1. Assistant Professor/Grain Markets Specialist
ECON 338C:
Topics in Grain Marketing
Chad Hart
Assistant Professor/Grain Markets Specialist 1

2. Today’s Topic Price Projections and Issues
with an update on the World Ag. Supply
& Demand Estimates report

3. Source: USDA, WASDE report, April 2009

4. Source: USDA, WASDE report, April 2009

5. Source: USDA, WASDE report, April 2009

6. Source: USDA, WASDE report, April 2009

7. July 2010 Corn Futures
Source: CBOT

8. Likely Range
Example: CBOT July 2010 Corn Futures

9. Likely Range
Based on current futures and the option premiums for options on those futures
They determine an implied volatility, a measure of the expected variability of the futures price from the current point on
If you take Econ 437, you’ll learn about the mathematical models used to derive the implied volatility
Given the volatility, we can outline the likely range

10. Pricing Paths
Example: CBOT July 2010 Corn Futures

11. Prices Could Be Higher
Example: CBOT July 2010 Corn Futures

12. … Or Lower
Example: CBOT July 2010 Corn Futures

13. Market Situation
Reviewing recent past and the current situation in the market
Using historical relationships to link changes in key variables to changes in commodity prices
Evaluating if current relationships differ from historical patterns

14. Market Outlook
Interpreting market factors that impact prices and shape marketing and management decisions
Analyzing how the changing supply and demand factors will impact price
Basing outlook on economic principles, statistical analysis, and market knowledge

15. Market Outlook Outlook depends on timing
Immediate: within a day or a week
Short term: few weeks to few months
Long term: next growing season to multiple years
Different information needed for each type

16. Immediate Term Outlook
Market timing
Any scheduled market movers
(USDA reports, etc.)
Example: CBOT July 2010 Corn Futures

17. Short Term Outlook
Prices are adjusting to balance demand with available supplies
One reason to need short term outlook: Storage decisions
Example: CBOT July 2010 Corn Futures

18. Long Term Outlook
Buyers and sellers have time to adjust to changes in prices and quantities.
Important for investment decisions and government policy setting
Example: CBOT July 2010 Corn Futures

19. Sources of Outlook Information
Private sector market analysis firms
For-profit companies that sell services
Often more short-term focused
May be associated with a trading company
In-house analysis
Outlook for the company with own staff
ADM, Cargill, etc.
But your local elevator may offer analysis as well

20. Sources of Outlook Information
Land grant universities
Long term
Example: Food and Agricultural Policy Research Institute (FAPRI)
Intermediate to short term
Examples: Iowa Farm Outlook (Grain, Livestock, Dairy), Farmdoc.com, Livestock Market Information Center
Often affiliated with university extension services
Commodity organizations
Typically narrowly focused on commodity
May miss breath of outlook

21. Sources of Outlook Information
USDA Data and Analysis Sources
National Agricultural Statistical Service (NASS)
Production, consumption, and survey statistics
Agricultural Marketing Service (AMS)
Summaries of local market prices
Economic Research Service (ERS)
Analysis of agricultural markets and government policies
Foreign Agricultural Service (FAS)
Trade information and analysis

22. Examples of Outlook Information
World Agricultural Supply and Demand Estimates report
Iowa Farm Outlook
FAPRI Outlook

23. U.S. Corn Supply and Use 2007 2008 2009 Area Planted (mil. acres) 93.5
86.0
85.0
Yield
(bu./acre)
150.7
153.9
Production
(mil. bu.)
13,038
12,101
Beg. Stocks
1,304
1,624
Imports 20 15
Total Supply
14,362
13,740
Feed & Residual
5,938
5,350
Ethanol
3,026
3,700
Food, Seed, & Other
1,337
1,290
Exports
2,436
1,700
Total Use
12,737
12,040
Ending Stocks
Season-Average Price
($/bu.)
4.20
Source: USDA, WASDE and NASS 23 23

24. Iowa Farm Outlook Monthly outlook from ISU Extension
Other universities offer similar services 24 24

25. FAPRI Reports U.S. Corn Utilization World Soybean Production
Source: FAPRI, 2009 25 25

26. Evaluating Source of Information
Know the source of data and analysis
Understand the motivation of the source
Public institution
Private analysis, for sale
Private analysis, confidential
What are the resources and track record

27. Outlook Issues Efficient market hypothesis
All available information is quickly factored into the markets and embedded in the price
New information and/or changes in supply and demand after the outlook alter outcomes
Participants react to forecasts

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

29. Seasonal Pricing Patterns
Source: USDA, NASS,
Monthly Price Data

30. Charting
Channel lines

31. Sell Signal A sell signal is one close below the charting lines

32. Buy Signal
Some chartists need only one close above the charting line to create a buy signal, others use two closes above.
Buy signal

33. Key Reversal
A key reversal is when the daily high and low price range exceed the price range for the previous two days.

34. Gaps
Gaps often occur when a major new piece of information hits the market. They are often filled in by later price movements.

35. Double Tops & Bottoms
Double tops and bottoms show prices with major technical resistance. These can be several days apart.

36. Head & Shoulders Source: Figure 7, Charting Commodity Futures
Ag Decision Maker, File A2-20

37. Moving Averages 9 day average 18 day average 40 day average
Sell signal
Buy signals

38. 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

39. Relative Strength Index
RSI for July 2010 Corn

40. Relative Strength Index
RSI’s above 70 (80) are considered signals of a market due to decline
RSI’s below 30 (20) are considered signals of a market due to rally

41. 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

42. Convergence Issues
Typically, as futures contracts reach maturity, futures price and cash prices at delivery points tend to converge to the same level.
For several grain and oilseed futures contracts over the last few years, this has not occurred.
“Poor Convergence Performance of CBOT Corn, Soybean and Wheat Futures Contracts: Causes and Solutions”
Scott Irwin, Philip Garcia, Darrel Good, and Eugene Kunda
University of Illinois, March 2009

43. Corn (Lack of) Convergence
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

44. Soybean (Lack of) Convergence
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

45. Wheat (Lack of) Convergence
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

46. Why Is Convergence An Issue?
Non-convergence indicates the market is out-of-balance.
“When a contract is out of balance the disadvantaged side ceases trading and the contract disappears.” (Hieronymus, 1977)
Non-convergence adds to the uncertainty in basis and limits hedging effectiveness.
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

47. Factors
The relationship between the spread between futures contracts and the cost of carry (think storage costs)
In the settlement process for corn and soybean futures, the delivery instrument is a shipping certificate.
If it is advantageous to the holder of a shipping certificate, they can delay delivery and effectively store the grain, paying CBOT set storage costs.
Structural issues related to the delivery process
Does the general trade flow of the commodity line up with the possible delivery points under the futures contract?
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

48. Spread vs. Carry
Look at the ratio of the futures spread versus the cost of carry
Futures PriceNext – Futures PriceNearby
Storage Costs + Interest
Irwin, et al. found lack of convergence when ratio is high (> 80%)
A lower ratio implies smaller returns to holding a shipping certificate and more offsetting positions are taken, lowering futures prices.
If the commodity is still in storage, then cash sales aren’t happening, lowering cash prices.
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

49. Delivery Points Corn Soybeans Wheat
How much of the commodity is moving through the delivery point areas?
Corn
Soybeans
Wheat
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

50. Convergence vs. Carry - Corn
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

51. Convergence vs. Carry - Soy
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

52. Possible Reasons for High Ratios
CBOT storage rates below commercial storage rates
Large “long-only” index funds rolling to the next contract at the same time
Large risk premiums built into futures to cover uncertainty
Irwin, et al. found support for #1 and arguments for #3, but did not find support for #2.
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

53. Possible Remedies Increase CBOT storage rates
Done for corn and soybeans in late 2008
Change delivery points to include more of the commodity shipping area
Mostly an issue for wheat
Other proposals:
Move to cash settlement
Force delivery
Limit the number of certificates that can be held
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

54. Relative Basis Change - Corn
The closer this is to one, the more effective hedging is.
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

55. Relative Basis Change - Soy
The closer this is to one, the more effective hedging is.
Source: Irwin, Garcia, Good, and Kunda, 2009
Marketing and Outlook Research Report

56. Class web site: http://www. econ. iastate
Class web site: See you next week!