance indicates the supply situation existed for both
sunflowers and soybeans.
The behavior of the indexes is described in this
section by commodity. The baseline is MGE to-arrive cash
prices during 1978-99 unless otherwise specified. The
commodities include: hard red spring wheat, hard amber
durum, corn, feed barley, malting barley, oats, soybeans and
oil sunflowers. The indexes are presented in Appendix
A, Tables 1-4, and Figures 1-50.
Hard Red Spring Wheat
Prices bottomed during August and peaked during
May, on average (Figure 1 - 8KB graph). From harvest lows, the price
increased 4.1 percent by November and 6.6 percent by
May, on average. Prices were the least variable in December
and the most variable in May.
During the 1990s, the price pattern remained the
same but the prices were more variable (Figure 2 - 8KB
graph). Also, the
least amount of variability occurred in January instead of
December, although December was the second lowest.
When new crop supplies were smaller than
expected, prices peaked during June, on average (Figure 3
- 10KB graph). A
pronounced increase occurred in the growing season
during 1988 when both the all wheat and HRS wheat new
crop supplies were smaller than expected. The increase
was less pronounced in 1980 and decreased from the peak
in 1997, when only HRS wheat new crop supplies
were smaller than expected.
All wheat, but not HRS, new crop supplies were
smaller than expected in 1989, 1991 and 1996. Prices peaked
early in 1989. Prices strengthened during the last half of 1991
in anticipation of substantial exports to the former
Soviet Union. Prices fell sharply from the peak in 1996 as the
HRS crop turned-out better than expected.
When new crop supplies were larger than
expected, prices peaked by April and generally bottomed
during harvest (Figure 4 - 10KB graph). Prices continued falling into
November-December in 1990 when large new crop supplies existed
for HRS, all wheat and world wheat.
At Minot, similar price patterns were exhibited (Figures
5-7) for comparable years. In contrast, the behavior of
the futures contract (Figures 8-11) was markedly different.
Figure 5 - 8KB graph
Figure 6 - 10KB graph
Figure 7 - 9KB graph
Figure 8 - 7KB graph
Figure 9 - 7KB graph
Figure 10 - 10KB graph
Figure 11 - 9KB graph
For the September futures contract, a modest
seasonal pattern was revealed, on average, although the
pattern peaked during the same month of May. In addition,
price variability was about the opposite for the futures, being
low in March and high in August. Similar price patterns
prevailed for the smaller and larger crops.
The seasonal pattern for terminal quality HAD
prices (Figure 12 - 8KB graph) resembles the pattern for HRS, on average,
but with less variation among months. The greatest price
variability occurred in July.
When new crop supplies were smaller than
expected, prices peaked in July, on average (Figure 13
- 9KB graph). They
generally remained strong into November.
When new crop supplies were larger than expected,
the seasonal price pattern for HAD (Figure 14 - 10KB
graph) was similar
to HRS. Both reflected a small post harvest recovery in
prices, on average.
At Minot, the average price patterns for milling
and terminal (Figures 15 - 8KB graph and 16
- 8KB graph) were similar to one for
the MGE. The variability was greater at Minot but that could
be due in part to the difference in price periods.
The seasonal price patterns for corn were the
most pronounced of the commodities. Prices peaked in June
and bottomed in October, on average (Figure 17 - 7KB
graph). The
smallest price variability occurred in February, the greatest in
July. The price pattern and variability were similar during
the 1990s (Figure 18 - 7KB graph).
When new crop supplies were smaller than
expected, price peaks were established during July in 1988, August
in 1983 and December in 1993 (Figure 19 - 9KB graph). On
average, prices strengthened into July and remained strong until
the end of the year.
When new crop supplies were larger than
expected, prices peaked, on average, by June (Figure 20
- 9KB graph). Prices
fell by 21.9 percent, on average, between June and October.
For the December futures contract (Figure 21 - 7KB
graph),
the average price pattern varied little throughout the year.
Price variability was at a low in May and at a high in
November. The situation was similar during the 1990s (Figure
22 - 7KB graph).
For smaller-than-expected supply years (Figure 23 -
8KB graph), the
price, on average, increased into July and remained strong
during the balance of the year. For larger-than-expected
supply years (Figure 24 - 10KB graph), the price remained strong into
June before collapsing.
