The Dynamics of Volatility and Correlations in the Commodity Space

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This paper examines several dynamics of volatility and correlations in the commodity space. Specifically, the paper discusses:
The fiction of normality and volatility dynamics
Catalysts for volatility shifts
Examining correlation patterns

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The Dynamics of Volatility and Correlations in the Commodity Space

  1. 1. © 2014 CME Group. All rights reserved. The Dynamics of Volatility and Correlations in the Commodity Space Blu Putnam, Chief Economist 1 July 2014 1© 2014 CME Group. All rights reserved.
  2. 2. © 2014 CME Group. All rights reserved. Investment Advice is Neither Given nor Intended The research views expressed herein are those of the author and do not necessarily represent the views of CME Group or its affiliates. All examples in this presentation are hypothetical interpretations of situations and are used for explanation purposes only. This report and the information herein should not be considered investment advice or the results of actual market experience. 2© 2014 CME Group. All rights reserved.
  3. 3. © 2014 CME Group. All rights reserved. Risks of Trading Futures and Swaps Neither futures trading nor swaps trading are suitable for all investors, and each involves the risk of loss. Swaps trading should only be undertaken by investors who are Eligible Contract Participants (ECPs) within the meaning of Section 1a(18) of the Commodity Exchange Act. Futures and swaps each are leveraged investments and, because only a percentage of a contract’s value is required to trade, it is possible to lose more than the amount of money deposited for either a futures or swaps position. Therefore, traders should only use funds that they can afford to lose without affecting their lifestyles and only a portion of those funds should be devoted to any one trade because traders cannot expect to profit on every trade. 3© 2014 CME Group. All rights reserved.
  4. 4. © 2014 CME Group. All rights reserved. Additional Disclosures The Globe Logo, CME®, Chicago Mercantile Exchange®, and Globex® are trademarks of Chicago Mercantile Exchange Inc. CBOT® and the Chicago Board of Trade® are trademarks of the Board of Trade of the City of Chicago, Inc. NYMEX, New York Mercantile Exchange, and ClearPort are trademarks of New York Mercantile Exchange, Inc. COMEX is a trademark of Commodity Exchange, Inc. CME Group is a trademark of CME Group Inc. All other trademarks are the property of their respective owners. The information within this presentation has been compiled by CME Group for general purposes only. CME Group assumes no responsibility for any errors or omissions. Although every attempt has been made to ensure the accuracy of the information within this presentation, CME Group assumes no responsibility for any errors or omissions. All matters pertaining to rules and specifications herein are made subject to and are superseded by official CME, CBOT and NYMEX rules. Current rules should be consulted in all cases concerning contract specifications. 4© 2014 CME Group. All rights reserved.
  5. 5. © 2014 CME Group. All rights reserved. CME Group Trading Volume Growth: Catalysts & Scenarios 1 Fiction of Normality and Volatility Dynamics 2 Catalysts for Volatility Shifts 3 Examining Correlation Patterns 5© 2014 CME Group. All rights reserved.
  6. 6. © 2014 CME Group. All rights reserved. The Fiction of Normality “There is no such thing as a normal period of history. Normality is a fiction of economic textbooks.” -- Joan Violet Robinson (1903-1983) 6© 2014 CME Group. All rights reserved. Source: Duke University Press, Durham, NC (The Provocative Joan Robinson: Making of a Cambridge Economist, 2009).
  7. 7. © 2014 CME Group. All rights reserved. Explanations and Definitions for Volatility and Price Momentum Charts to Follow Chart Construction – The red dotted line is an indicator measuring the evolving pattern of volatility. The solid black line is an indicator measuring the direction and strength of the evolving price momentum. Volatility – We used an estimate of the annualized standard deviation of daily price percent changes to represent volatility, expressed as a percent. Our volatility indicator is calculated from a smoothed exponential decay process. Price Momentum – We use an estimate of the annualized price momentum based on daily percent changes and a smoothed exponential decay process. The indicator suggests the current trend expressed as an annual percentage rate related to the current price momentum. 7© 2014 CME Group. All rights reserved.
