Commodity Price Movements and Financialization : What We Know and What We Don't
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Transcript of Commodity Price Movements and Financialization : What We Know and What We Don't
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Commodity Price Movements and Financialization: What We
Know and What We Don'tJames D. Hamilton
University of California at San Diego
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What is “financialization”?
• Financial investors buying commodity futures– S&P Goldman Sachs Index– Dow Jones UBS Commodity Index
• Take long position in near futures contract• Sell contract and take new position in next
contract near expiry
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Solid line: Oil price. Dashed line: Long positions in oil futurescontracts of commodity index funds as inferred using the methodology of Masters (2008). Source: Singleton (2011).
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Monthly price of West Texas Intermediate ($/barrel) and city gate price of natural gas (in $/1000 cubic feet times 6). Data source: EIA.
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Price of crude oil and natural gas
wti nat gas*6
Both WTI and n gas are in DJ and GS
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Monthly price of West Texas Intermediate ($/barrel) and London spotprice of rhodium ($/ounce divided by 30). Data source: EIA and Kitco.
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Price of crude oil and rhodium
wti Rhodium/30
There is no futures market in rhodium
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Relation between crude oil price and Masters’ estimate of CIT subsequently broke down
Source: Hamilton and Wu, International Economic Review, forthcoming.
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Masters’ imputed CIT for oil
• CFTC Supplemental Commitment of Traders estimates CIT for 12 agricultural commodities
• Masters assumed all reported CIT was either following GS index or DJ index
• GS does not include soybean oil• Given known weights of DJ for crude oil
and soybean oil, Masters inferred holdings of crude oil for DJ funds
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• Likewise, GS includes KC wheat whereas DJ does not
• From SCOT reported CIT for KC wheat, Masters inferred total crude oil futures contracts held by GS-based funds
• GS also includes feeder cattle and DJ does not
• This gives second estimate of GS crude oil• Masters' imputed CIT for crude oil is the
sum of his estimates for DJ and GS
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Green line is based on holdings of soybean oil, feeder cattle, and KC wheat. Blue is price of crude oil
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• Actually, method does not require finding commodities held in only one fund
• Given known weights of both funds, observed SCOT for any two agricultural commodities gives two equations in two unknowns with which could calculate an imputed sum of DJ and GS crude oil holdings
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Estimates of GS and DJ holdings of crude oil contracts imputedUsing Masters’ method from soybean oil and one other commodity
Source: Hamilton and Wu, International Economic Review, forthcoming.
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• CFTC also has direct estimates (“Index Investment Data”) of crude oil CIT (quarterly since 2007, monthly since 2010:M6)
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Number of crude oil futures contracts held by index investment funds as inferredfrom CFTC estimates of index fund positions in soybean oil, KC wheat, and feeder cattle (dashed) and direct CFTC estimates of crude oil (solid). Source: Irwin and Sanders, Energy Economics, 2012.
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Oil price and net number of long index con-tracts
oil price oil contracts
Oil prices and CIT oil positions based on Index Investment Data
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Natural gas price and net number of long index contracts
gas price gas contracts
Natural gas prices and CIT gas positions based on Index Investment Data
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• Masters (2009):– "Buying pressure from Index Speculators
overwhelmed selling pressure from producers and the result was skyrocketing commodity prices."
• Claim involves two links:– 1) increased volume on the buy side
drives up the price of futures contract– 2) higher futures prices produce
increase in spot prices
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1) Could increase volume on buy side increase futures price?
Answer: yes, if counterparties require higher expected returns in compensation for taking on more nondiversifiable risk
(Hamilton and Wu, Journal of International Money and Finance, 2014; International Economic Review, forthcoming)
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• Easily testable: if CIT volume leads to compensation to counterparties, should help predict excess returns on futures contracts
• Empirical evidence that it does not: – Brunetti, et. al. (2011)– Sanders and Irwin (2011a,b)– Stoll and Whaley (2010)– Alquist and Gervais (2011)– Irwin and Sanders (2012)– Buyuksahin and Harris (2011)– Hamilton and Wu (forthcoming)
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Tests of whether notional CIT exposure in given commodity predicts weekly returns
(2006-2012)
Source: Hamilton and Wu, International Economic Review, forthcoming.
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demand
supply
P0
P2
Δ inventories
2) Could higher futures pricesproduce increase in spot prices?
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r = -0.23
Actual inventory changes and predicted changes if price change over 12 Months was due solely to speculation and supply and demand elasticities = 0.2.Source: Knittel and Pindyck (2014)
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• Conclusion: “financialization” could not explain long-run movements in relative commodity prices
• However, “speculation” accounts for 100% of high-frequency movements
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Hurricane Katrina (Aug 2005) had a large and permanent effect on oil production
Source:www.econbrowser.com/archives/2008/09/effects_of_hurr.html
Gulf of Mexico offshore crude oil production, 2005-2006 (1000 b/d)
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Hurricane Alex (June 2010)
• June 27: National Hurricane Center warns Alex could develop into Category 3 hurricane and damage oil production facilities in Gulf of Mexico
• June 29: clear there will be no effect on oil production (www.theoildrum.com/node/6671)
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WTI spot and NYMEX futures prices
Hurricane Alex (June 2010)
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Data source: EIA
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U.S. inventories of crude oil (excluding Strategic Petroleum Reserve):
• June 18, 2010-- 365.1 M• June 25, 2010-- 363.1 M• July 2, 2010-- 358.1 M
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P0
P2
ΔN2
Very short run: elasticities are very low and inventory changes are negligible
5-year assessments: elasticities are not zero
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World field production of crude oil up 2.3 mb/d since 2005 (= 3% increase)
World GDP increased 27.7% from 2005 to 2013
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Growing income would predict growing energy use (elasticity = 0.7)
Cross-section scatterplot (log scale) of energy use and GDP per capita for indicated years. Source: David Stern (http://www.sterndavidi.com/animation.gif)
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Projected demand growth based on growth of world GDP assuming constant price and
Stern’s income elasticity of 0.7
2013 shortfall = 13.5 mb/d (16% of production)
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Example: long-run price-elasticity of oil demand = 0.25
• Δ ln Qt = 0.25 Δ ln Pt • Δ ln Pt = 0.16/0.25 = 0.64• P2005 = $60/barrel (in 2014 $)• P2013 = 60 exp(0.64) = $114/barrel• If short-run price elasticity is less than
long-run, price should have been higher than $114 before coming down
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Why did global oil production stagnate?
Source: Steven Kopits (Douglas-Westwood, 2012)
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Norway oil production (1000 b/d) and % of world total
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• If resource depletion becomes a factor in pricing, producers need to know transversality conditions
• Very hard to calculate, rely on futures markets for price discovery, information assimilation
• If “financialization” impedes price discovery, could cause bigger problems
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Gulf of Mexico rig utilization rates and price of WTI
Source: Knittel and Pindyck (2014)
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Oil production of listed majors has declined even as capital spending surged
Source: Steven Kopits (Douglas-Westwood, 2014)
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Middle East production stagnated despite huge increased drilling effort
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oil production rig count
Data source: EIA (field production plus condensate) and Banker-Hughes.BH stopped counting Iran in Jan 2006, accounting for the drop at that date.
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But excessive preoccupation by academics with “financialization”, and not enough consensus on big
picture, may also impede price discovery
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