Prices bottomed in August and peaked in November
and May, on average (Figure 25 - 7KB graph). The pattern was similar
during the 1990s (Figure 26 - 8KB graph).
When new crop supplies were smaller than
expected, prices were also the highest in November, on
average (Figure 27 - 9KB graph). Prices bottomed in August and remained
low, on average, when new crop supplies were larger
than expected (Figure 28 - 10KB graph).
Prices in 1979 appear contraseasonal (Figure 28 -
10KB graph).
However, new crop supplies were larger than expected for
corn, not for feed barley.
The seasonal price pattern at Minot (Figure 29 -
7KB graph)
was similar to the MGE pattern for comparable years. The
Minot pattern did have a more pronounced August low.
The seasonal price patterns for malting barley
(Figures 30-34) were similar to those for feed barley, on average.
Figure 30 - 7KB graph
Figure 31 - 8KB graph
Figure 32 - 9KB graph
Figure 33 - 11KB graph
Figure 34 - 7KB graph
When new crop supplies were smaller than expected
for barley only, prices rose sharply between May and August
in 1988, according to Figure 32. They almost doubled.
In contrast, prices generally fell sharply between
May and August, according to Figure 33, when new crop
supplies were larger than expected. They fell 16.8 percent,
on average.
The highest price for oats occurred in December,
on average, over the 1978-1999 period (Figure 35 - 7KB
graph) and
during May (Figure 36 - 7KB graph) during the 1990s. The anticipation of a
very small crop led to a price peak in June during 1988 (Figure
37 - 9KB graph). Prices decreased into August when supplies
were larger than expected (Figure 38 - 9KB graph). The price pattern at
Minot was similar to the one at the MGE for comparable
periods (Figure 39 - 7KB graph).
Prices were the lowest in October and the highest in
May, on average, for soybeans (Figure 40 - 7KB graph). The price pattern
was similar during the 1990s (Figure 41 - 7KB graph).
During smaller-than-expected new crop supply
years (Figure 42 - 10KB graph), prices peaked in various months of the year.
On average, they peaked in August and remained high
through November.
During years with larger-than-expected new crop
supplies, prices fell by 18.2 percent, on average, between
June and October (Figure 43 - 9KB graph). On average, the price in
March was almost as high as in June.
As for the other futures prices, the price pattern
was modest for November soybean futures, on average (Figures
44 - 7KB graph). The situation was the same for the
1990s (Figure 45 - 7KB graph). Cash and futures prices had similar patterns
for smaller and larger-than-expected new crop supply
years (Figures 46-47).
Figure 46 - 10KB graph
Figure 47 - 10KB graph
Oil Sunflowers
Oil sunflower prices reached a peak in May, on
average, during 1986-1999 (Figure 48 - 7KB graph) and during July, on
average, when new crop supplies were smaller than expected (Figure
49 - 9KB graph). Prices weakened during most of 1989 when
the smaller-than-expected new crop supplies prevailed only
for sunflowers. During years with larger-than-expected
new crop supplies (Figure 50 - 9KB graph), prices also reached a peak
in May, on average, but then fell sharply into August,
on average.
Seasonal price indexes have implications for
marketing plans. In this section, examples illustrate how to
make practical use of seasonal price indexes.
Price Forecasting
Seasonal indexes can be used to calculate a
price forecast. The forecast can be based on a projected
seasonal average price or on the current monthly price.
Prices can be forecast for each month of the
marketing year by multiplying the projected seasonal average price
by the appropriate index for each month. Given a
projected seasonal average HRS wheat price of $3.10 and
normal supply and demand conditions, price projections would
be based on the indexes presented in Figure 1. Price
projections would be $2.99 in August, $3.02 in September,
$3.09 in October and so on. Combining this information
with storage costs permits the producer to make an
informed decision about the best time to plan sales.
Suppose that a forecast is desired based on the
current monthly price. The forecast price is the current
monthly price times the ratio of the forecast month's index to
current month's index. For example, suppose the HRS wheat
price in August is $3.00 and a forecast for November is
desired. The equation is:
Index in forecast month
This month's price X ----------------------- = Forecast price
Current month's index
100.6
$3.00 X ----- =$3.13
96.5
The November index was taken from Figure 1 to
derive the forecast price of $3.13, under the assumption
that normal supply and demand conditions will materialize.