  8. 8. © 2014 CME Group. All rights reserved. S&P and US Treasury Volatility Patterns are Typical – Declining to Lower Levels 8© 2014 CME Group. All rights reserved. -6% -4% -2% 0% 2% 4% 6% 8% 10% 12% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: BloombergProfessionalforpricedata. CMEEconomicsforvolatilityandpricemomentumindicatorcalculations. US10-YearTreasuries(Price): VolatilityandPriceMomentumComparisons -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: Bloomberg Professionalfor price data. CME Economics forvolatilityandprice momentum indicator calculations. USS&P500: Volatility andPriceMomentum Comparisons
  9. 9. © 2014 CME Group. All rights reserved. The Same Declining Volatility Patterns are Occurring in Major Currency Markets 9© 2014 CME Group. All rights reserved. -10% -5% 0% 5% 10% 15% 20% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: BloombergProfessionalforpricedata. CMEEconomicsforvolatilityandpricemomentum indicatorcalculations. Euro(USDperEUR): VolatilityandPriceMomentumComparisons -15% -10% -5% 0% 5% 10% 15% 20% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: BloombergProfessionalforpricedata. CMEEconomicsforvolatilityandpricemomentumindicatorcalculations. JapaneseYen(USDperJPY): VolatilityandPriceMomentumComparisons
  10. 10. © 2014 CME Group. All rights reserved. Volatility Patterns Across Almost All Products are Declining To Historical Lows 10© 2014 CME Group. All rights reserved. 2003-2006 9/2008 - 3/2009 2012-2013 2014 YTD US Treasury 10-Year 5.81% 12.21% 5.12% 4.17% S&P500 Index 12.24% 54.74% 11.71% 10.85% Euro (USD per EUR) 9.41% 18.43% 7.71% 4.96% Yen (USD per JPY) 8.62% 20.10% 9.92% 6.46% WTI Crude Oil 34.58% 91.80% 22.26% 15.27% Brent Crude Oil 32.18% 71.62% 20.03% 13.23% Brent-WTI Spread Index 22.48% 55.88% 14.14% 11.25% Natural Gas (US) 92.52% 59.19% 41.20% 112.67% Gold 17.59% 36.68% 18.19% 12.85% Copper 27.04% 61.83% 19.24% 14.10% Corn 25.69% 54.73% 27.74% 20.49% Wheat 28.00% 42.14% 22.45% 17.06% Soybeans 30.89% 67.17% 27.29% 26.06% Volatility (Annualized Standard Deviation) by Selected Periods Shading shows period with the lowest volatility. Source: Price data from Bloomberg Professional, Calculations by CME Economics.
  11. 11. © 2014 CME Group. All rights reserved. Declining Volatility is not necessarily the same as weak trading volumes Primary Source of Declining Volatility: Zero rates from the US Fed, ECB, and Bank of Japan, along with the perceived market put, that these big central banks will do whatever it takes to avoid a future financial disaster, creates a relatively lower risk environment compared to the pre-2008 period. Weak Trading Volumes in Certain Markets and Sectors: The extensive increase in regulation, especially in the banking sector, disrupted the previous model of bank proprietary trading. The pendulum is swinging to asset managers and hedge funds, but the transition period involves less trading and less capital allocated to risk trading. Specific to US stock markets, algorithmic and other computerized trading systems may have seen their previous profits competed away by arrival of many more firms getting into the fray -- higher returns attracted more players and then more players eliminated the higher returns – resulting in less trading volume in stock markets. 11© 2014 CME Group. All rights reserved.
  12. 12. © 2014 CME Group. All rights reserved. Scenarios for Fed Decision to Raise Rates and Possible Bond Market Reactions Scenario #1 – US labor markets continue to improve while core inflation only creeps very slowly higher. Fed raises target federal funds rate in Q2/2015. Since no inflation pressure, the yield curve flattens. (60%) Scenario #2 – US labor markets continue to improve and core inflation rises above 2% year over year rate, and inflation expectations appear to rise toward 2.5% to 3% for a year ahead. Fed raises target federal funds rate in Q2/2015. With some inflation pressure, the Fed is perceived as being behind the game, and the yield curve rises in parallel across the maturity spectrum. (30%) Scenario #3 – US economy hits a rough patch and Fed stays on hold. US Treasuries may rally and yields move lower. (10%) 12© 2014 CME Group. All rights reserved.
  13. 13. © 2014 CME Group. All rights reserved. US Unemployment Rate Projected to Decrease to 5.5% by Mid-2015 0% 3% 6% 9% 12% Percentage Source: St. Louis Federal Reserve Bank FRED Database (UNRATE) US Unemployment Rate The last time the unemployment rate went above 10% (1982), it took 5 years to get back below 6%. -- the same time path the economy is currently following. 13© 2014 CME Group. All rights reserved.
  14. 14. © 2014 CME Group. All rights reserved. Inflation Path is Key to Bond Reaction to Any Fed Rate Rises 0% 1% 2% 3% 4% 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 Year-over-YearPercentChange Source: Data from St. Louis Federal Reserve, Projections by CME Economics. US Core Inflation Scenarios 14© 2014 CME Group. All rights reserved.
  15. 15. © 2014 CME Group. All rights reserved. Scenarios for Equity Markets Scenario #1 – US economy continues to improve, but with no inflation pressure, no pricing power for corporation, so earnings growth decelerates. S&P500 suffers a 10% correction but ends up on the year. (60%) Scenario #2 – M&A activity and solid US economy propel S&P500 Index to new highs, up 10% or more on the year, give or take. (30%) Scenario #3 – US economy hits a rough patch, (possibly due to international causes) and equities swoon, for a 20% bear market downturn. (10%) 15© 2014 CME Group. All rights reserved.
  16. 16. © 2014 CME Group. All rights reserved. Equity Markets & Earning Expectations Dynamics -- Growth Rate is Decelerating $0 $200 $400 $600 $800 $1,000 $1,200 $1,400 $1,600 $1,800 $2,000 2003 2005 2007 2009 2011 2013 2015 US$Billions,AnnualRate Source: St. Louis Federal Reserve (CP). US Corporate Profits (After Tax, GDP Basis) 16© 2014 CME Group. All rights reserved.
  17. 17. © 2014 CME Group. All rights reserved. Scenarios for New Dynamics in FX Depend on Central Bank Divergence Scenario #1 – US and UK economies perform well enough to lead to expectations of rate rises in 2015, while Euro-Zone and Japan hit economic rough patches. USD and GBP outperform EUR and JPY. (60%) Scenario #2 – Creeping inflation in the US and UK versus deflation fears in Europe and Japan magnify country differences. (30%) Scenario #3 – US, UK, Euro- Zone, and Japan all disappoint on economic growth. Zero rates remain in all countries. No trends, not much volatility. (10%) 17© 2014 CME Group. All rights reserved.
  18. 18. © 2014 CME Group. All rights reserved. UK & US improving Growth, Japan and Euro-Zone Still Struggling -2% 0% 2% 4% 2011 2012 2013 2014 AnnualAverageRealGDPGrowthRate Source: Data from Bloomberg Professional, Projections from CME Economics. Real GDP Scenarios UK US Japan Euro-Zone 18© 2014 CME Group. All rights reserved.
  19. 19. © 2014 CME Group. All rights reserved. US Fed Ends Quantitative Easing in Q4/2014, Rates the Next Decision $0 $1 $2 $3 $4 US$Trillions Source: Federal Reserve Bank of St. Louis FRED Database Federal Reserve Assets Other MBS UST 10+ Years US Treasuries Less Than 10-Years 19© 2014 CME Group. All rights reserved.
  20. 20. © 2014 CME Group. All rights reserved. Bank of Japan Remains Committed to Massive Asset Purchases 0 50,000 100,000 150,000 200,000 250,000 300,000 1997 1999 2001 2003 2005 2007 2009 2011 2013 BillionsofJapaneseYen Source: Bank of Japan (www.boj.or.jp) Bank of Japan Assets Japanese Government Securities Loans Other 20© 2014 CME Group. All rights reserved.
  21. 21. © 2014 CME Group. All rights reserved. Alone Among the Major Central Banks – ECB Balance Sheet is Shrinking 0 500 1,000 1,500 2,000 2,500 3,000 3,500 1999 2001 2003 2005 2007 2009 2011 2013 EuroBillions Source: European Central Bank Monthly Bulletins European Central Bank Assets 21© 2014 CME Group. All rights reserved.
  22. 22. © 2014 CME Group. All rights reserved. Japanese yen fell 20% with Abe’s Election and has Hardly Moved Since 75 80 85 90 95 100 105 110 JPYperUSD Source: Bloomberg Professional (JPY) Japanese Yen 22© 2014 CME Group. All rights reserved.
  23. 23. © 2014 CME Group. All rights reserved. Euro has Gained Ground Since the Debt Crisis Eased, but May Have Hit its Cap 1.20 1.25 1.30 1.35 1.40 USDperEUR Source: Bloomberg Professional (EUR) Euro 23© 2014 CME Group. All rights reserved.
  24. 24. © 2014 CME Group. All rights reserved. Scenarios for Oil and Natural Gas Diverge Scenario #1 – Natural gas prices develop a slow yet definitive upward trend based on rising consumption and deceleration of production boom, while crude oil bounces around in a narrow range. (60%) Scenario #2 – No definitive trends in either natural gas or crude oil develop. (20%) Scenario #3 – More unexpected negative surprises from geo-politics or a total shutdown of Iraqi oil sends crude oil surging higher – toward $150 per barrel. (20%) 24© 2014 CME Group. All rights reserved.
  25. 25. © 2014 CME Group. All rights reserved. Crude Oil Price and Volatility Momentum 25© 2014 CME Group. All rights reserved. -60% -40% -20% 0% 20% 40% 60% 80% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: Bloomberg Professional for price data. CME Economics for volatility and price momentum indicator calculations. WTI Crude Oil: Volatility and Price Momentum Comparisons
  26. 26. © 2014 CME Group. All rights reserved. Natural Gas Price and Volatility Momentum 26© 2014 CME Group. All rights reserved. -100% -50% 0% 50% 100% 150% 200% 250% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: Bloomberg Professional for price data. CME Economics for volatility and price momentum indicator calculations. US Natural Gas: Volatility and Price Momentum Comparisons
  27. 27. © 2014 CME Group. All rights reserved. More Petroleum Exports and Less Imports Have Helped US Reconnect to Markets 0 100,000,000 200,000,000 300,000,000 400,000,000 500,000,000 1981 1985 1989 1993 1997 2001 2005 2009 2013 BarrelsofPetroleumProductsPerMonth Source: US Energy Information Administration, Sourcekeys MTTIMUS1 (Imports) and MTTEXUS1 (Exports). US Oil Petroleum Products: Imports and Exports Imports Exports 27© 2014 CME Group. All rights reserved.
  28. 28. © 2014 CME Group. All rights reserved. Rising Consumption, Deceleration of Production = New Nat Gas Price Dynamics 0 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000 30,000,000 35,000,000 1949 1957 1965 1973 1981 1989 1997 2005 2013 MMcf Source: US Energy Information Administration, Sourcekeys N9140US2 (Consumption) and N9010US2 (Withdrawals). US Natural Gas Production & Consumption Production Consumption 28© 2014 CME Group. All rights reserved.
  29. 29. © 2014 CME Group. All rights reserved. Scenarios for Metals Depend on Inflation and Global Growth Scenario #1 – No meaningful inflation pressure in the major countries and no financial disasters. US economy improves enough for Fed to tighten. Gold has another price break toward $900 - $1000 per ounce. (60%) Scenario #2 – Some US inflation pressure develops and Fed is seen as behind the game. Gold rises to $1400+. (30%) Scenario #3 – US and other economies hit a rough patch and fears of deflation return. Gold has another price break toward $600 - $900 per ounce. (10%) 29© 2014 CME Group. All rights reserved.
  30. 30. © 2014 CME Group. All rights reserved. Gold Price and Volatility Momentum 30© 2014 CME Group. All rights reserved. -15% -10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: Bloomberg Professional for price data. CME Economics for volatility and price momentum indicator calculations. Gold: Volatility and Price Momentum Comparisons
  31. 31. © 2014 CME Group. All rights reserved. Copper Price and Volatility Momentum 31© 2014 CME Group. All rights reserved. -100% -50% 0% 50% 100% 150% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: Bloomberg Professional for price data. CME Economics for volatility and price momentum indicator calculations. Copper: Volatility and Price Momentum Comparisons
  32. 32. © 2014 CME Group. All rights reserved. Gold Has Become Range Bound without Inflation Fears or Financial Panic 1000 1200 1400 1600 1800 2000 US$SpotPriceofGold Source: Bloomberg Professional (GOLDS) Gold 32© 2014 CME Group. All rights reserved.
  33. 33. © 2014 CME Group. All rights reserved. Scenarios for Agriculture are Weather Dependent and Not Mutually Exclusive Scenario #1 – El Niño returns. Too much rain in Brazil and Argentina. Drought in India and Australia. Rain in the US corn belt. Storms in California in latter stages of El Niño. Benign US hurricane season. Soybeans lead other ag prices higher. (60%) Scenario #2 – Drought in California and Texas/Oklahoma continues through summer, pushing livestock prices higher, as well as US food inflation. (80%) Scenario #3 – CA, TX, and OK drought ends. No El Niño. But hurricane activity exceeds expectations. (20%) 33© 2014 CME Group. All rights reserved.
  34. 34. © 2014 CME Group. All rights reserved. Corn Price and Volatility Momentum 34© 2014 CME Group. All rights reserved. -30% -20% -10% 0% 10% 20% 30% 40% 50% 60% 2002 2005 2008 2011 2014 Volatilityindicatorisbasedonasmoothedannualized standarddeviation,andthepricemomentumindicatoris basedonsmoothedannualreturns. Source: Bloomberg Professional for price data. CME Economics for volatility and price momentum indicator calculations. Corn: Volatility and Price Momentum Comparisons
  35. 35. © 2014 CME Group. All rights reserved. Warming Trends in Equatorial Pacific Has Increased Fears of an El Niño. Source: National Oceanic and Atmospheric Administration (NOAA). 35© 2014 CME Group. All rights reserved.
  36. 36. © 2014 CME Group. All rights reserved. Some Possible El Niño Effects Scenario #1 – By 2015, warmer waters in the Equatorial Pacific may drift northward and bring severe winter weather to California, ending drought but not without potentially high costs from storm damage. Scenario #2 – Australia and India may experience higher probability of drought. More rain in Brazil and Argentina. Scenario #3 – Milder winters in southern Canada and US, fewer hurricanes for the US, among other things. 36© 2014 CME Group. All rights reserved.
  37. 37. © 2014 CME Group. All rights reserved. US Drought in California, and Texas / Oklahoma like to Raise Food Prices Source: University of Nebraska, US Drought Monitor. 37© 2014 CME Group. All rights reserved.
  38. 38. © 2014 CME Group. All rights reserved. Final Thoughts: Summary of Global Catalysts and Scenarios Scenario #1 – Lower US unemployment triggers Fed rate decision, equity market uncertainty, differential FX rate patterns, among other effects. (60%) Scenario #2 – US and UK inflation start to creep higher which further drives the Fed and BoE toward rate rises, while the ECB and BoJ continue to worry about low growth and potential deflation. (30%) Scenario #3 – China slows more than expected, US economy hits a rough patch, (or a major geo-political event hits global growth), such that equities swoon and Fed postpones rate hikes. (10%) 38© 2014 CME Group. All rights reserved.
  39. 39. © 2014 CME Group. All rights reserved. Selected Notes on Energy Correlation Dynamics #1 – Oil’s correlation to the S&P500 rose with the start of the US production boom, and has declined as the infrastructure has caught up with the boom and re-linked US oil to the rest of the world. #2 – WTI crude oil and US Henry Hub natural gas dance to totally different drummers. Nevertheless, over time, the differential price of a BTU of energy will drive investment and consumption to the less expensive sector, and then narrow the BTU price gap. #3 – Oil and gold have occasionally shown a positive correlation, but no inflation trends, energy production booms, and geo-politics appear to be eliminating what correlation is left. 39© 2014 CME Group. All rights reserved.
  40. 40. © 2014 CME Group. All rights reserved. Oil was Correlated to the S&P500 only During the Early Stages of Production Boom Before the Infrastructure Development Caught Up 40© 2014 CME Group. All rights reserved. -1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 2004 2006 2008 2010 2012 2014 Rolling1-YearCorrelationCoefficient forDailyPricePercentChanges Source: Daily Price Data from Bloomberg Profressional. Rolling window correlation calculations by CME Economics. US S&P500 - WTI Crude Oil: Evolving Correlation Pattern
  41. 41. © 2014 CME Group. All rights reserved. WTI Crude Oil and US Natural Gas Dance to Totally Different Market Forces 41© 2014 CME Group. All rights reserved. -1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 2004 2006 2008 2010 2012 2014 Rolling1-YearCorrelationCoefficient forDailyPricePercentChanges Source: Daily Price Data from Bloomberg Profressional. Rolling window correlation calculations by CME Economics. US Natural Gas - WTI Crude Oil: Evolving Correlation Pattern
  42. 42. © 2014 CME Group. All rights reserved. Oil and Gold Were Modestly Correlated in 2006-2008, but No More 42© 2014 CME Group. All rights reserved. -1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 2004 2006 2008 2010 2012 2014 Rolling1-YearCorrelationCoefficient forDailyPricePercentChanges Source: Daily Price Data from Bloomberg Profressional. Rolling window correlation calculations by CME Economics. Gold - WTI Crude Oil: Evolving Correlation Pattern
  43. 43. © 2014 CME Group. All rights reserved. Selected Notes on Other Correlation Dynamics #1 – Copper’s correlation to the S&P500 has been diminishing as China’s growth rate has decelerated, reducing the demand growth for copper. #2– Agricultural products are correlated to each other, but not to much of anything else since weather, not economic conditions dominates price patterns. #3 – Copper, oil and gold have had the least stable correlation patterns to equities. Multiple drivers, from inflation to China, to production booms have sometimes coordinated but are now pulling in different directions. 43© 2014 CME Group. All rights reserved.
  44. 44. © 2014 CME Group. All rights reserved. Copper was Increasingly Linked to Equities until the China Growth Deceleration Started 44© 2014 CME Group. All rights reserved. -1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 2004 2006 2008 2010 2012 2014 Rolling1-YearCorrelationCoefficient forDailyPricePercentChanges Source: Daily Price Data from Bloomberg Profressional. