November 2014

Global environment

Local execution

Michael Swanson Ph.D.

Wells Fargo

Key questions

1. What are commodities worth?2. Why are commodities worth that?3. Who gets what share?4. What differentiates the producers?5. What’s your “play”

2

Where does volatility come from?

Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14$0

$1

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$7

$8

Minnesota Corn Prices and Cost of Productionper bushel

GRAIN in $ / BUAverage cost of production

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More money – More risk

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2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013F 2014F$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

MN Farm Income in Billions

Gross expensesNet Farm Income

Loops create cycles

Monetary

Policy

Economy

Fiscal Policy

Agriculture Energy

5

Interest rates and valuations

Federal Reserve Ultra low rates are not about ag They have inflated valuations They have influenced exchange rates

Foreign central banks Respond to the Federal Reserve Focused on their economies

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Bullish or Bearish? Or wrong?

Apr-73 Apr-78 Apr-83 Apr-88 Apr-93 Apr-98 Apr-03 Apr-08 Apr-13-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%Performance Gap: Actual GDP less Potential

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Farm the best – Forget the rest

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$-

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

$9,000 MN South Central Farm Land

Productivity 50s

Productivity 70s

Productivity 90s

Per Acre

42 degrees in Fargo ND

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0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000 MN Ag Land Sales Price$ per acre

Me-dian

Source: U of MN MLE, Wells Fargo

What about Minnesota?

10Jan-93 Jan-95 Jan-97 Jan-99 Jan-01 Jan-03 Jan-05 Jan-07 Jan-09 Jan-11 Jan-13

$-

$100

$200

$300

$400

$500

$600

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1

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9"Cash flow v. Opportunity Cost"

Returns w/o labor, mgmt or land15 Fixed Rate Mortgage

Per acre Percent

Keep an eye on the future not past

11Jan-93 Jan-95 Jan-97 Jan-99 Jan-01 Jan-03 Jan-05 Jan-07 Jan-09 Jan-11 Jan-13

$-

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

$16,000

$18,000

Implied Net Present Values

How are the cycles linked?

NAFTAEconomy

NAFTAAgriculture

GlobalAgriculture

GlobalEconomy

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How fast can panic spread?

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

Real GDP GrowthWorld less USAUnited States

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China

What is the answer to the question?

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A Standard Pareto Distribution

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China/Hong Kong

Canada

Mexico

Japan

Korea, South

Taiwan

Indonesia

Germ

any(*)

Philippines

Vietnam

United Kingdom

Netherlands

Turkey

Brazil

Spain

Australia(*)

Egypt

Venezuela

Colombia

Thailand

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

16%

32%

45%54%

59%

61%

Cumulative Agricultural Exports by Country

The Wal*Mart Effect

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2007 2008 2009 2010 2011 2012 2013 Jan - Sep 2014

-$5

$0

$5

$10

$15

$20

$25

2.6 6.5

9.1

13.8 16.1

22.0 22.7

11.3 2.6

10.3 3.9

5.2

7.1

0.5

(1.1) (3.3)

Net Trade BalanceAg, Forestry and Fishing

ROWChina/HK

Billions

What has happened in 2014 so far?

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Product 2009 2010 2011 2012 2013Jan - Sep

2013Jan - Sep

2014Chg YTD

Bulk 10.2 13.4 14.1 19.7 17.8 7.7 7.9 0.2$ Intermediate 0.9 2.2 1.9 2.4 3.5 2.5 2.7 0.2$ Consumer Oriented 1.1 1.3 2.2 2.6 3.5 2.0 2.2 0.2$ Forest Products (1.7) (1.5) (0.6) (1.3) (0.7) (0.6) (0.4) 0.1$ Fish Products (1.4) (1.5) (1.4) (1.4) (1.4) (0.9) (1.1) (0.2)$

Grand Total 9.1 13.8 16.1 22.0 22.7 10.6 11.3 0.6$

China/Hong Kong Net Ag Trade in Billions

Which countries drive prices Same commodity different price

Market based signals Policy based signals

Which commodity Protein Energy Minerals

Sell Side Buy Side

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Compare and contrast

-5

0

5

10

15

20

25

30

35

(2.2)

29.6

US Net Agricultural Trade

IndiaChina/HK

Billions of $s

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Does India ever find a higher gear?

-

1,000

2,000

3,000

4,000

5,000

6,000

4,832

1,483

GDP in Constant US Dollars

ChinaIndia

Billions

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Question your assumptions Global demand growth

Population GDP Diet

Global supply growth Acreage Productivity Trade barriers

Policy shocks

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Productivity

Income

Population

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The gears work together

The numbers everyone quotes

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

-

1

2

3

4

5

6

7

8

$0

$10

$20

$30

$40

$50

$60

$70

$80

Global Population (left axis)

Global GDP (right axis)

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Same numbers different dimension

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

-

0.5

1.0

1.5

2.0

2.5

(3)

(2)

(1)

-

1

2

3

4

5

6

7 Global Population (left axis)Global GDP (right axis)

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Big numbers all around

500

1,000

1,500

2,000

2,500

f(x) = 27.9573375901876 x + 804.315147474748R² = 0.974784532143057

Global Grain ProductionMillions of metric tons

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The feedback mechanism in action

285

295

305

315

325

335

345

355 Global Grain per CapitaKilograms

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No one punches harder than the US in the grain world Top 10 countries

86% of the acreage 90% of the production

Remaining 112 countries 14% of acreage 10% of the production

That still misses the point

27

Just like the “Big 10” a mix of champs and chumps

Area Harvested

Production Yield

CountryGrain (1000

HA)Grain (1000

MT)Grain

(MT/HA)% of

acreage% of

productionYield

PunchChina 62,271 343,322 5.5 14.1 21.8 1.5 United States 58,009 404,141 7.0 13.2 25.6 1.9 European Union 57,308 296,740 5.2 13.0 18.8 1.4 India 54,877 135,140 2.5 12.5 8.6 0.7 Russia 38,071 84,401 2.2 8.6 5.3 0.6 Brazil 18,860 86,920 4.6 4.3 5.5 1.3 Australia 18,700 36,920 2.0 4.2 2.3 0.6 Kazakhstan 14,882 15,504 1.0 3.4 1.0 0.3 Canada 14,845 55,894 3.8 3.4 3.5 1.1 Ukraine 14,580 55,930 3.8 3.3 3.5 1.1

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How much grain does the world need?

Per capita Best measure Substitutes

Grain Meat

Efficiency of conversion Diet Demographics Distribution

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Trend versus Cycle

1.25

1.45

1.65

1.85

2.05

2.25

2.45

2.65

f(x) = 0.000224580898538896 x + 2.50044468807954R² = 0.0221067393306588

f(x) = 0.00973092497475068 x + 1.43661275307303R² = 0.962728298154432

f(x) = 0.00197519499824517 x + 1.2960218090599R² = 0.650479333602565

Global Supplies Per Capita

GrainsLinear (Grains)

Log of Per Capita

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You “economic” life is in their hands

Monetary policy When does “cheap” money end? Who is the furthest out of line? Values

China trade Trade policies Internal supply competition

Biofuels policy Energy pricing and arbitrage Lobbyists in action

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