If large wheat crops are being produced around the
world, then the larger-than-expected new crop supply price
index might be used.
The moving average index for HRS wheat in Figure
1 indicates that the price recovers rapidly from harvest
and reaches a fall high, on average, during November.
The producer could make plans early in the calendar year
to have two-thirds of actual production sold by that
time, keeping in mind that the seasonal change in price
between harvest and November must be at least as great as
storage costs to justify storage.
The moving average seasonal price pattern was
selected for this decision because growing conditions
were unknown. During the growing season the producer
may decide that a different seasonal price pattern is
more appropriate for the decision.
Suppose that as of mid-June it appears that dry
growing conditions will reduce U.S. wheat production,
carryover supplies are relatively low, and current prices are
relatively high. The producer needs to update the marketing plan.
The price indexes for HRS wheat in Figure 3
(smaller-than-expected new crop supplies) indicates that the price
is the highest, on average, during June. The producer
may make plans to sell one-half of anticipated production
during June and to sell the balance off the combine. Such
a decision would be supported by the price index in Figure
10, which depicts the movement of the September futures
price when new crop supplies are smaller than expected.
Consider a situation where carryover supplies are
plentiful, and in mid-June it becomes apparent that a very
large wheat crop is being produced. The producer should
consider selling a substantial amount of anticipated
production immediately according to Figure 4
(larger-than-expected new crop supplies). Should the producer sell the balance
of the crop off the combine or wait for the price
improvement in the fall that the moving average seasonal price
index suggests is likely, on average? Figure 4 needs to be
studied along with the information and methods in EC-1011.
If large wheat crops are being produced worldwide as
in 1990, the producer should probably consider selling
the balance off the combine. If government programs are
being used aggressively to export wheat as in 1992,
storage should be considered if futures prices, basis and
storage costs support the decision.
Campbell, Gerald, Primer on Agricultural
Options, Fact Sheet No. 1, NCR Publication No. 217.
Ferris, John, Developing Marketing Strategies and
Keeping Records on Corn, Soybeans and Wheat, Fact Sheet No.
4, NCR Publication No. 217, December 1985.
Ferris, John, Using Seasonal Cash Price Patterns for Selling
Decisions on Corn, Soybeans and Wheat, Fact Sheet
No. 3, NCR Publication No. 217.
Flaskerud, George, Basis For Selected North Dakota
Crops, North Dakota State University Extension Service
Publication EC-1011, March 1991.
Good, Darrel, Deferred Pricing Alternatives for
Grain, Fact Sheet No. 2, NCR Publication No. 217.
King, Robert P., Paul L. Fackler and Patti A. Held,
Options, Microcomputer Program, University of Minnesota
Extension Publication AG-CS-3003-S, 1991.
McDonald, Hugh, The Minimum Price Contract - A
New Marketing Alternative, Fact Sheet No. 9, NCR
Publication No. 217.
O'Connor, Carl and Kim Anderson, "Understanding
Basis," Business Management in Agriculture: Volume
III, Joint Project of the Cooperative Extension Service, Farm
Credit Services and Chicago Mercantile Exchange, 1989.
Purcell, Wayne D. Agricultural Marketing: Systems,
Coordination, Cash and Futures Prices, Reston Publishing
Company, Reston, Virginia, 1979.
Reff, Tom, Determining Grain Storage
Costs, North Dakota State University Extension Service Publication EC-801,
July 1983.
Satrom, John P., Alfred K. Chan, and William W.
Wilson, Commercial and Producer Applications Using Options
on Grain Futures, Agricultural Economics Report No.
200, Department of Agricultural Economics, North Dakota
State University, Fargo, N.D., May 1985.
Shane, Richard, Feed Grain Buying
Alternatives, Fact Sheet No. 15, NCR Publication No. 217, February 1992.
For Crops
Table A.1. Seasonal price and variability indexes based on
the moving average, 1978-1999 to-arrive prices.
