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7/30/2019 Commodity Markets and Commodity Mutual Funds
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Commodity Markets andCommodity Mutual Funds
Chris Plantier
Investment Company Institute
October 15, 2012
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Why Commodity Investment Doesnt
Explain Commodity Price Increases
I. Commodity Investment Globally and theFinancialization of Commodities
II. Spurious Relationship btw Assets and PricesIII. Economic Fundamentals Strong Global
Growth and Weak U.S. Dollar
IV. An Empirical Horse RaceV. Why Commodity Mutual Funds Cant Explain
Higher Commodity Prices
2
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Commodity Investment Globally
According to BarCap, worldwide assets undermanagement in commodity investment products
(ETPs, commodity swaps, and medium-termnotes) stood at $426 billion in November 2011,compared to $156 billion in November 2008
Most of the increase ($170 billion) represents net
inflows from investors spread across a number ofcommodity markets; the remainder$100billionreflects the recovery in commodity pricessince late 2008
3
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Global Commodity Markets are Massive
With Over $10 Trillion Monthly Turnover
Barcap estimates global commodity futures andoptions markets at $11.8 trillion in October 2011
However, size varies by commodity with futuresand options markets of gold, zinc, crude oil, andcopper all exceeding $1 trillion
4
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Global Commodity Market Size
5
Billions of dollars
Note: Spot (physical) market value is calculated using supply and average price for 2010 for each individual commodity.
Source: Barclays Capital
CommodityTotal sales in spot
market$ Billions, annual
Trading volume in futures andoptions markets
$ Billions, monthly
Futures and optionsmarket open interest
$ Billions
West Texas Intermediateand Brent crude oil
2,500 2,800 279
Live cattle CME 1,500 76 21
Heating oil and gasoil 800 982 74
Unleaded gasoline 705 318 33
Gold 182 2,067 145
Silver 21 369 30
Zinc 27 1,910 13
Copper 144 1,228 58Aluminium 89 484 47
Corn 104 291 64
Wheat CBOT 165 61 17
Soybean 120 375 55
Totals 6,357 10,964 835.0
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Impact of Financialization of
Commodities on Commodity Prices
Any price impact from index funds likely stemsfrom two sourcesnew flows and the
rebalancing of positions over time In theory, fund flows could impact prices as
some critics argue, empirical question though
Rebalancing generally stabilizes prices P fund (or swap dealer) sells position and P fund (or swap dealer) buys position
However, monthly roll may impact prices at
certain times of the month 6
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Financialization of Commodities,
a.k.a. the Massive Passive ArgumentSometimes referred to as massive passives, commodity indexfunds have created a massive, ongoing demand for futures contractsunconnected to normal supply and demand for the underlying
commodities... the more index funds and their swap dealers push tobuy long future contracts and outnumber the speculators seeking tobuy shorts, the more their buying pressure, by the very nature ofsupply and demand, will drive up the price of the long contracts. Theresulting higher futures prices then translate all too often into higherprices for the underlying commodities, in part because so many of
the contracts for the underlying commodities use futures prices asthe commodity selling prices. Senator Levins Opening StatementNov 2011
7
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0
50
100
150
200
250
300
350
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
1997 1999 2001 2003 2005 2007 2009 2011
Gold (left scale), price per ounce
Corn (right scale), price per metric ton
WTI (right scale), crude oil price per barrel
Commodity Prices Rose Over the Last
Fifteen YearsMonthly, 1997-2011*
Price per unit (dollars) Price per unit (dollars)
*Data to December 2011
Source: World Bank
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Assets and Number of Commodity
Mutual Funds (CMFs)
9
Monthly, 2004-2011*
*Data through December 2011
Source: Investment Company Institute
0
5
10
15
20
25
30
$0
$10
$20
$30
$40
$50
$60
2004 2005 2006 2007 2008 2009 2010 2011
Assets (billions) Number of funds
Assets (left scale)
Number of funds(right scale)
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Commodity Mutual Fund (CMF) Assetsand Commodity Price Indexes
10
Monthly, 2006-2011*
*Data through December 2011Note: Prices indexed to 100 in January 2006
Sources: Investment Company Institute and Bloomberg
50
75
100
125
150
175
200
$0
$10
$20
$30
$40
$50
$60
2006 2007 2008 2009 2010 2011
Assets (billions) Index level
Commodity mutual fund assets (left scale)
Dow Jones-UBS CommodityIndex (right scale)
S&P GSCI (right scale)
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Emerging Market Industrial Production
Growth and Commodity Price Growth
11
Monthly, 2005-2011*
*Data to October 2011.Note: The correlation between the two growth rates is 0.82.
