ECON 337:

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ECON 337 Agricultural Marketing

Chad Hart Associate Professor chart_at_iastate.edu 51
5-294-9911
Lee Schulz Assistant Professor lschulz_at_iastate.edu
515-294-3356
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Seasonal Patterns

• A price pattern that repeats itself with some
  degree of accuracy year after year.
• Supply and demand
• Often sound reasons
• Widely known
• Linked to storage cost or basis patterns in
  grains
• Linked to conception and gestation in livestock

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How to Calculate Seasonal Index

• Pick time period (number of years)
• Pick season period (month, quarter)
• Calculate average price for season
• Calculate average price over time
• Divide season average by over time average price
  x 100

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Iowa S. Minnesota Live Cattle Prices Total All
Grades, /cwt
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2004 81.30 79.55 85.49 86.90 88.16 89.64 84.04 84.15 81.27 82.43 82.37 85.39 84.22
2005 88.36 87.48 92.37 91.92 89.03 83.09 79.66 80.11 83.83 86.61 89.16 92.84 87.04
2006 92.96 89.70 86.07 82.25 79.74 81.72 80.90 85.41 88.03 87.24 86.17 85.76 85.50
2007 87.30 90.17 96.90 98.69 96.28 88.02 89.07 91.45 92.46 89.98 91.21 91.03 91.88
2008 90.27 90.49 89.39 89.86 93.22 93.90 98.02 98.34 95.32 87.21 88.42 83.93 91.53
2009 83.15 80.31 81.79 87.55 85.26 81.61 82.39 82.06 81.52 80.71 81.85 81.54 82.48
2010 84.70 87.26 92.30 98.77 98.03 92.60 93.34 94.83 96.06 97.43 98.68 101.93 94.66
2011 105.63 108.04 117.94 119.89 111.74 109.60 112.52 113.83 116.54 120.11 125.20 124.57 115.47
2012 123.85 124.37 127.38 123.27 121.82 121.27 114.93 118.77 123.40 123.72 125.73 125.45 122.83
2013 125.24 124.30 126.00 127.17 126.42 122.20 121.19 123.97 123.76 128.55 130.68 131.69 125.93

Average 96.28 96.17 99.56 100.63 98.97 96.37 95.61 97.29 98.22 98.40 99.95 100.41 98.15
Ratio 98.1 98.0 101.4 102.5 100.8 98.2 97.4 99.1 100.1 100.2 101.8 102.3
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Using Seasonal Index to Forecast

• Observe price in time t1 P1
• Forecast price in time t2 P2
• Start with P1/ I1 P2 / I2
• Then P1 x I2 / I1 P2
• Assume that cattle are selling at 141.61 /cwt in
  January. What is the forecast of July?
• PJan x IJul / IJan PJul
• 141.61 x 0.974 / 0.981 140.78

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Livestock Marketing Information Center Data
Source USDA-AMS, Compiled Analysis by LMIC
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Livestock Marketing Information Center Data
Source USDA-AMS, Compiled Analysis by LMIC
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Livestock Marketing Information Center Data
Source USDA-AMS, Compiled Analysis by LMIC
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Livestock Marketing Information Center Data
Source USDA-AMS, Compiled Analysis by LMIC
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Livestock Marketing Information Center Data
Source USDA-AMS, Compiled Analysis by LMIC
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Estimated Returns to Finishing Yearling Steers

• During 2003-2013 the range in profits was
  -306.51 to 377.94 per head
• 31.1 (68.9) of the months profitable
  (unprofitable)

  Months of Months of   Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss)
Month sold Profit Loss   Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss)
January 27.3 72.7   Over 100 7.58
February 9.1 90.9   80.01 to 100 3.79
March 45.5 54.5   60.01 to 80 6.06
April 54.5 45.5   40.01 to 60 6.06
May 54.5 45.5   20.01 to 40 3.79
June 36.4 63.6   0.01 to 20 3.79
July 27.3 72.7   -0.01 to -20 11.36
August 27.3 72.7   -20.01 to -40 5.30
September 18.2 81.8   -40.01 to -60 9.85
October 18.2 81.8   -60.01 to -80 6.82
November 27.3 72.7   -80.01 to -100 6.82
December 27.3 72.7   Under-100 28.79
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Livestock Marketing Information Center Data
Source USDA-AMS, Compiled Analysis by LMIC
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Dramatic Changes Have Taken Place
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Estimated Returns to Farrow to Finish

• During 2003-2013 the range in profits was -53.63
  to 46.82 per head
• 55.3 (44.7) of the months profitable
  (unprofitable)

  Months of Months of   Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss)
Month sold Profit Loss   Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss) Percentage of Months with Profit (Loss)
January 18.2 81.8   Over 25.00 21.2
February 54.5 45.5   20.01 to 25.00 5.3
March 54.5 45.5   15.01 to 20.00 3.0
April 54.5 45.5   10.01 to 15.00 11.4
May 72.7 27.3   5.01 to 10.00 6.8
June 81.8 18.2   0.01 to 5.00 7.6
July 81.8 18.2   -0.01 to -5.00 6.8
August 81.8 18.2   -5.01 to -10.00 5.3
September 63.6 36.4   -10.01 to -15.00 8.3
October 45.5 54.5   -15.01 to -20.00 3.8
November 27.3 72.7   -20.01 to -25.00 3.8
December 27.3 72.7   Over -25.00 16.7
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Seasonal Pricing Patterns
Source USDA, NASS, Monthly Price Data 1980-2013
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Corn Pricing Patterns
Source USDA, NASS, Monthly Price Data 1980-2013
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Soybean Pricing Patterns
Source USDA, NASS, Monthly Price Data 1980-2011
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Charting
Channel lines
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Sell Signal
A sell signal is one close below the charting
lines
Sell signal
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Buy Signal
Some chartists need only one close above the
charting line to create a buy signal, others use
two closes above.
Buy signal
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Resistance and Support
Resistance level A price level where the market
seems to hit and bounce down
Support level A price level where the market
seems to hit and bounce up
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Key Reversal
A key reversal is when the daily high and low
price range exceed the price range for the
previous two days.
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Gaps
Gaps often occur when a major new piece of
information hits the market. They are often
filled in by later price movements.
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Double Tops Bottoms
Double tops and bottoms show prices with major
technical resistance. These can be several days
apart.
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Head Shoulders
Source Figure 7, Charting Commodity Futures Ag
Decision Maker, File A2-20
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Moving Averages
9 day average 18 day average 40 day average
Sell signal
Buy signals
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Relative Strength Index

• Looks at last X days worth of closing prices
• X 9, 14, 30, etc.
• Summarizes upward and downward price movements
  during the period
• Record the last 14 days worth of price changes,
  based on closing prices
• Sum the positive and negative price changes and
  create average for each
• Relative Strength Index
• (Up average/(Up average Down average))100

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RSI for Nov. 2014 Soybeans
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Relative Strength Index
RSIs above 70 (80) are considered signals of a
market due to decline
RSIs below 30 (20) are considered signals of a
market due to rally
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Does Technical Analysis Work?

• Arguments for it
• Real world markets are not perfectly rational
• Markets may be slow to respond to new information
• Technical analysis works with the psychological
  biases
• It works because so many people use it
• Self-fulfilling
• Arguments against
• Efficient market hypothesis
• The current price holds all of the relevant
  information

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• Class web site
• http//www.econ.iastate.edu/chart/Classes/econ337
  /Spring2014/
• See you in lab, Heady 68.