-------------------------------------------------------------
Commodity Jan Feb Mar Apr May Jun
-------------------------------------------------------------
Hard Red
Spring Wheat
Price index 99.5 99.3 99.7 102.1 103.1 102.3
Variability index 8.5 10.7 11.4 13.7 15.4 14.6
Hard Amber
Durum
Price index 101.5 101.9 100.5 99.5 101.3 99.1
Variability index 14.5 17.1 15.7 16.7 16.9 15.4
Corn
Price index 95.7 97.8 103.1 106.5 108.2 108.6
Variability index 11.9 9.7 12.0 12.1 17.6 17.0
Feed Barley
Price index 99.4 100.2 101.1 103.1 104.2 102.3
Variability index 11.6 11.8 9.1 12.2 16.3 20.4
Malting Barley
Price index 99.4 99.5 99.6 102.5 103.2 102.1
Variability index 8.3 11.4 17.1 19.7 18.0 16.8
Oats
Price index 101.5 99.9 100.1 99.9 101.9 101.3
Variability index 12.4 13.9 15.7 16.7 16.0 18.2
Soybeans
Price index 97.8 97.8 100.6 102.4 104.4 104.0
Variability index 6.6 6.1 9.8 10.9 14.0 16.0
Sunflower Oil Type
Price index 99.4 98.3 100.5 103.9 107.5 106.8
Variability index 14.0 12.3 13.9 14.2 15.6 15.7
-------------------------------------------------------------
-------------------------------------------------------------
Commodity Jul Aug Sep Oct Nov Dec
-------------------------------------------------------------
Hard Red
Spring Wheat
Price index 99.7 96.5 97.4 99.7 100.6 100.1
Variability index 13.6 11.5 11.5 10.2 10.4 8.4
Hard Amber
Durum
Price index 97.0 96.5 99.2 101.4 101.4 100.6
Variability index 20.1 19.5 16.3 14.2 11.9 10.8
Corn
Price index 104.1 98.5 94.4 93.1 95.4 94.6
Variability index 18.4 16.7 15.5 14.2 13.7 11.7
Feed Barley
Price index 98.1 96.1 97.2 99.7 101.3 97.3
Variability index 15.3 12.0 13.4 14.7 18.6 13.6
Malting Barley
Price index 97.4 95.3 98.0 100.9 102.6 99.7
Variability index 16.2 17.3 16.8 14.4 9.0 8.6
Oats
Price index 99.0 95.5 97.7 99.0 101.6 102.7
Variability index 18.6 15.9 11.9 10.7 14.4 13.5
Soybeans
Price index 102.5 99.3 98.5 96.2 98.8 97.8
Variability index 11.3 15.4 16.3 11.7 12.4 7.3
Sunflower Oil Type
Price index 103.4 99.3 96.8 93.3 94.2 96.6
Variability index 18.9 16.9 13.2 8.8 8.6
-------------------------------------------------------------
Table A.2. Seasonal price indexes for hard red spring wheat
September futures on the MGE, select years, based on the
annual average.
-------------------------------------------------------------
Smaller-than-Expected Supply
1978-99 ---------------------------------------------
Month Avg. 1980 1988 1989 1991 1996 1997 Avg.
-------------------------------------------------------------
Jan 99.4 101.1 87.3 99.6 97.2 89.3 91.3 94.3
Feb 99.6 102.9 88.9 100.6 99.1 92.4 93.4 96.2
Mar 99.1 98.5 86.9 102.4 104.1 93.9 100.2 97.7
Apr 100.2 93.6 90.4 100.8 105.3 111.0 111.0 102.0
May 101.2 97.6 93.5 102.9 102.2 121.6 106.1 104.0
Jun 101.1 97.6 120.0 98.7 99.1 109.0 98.1 103.8
Jul 100.3 105.6 117.4 98.5 94.2 98.7 96.2 101.8
Aug 99.2 103.0 115.6 96.5 98.7 94.7 103.7 102.0
-------------------------------------------------------------
------------------------------------------------
Larger-than-Expected Supply
1978-99 ---------------------------------
Month Avg. 1982 1990 1992 1998 Avg.
------------------------------------------------
Jan 99.4 103.4 108.9 103.4 105.9 105.4
Feb 99.6 104.7 107.3 111.0 107.3 107.6
Mar 99.1 101.8 105.3 105.2 107.1 104.9
Apr 100.2 102.5 104.7 98.8 101.8 102.0
May 101.2 98.8 104.0 101.2 100.2 101.1
Jun 101.1 96.1 98.9 101.0 96.6 98.2
Jul 100.3 97.2 89.5 93.0 92.7 93.1
Aug 99.2 95.4 81.4 86.2 88.3 87.8
------------------------------------------------
Table A.3. Seasonal price indexes for corn
December futures on the CBOT, select years,
based on the annual average.
--------------------------------------------
Smaller-than-Expected Supply
1978-99 ----------------------------
Month Avg. 1983 1988 1993 Avg.
--------------------------------------------
Jan 101.1 89.8 80.1 99.1 89.7
Feb 101.8 91.9 82.7 97.8 90.8
Mar 102.2 94.3 83.5 99.1 92.3
Apr 102.4 96.5 85.9 99.6 94.0
May 101.8 92.9 88.2 97.4 92.8
Jun 102.4 88.8 117.3 94.5 100.2
Jul 100.3 96.4 123.3 101.7 107.1
Aug 97.7 113.3 113.9 99.4 108.9
Sep 96.5 114.1 111.9 98.1 108.0
Oct 96.7 110.7 110.2 101.5 107.5
Nov 97.2 111.3 102.9 111.8 108.7
--------------------------------------------
------------------------------------------------------
Larger-than-Expected Supply
1978-99 ---------------------------------------
Month Avg. 1979 1982 1985 1992 1994 Avg.
------------------------------------------------------
Jan 101.1 91.6 111.0 108.2 108.5 111.2 106.1
Feb 101.8 94.3 113.3 107.6 111.2 110.8 107.4
Mar 102.2 94.3 109.0 106.3 110.0 108.6 105.6
Apr 102.4 96.8 112.1 107.6 104.3 105.3 105.2
May 101.8 99.1 107.3 105.1 107.1 104.2 104.6
Jun 102.4 108.4 103.8 102.8 108.3 106.1 105.9
Jul 100.3 112.9 98.4 97.1 97.1 92.6 99.6
Aug 97.7 102.5 89.6 90.1 90.8 91.8 93.0
Sep 96.5 101.3 84.6 88.8 89.7 91.0 91.1
Oct 96.7 101.2 83.0 90.2 85.9 89.2 89.9
Nov 97.2 97.7 87.9 96.2 87.1 89.1 91.6
------------------------------------------------------
Table A.4. Seasonal price indexes for soybean
November futures on the CBOT, select years,
based on the annual average.
------------------------------------------------------
Smaller-than-Expected Supply
1978-99 ----------------------------------------
Month Avg. 1980 1983 1984 1988 1993 Avg.
------------------------------------------------------
Jan 100.9 104.4 99.9 94.1 96.1 101.2 99.1
Feb 100.6 103.7 100.0 95.0 92.7 97.9 97.9
Mar 101.0 97.0 96.3 101.5 89.8 98.1 96.5
Apr 101.4 89.7 97.0 104.0 91.9 97.6 96.0
May 101.6 88.9 91.4 107.1 98.2 97.0 96.5
Jun 101.2 90.1 87.1 106.2 120.6 96.9 100.2
Jul 99.2 103.9 95.7 94.1 113.2 113.2 104.0
Aug 98.1 104.0 119.0 95.1 110.0 106.5 106.9
Sep 98.8 109.9 122.3 93.0 108.1 100.3 106.7
Oct 97.2 110.1 113.4 95.3 99.3 96.1 102.8
------------------------------------------------------
--------------------------------------------------
Larger-than-Expected Supply
1978-99 ---------------------------------
Month Avg. 1979 1985 1992 1994 Avg.
--------------------------------------------------
Jan 100.9 97.3 101.3 100.2 101.6 100.1
Feb 100.6 99.1 102.1 101.9 102.7 101.5
Mar 101.0 99.7 103.2 104.6 104.5 103.0
Apr 101.4 98.4 106.7 101.6 100.7 101.9
May 101.6 100.7 102.9 105.4 104.4 103.4
Jun 101.2 109.0 100.1 106.7 107.2 105.8
Jul 99.2 105.5 98.4 97.8 94.6 99.1
Aug 98.1 99.2 93.1 93.0 94.2 94.9
Sep 98.8 98.9 93.9 93.9 94.6 95.3
Oct 97.2 93.6 94.1 92.4 91.5 92.9
--------------------------------------------------
This publication was partially produced with support from the North Dakota Grain Growers Association and
the Farm Credit Services Associations in North Dakota headquartered in Fargo, Mandan, Minot and Grand Forks.
EB-61,
December 2000
|