Sources: Netherlands Bureau for Economic Policy Analysis and Bloomberg
-60%
-50%
-40%-30%
-20%
-10%
0%
10%
20%
30%
40%
50%
-10%
-5%
0%
5%
10%
15%
20%
2005 2006 2007 2008 2009 2010 2011
Percentage year over year Percentage year over year
Emerging market industrial production growth
(left scale)
Dow Jones-UBS Commodity Index
(right scale)
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Commodity Prices & U.S. Dollar Value
12
*Data to October 2011.Note: The correlation between the two series is -0.87.
Sources: Bloomberg, Federal Reserve
Monthly, 2004-2011*
65
70
75
80
85
90
95200
300
400
500
600
700
800
900
2004 2005 2006 2007 2008 2009 2010 2011
Commodity price index Trade-weighted Index (inverted scale)
S&P GSCI (left scale)
Broad trade-weighted exchange value of U.S. dollar(right scale)
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Estimated Monthly/Weekly Regressions
Prices and contemporaneous CMF flows
(1) ln(Pt)= + *Ct/At-1,
Commodity prices, CMF flows, & fundamentals
(2) ln(Pt)= f(ln(Pt-1), Ct/At-1, ln(USDt),ln(EMt))
Lead/Lag relationship (VAR) on weekly data (3) ln(Pt)= f(ln(Pt-k), Ct-k/At-1-k),
(4) Ct/At-1 = f(ln(Pt-k), Ct-k/At-1-k),
13
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Monthly Results
14
Equation 1Fund Flows, CtEquation 2USD only Equation 2EM only Equation 2All Equation 2w/o Ct
Intercept -0.0062
(0.0093)
-0.0464
(0.5370)
-1.3131
(0.8889)
-1.8066**
(0.7105)
-1.1895*
(0.6807)
ln(Pt-1) -0.1819
(0.1198)
-0.0296
(0.1044)
-0.3140***
(0.0836)
-0.2944***
(0.0969)
Ct/At-1 0.2876**
(0.1385)
0.2609***
(0.0717)ln(USDt) -2.5333***
(0.5625)
-2.4282***
(0.4500)
-2.3703***
(0.5285)
ln(EMt) 2.4242***
(0.8163)
1.6917**
(0.6472)
1.8948***
(0.6327)
R-squared 0.0557 0.2985 0.1115 0.3955 0.3512
Adj. R-squared 0.0456 0.2832 0.0920 0.3683 0.3296D-W Statistic 1.738 1.946 2.106 2.012 1.995
Sample 2004M02 to
2011M12
2004M02 to
2011M12
2004M02 to
2011M11
2004M02 to
2011M11
2004M02 to
2011M11
*denotes statistical significance at the 10 percent level
** denotes statistical significance at the 5 percent level
*** denotes statistical significance at the 1 percent level
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ForecastsEconomic Fundamentals
versus Commodity Mutual Fund Flows
15
*Data and dynamic forecasts are from February 2004 to November 2011.Note: The correlation between the Dow Jones-UBS Commodity Index and the forecast based on economic fundamentals is0.80. It is -0.05 for the forecast based on flows.
Source: Bloomberg
Commodity price index level, monthly, 2004-2011*
100
150
200
250
300
350
400
450
500
2004 2005 2006 2007 2008 2009 2010 2011
Forecast based only oneconomic fundamentals
Dow Jones-UBS Commodity IndexForecast based only on
commodity fund flows
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Net New Cash Flow to CMFs and
Commodity Price Changes
16
Monthly, 2004-2011*
*Data as of December 2011
Sources: Investment Company Institute and Bloomberg (Dow Jones UBS Commodity Total Return Index)
-20%
0%
20%
40%
60%
80%
-$0.5
$0.0
$0.5
$1.0
$1.5
$2.0
2004 2005 2006 2007 2008 2009 2010 2011
Billions Monthly percent change
Monthly net new cash flow(left scale) Dow Jones-UBS Commodity Total
Return Index (right scale)
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Conclusion
Fundamentals, not funds, drive commodityprices, e.g., EM growth and USD matter
Flows to commodity mutual funds have little orno influence on commodity prices
This finding is consistent with academicresearch showing that financialization has not
driven commodity prices
Investing in commodity mutual funds providesimportant benefits for investors diversificationand natural hedge against inflation
17
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Why Commodity Mutual Funds CantExplain Higher Commodity Prices
First, commodity mutual funds experienced net outflowson average from January 2006 to June 2008 whilecommodity prices rose
Second, flows into commodity mutual funds are spreadacross a wide range of markets and thus do notconcentrate investment in a particular commodity (seeFigure 15 in paper)
Finally, the $47.7 billion in commodity mutual funds asof December 2011 is miniscule relative to the size ofglobal commodity markets
18
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Commodity Mutual Funds' ImpliedPosition in Commodity Markets
19
MarketImplied weight in individual
commodities1Percent
Implied dollar position incommodity, assets2
Billions
Share of index in market volumePercent
WTICrude 16.2% $7.7 0.5%Natural gas 10.4% 4.9 1.5%Gold 9.7% 4.6 0.2%Soybean 7.3% 3.5 0.9%Copper 7.1% 3.4 0.3%Corn 6.8% 3.2 1.1%Aluminium 4.9% 2.3 0.5%Wheat CBOT 4.5% 2.1 3.5%Heating oil 3.7% 1.8 0.5%
Unleaded gasoline 3.6% 1.7 0.5%Live cattle CME 3.3% 1.6 2.1%Sugar 3.2% 1.5 1.8%Silver 3.0% 1.4 0.4%Soybean oil 2.6% 1.3 N/AZinc 2.6% 1.3 0.1%Coffee 2.2% 1.1 1.3%
Nickel 2.1% 1.0 1.1%Lean hogs CME 1.9% 0.9 2.3%Cotton 1.9% 0.9 3.6%Brent crude 1.7% 0.8 0.1%Gasoil 0.7% 0.3 0.1%Wheat (KBOT) 0.1% 0.0 0.1%Lead 0.0% 0.0 0.0%
Feeder cattle CME 0.0% 0.0 0.2%Cocoa 0.0% 0.0 0.1%Tin 0.0% 0.0 0.0%Palladium 0.0% 0.0 0.0%
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Footnotes to Commodity Mutual Funds'Implied Position
Note: Based on December 2011 Assets of $47.7 billion
1 Implied weight is calculated from the weights in the Dow-Jones UBS and S&P GScommodity indexes. Each is weighted according to the assets of commodity mutualfunds tied to the underlying index. For example, over 90 percent of commoditymutual funds assets are linked to the Dow-Jones UBSCI and less than 10 percentto the S&P GSCI; each of which has a weight, respectively, of 29.9% and 14.7% onWTI oil. That implies that an average weight for commodity mutual funds of 16.2%as of December 2011.
2 Implied dollar position is the corresponding weight multiplied by total assets incommodity mutual funds as of December 2011 ($47.7 billion). For example,
commodity mutual funds have an implied weight of 16.2% of their $47.7 billion inassets invested in WTI crude oil, for an estimated dollar position of $7.7 billion.
Sources: Dow Jones-UBS, Barclays Capital
20
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Annex
Some literature on impact of commodity investment
Figures 8 through 12, and Figure 14 from paper
8-global size of flows, 9-rebalancing and oil, 10-examples and #s of commodity investment products,11-index weights in two broad commodity indexes, 12-CPI ex FE versus S&P500 and commodity index, and14-weekly CMF flows since early 2009
Weekly regression results
21
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Commodity index-linked new flows donot affect returns
Stoll and Whaley 2010find that neither commodityindexlinked flows nor monthly rolls cause futuresprice levels to change across a wide variety of
commodity markets Irwin and Sanders 2011bfind little evidence that
index-linked investment affects commodity marketreturns or volatility
Using internal CFTC data, Aulerich, Irwin, andGarcia 2010find negligible evidence that dailyindex-linked investment affects commodity returnsin 12 agricultural markets
22
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Rebalancing impact on commodityprice volatility
Irwin and Sanders 2010suggests that commodityindex investors may reduce commodity pricevolatility because the indexes fixed weights force
them to sell into markets with the greatest priceincreases and buy into markets with falling prices
Aulerich, Irwin, and Garcia 2010shows that indexinvestors can dampen volatility in some markets
Brunetti, Byksahin, and Harris 2011 examinedaily swap dealer positions (a proxy for indexinvestment) and find no evidence that thesepositions contribute systematically to price changes
or volatility in the crude oil, natural gas, and corn 23
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Monthly rolls of positions do not causefutures price levels to change
Mou 2010and Frenk and Turbeville 2011 examine theperiod when index investors typically exit futurespositions and roll into new positions. They find that the
spread between prices for nearby and next-nearbywidens during the roll, but no persistent levels effect
Stoll and Whaley 2010find that monthly rolls do notcause futures price levels to change across a wide
variety of commodity markets Kastner 2010shows that United States Natural Gas (a
commodity ETF) has no significant effect during the timethe monthly roll occurs
24
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8: Investment Flow into Global
Commodity Markets by Sector, 12MSum
25
Billions of dollars, monthly, 20092011*
*Data to November 2011.
Source: Barclays Capital
$0
$5
$10
$15
$20
$25
$30
$35
2009 2010 2011
Agriculture
Base metals
Precious metals
Energy
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9: Oil Price Versus Futures EquivalentPosition of Commodity Index Traders
26
Daily, December 2007 to December 2008
Sources: Federal Reserve, U.S. Commodity Futures Trading Commission
300
320
340
360
380
400
420
0
20
40
60
80
100
120
140
160
12/3/2007 3/3/2008 6/3/2008 9/3/2008 12/3/2008
Price per barrel Number of contracts (thousands)
Futures equivalent(right scale)
Oil Price(left scale)
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10: Number of Commodity Exchange-Traded Products and Mutual Funds
27
1 Commodity mutual funds are mutual funds whose primary investment objective is to give investors broad exposure to commodities by benchmarking tocommodity indexes that are diversified across a wide array of commodities.2 Managed futures strategy mutual funds are those that seek to give investors exposure to commodities, interest rates, and exchange rates through derivativessuch as futures and swaps. To date, these funds have not been predominately invested in commodities, so are included in this table purely for completeness.Note: Number in parentheses denotes number of broad-based commodity ETFs or ETNs.Source: Morningstar
Commodity ETFs Commodity ETNs Commodity mutual funds1Managed futures strategy
mutual funds2
December 1, 2004 1 (0) 0 (0) 2 0
December 1, 2006 6 (2) 3 (2) 7 0
December 1, 2008 18 (3) 42 (6) 12 2
December 1, 2010 28 (4) 43 (7) 2313
September 30, 2011 34 (4) 61 (8) 30 20
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11: Commodity Index Weights, 2011
28
Note: Weights on tin andpalladium are zero in bothindexes.Sources: Dow Jones-UBS, Barclays Capital
Commodity S&P GSCI
Dow Jones-UBS
Commodity Index
WTIcrude 29.9% 14.7%
Brent crude 16.8% 0.0%
Gasoil 7.2% 0.0%
Heating oil 5.3% 3.6%
Corn 5.1% 7.0%
Unleaded gasoline 4.9% 3.5%
Copper 3.6% 7.5%
Wheat CBOT 3.4% 4.6%
Gold 3.4% 10.5%Natural gas 2.8% 11.2%
Soybean 2.7% 7.9%
Live cattle CME 2.5% 3.4%
Aluminium 2.4% 5.2%
Sugar 2.4% 3.3%
Lean hogs CME 1.4% 2.0%
Cotton 1.3% 2.0%
Coffee 1.1% 2.4%
Wheat (KBOT) 0.9% 0.0%Nickel 0.7% 2.3%
Silver 0.6% 3.3%
Zinc 0.6% 2.9%
Lead 0.5% 0.0%
Feeder cattle CME 0.4% 0.0%
Cocoa 0.3% 0.0%
Soybean oil 0.0% 2.9%
Tin 0.0% 0.0%
Palladium 0.0% 0.0%
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12: Commodity Index and S&P 500
index vs. CPI F&E Component
29
Dollars invested, monthly, 2002-2011*
*Data are as of December 2011Sources: Bloomberg, U.S. Bureau of Labor Statistics
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
$35,000
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Dow Jones-UBS Commodity Total Return Index
S&P 500 index (total return )
Consumer Price Index, food and
energy component
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14: Net New Cash Flow to CMFs and
Weekly Price Changes
30
Weekly, 2009-2011*
*Data as of December 2011
Sources: Investment Company Institute and Bloomberg (Dow Jones UBS Commodity Total Return Index )
-10%
0%
10%
20%
30%
40%
-$0.5
$0.0
$0.5
$1.0
$1.5
$2.0
2009 2010 2011
Billions Weekly percent change
Weekly net new cash flow(left scale)
Dow Jones-UBS Commodity TotalReturn Index (right scale)
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Weekly Contemporaneous Results
31
Equation 1 Equation 1 with S&P GSCI
, Intercept -0.00157
(0.00173)
-0.00217
(0.00243)
, Slope 0.2776**(0.1188)
0.3209**(0.1611)
R-squared 0.0195 0.0138
Adjusted R-squared 0.0171 0.0114
Durbin-Watson Statistic 2.002 1.996
Sample 1/12/2004 to 12/26/2011 1/12/2004 to 12/26/2011
*denotes statistical significance at the 10 percent level
** denotes statistical significance at the 5 percent level
*** denotes statistical significance at the 1 percent level
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Weekly VAR Resultsln(Pt) Ct/At-1
Intercept -0.00008
(0.0016)
0.0012**
(0.0005)
Coef on ln(Pt-1) 0.0016
(0.0502)
0.0189
(0.0149)
ln(Pt-2) -0.0530
(0.0503)
-0.0121
(0.0149)
ln(Pt-3) 0.0334(0.0500)
-0.0018(0.0148)
Coef on Ct-1/At-2 -0.0200
(0.1656)
0.2474***
(0.0490)
Ct-2/At-3 0.3049*
(0.1606)
0.3106***
(0.0475)
Ct-3/At-4 -0.1482
(0.1516)
0.2172***
(0.0448)R-squared 0.0125 0.5515
Adjusted R-squared -0.0021 0.5448
Sample 2/02/2004 12/26/2011 2/02/2004 12/26/2011
*denotes statistical significance at the 10 percent level
** denotes statistical significance at the 5 percent level
*** denotes statistical significance at the 1 percent level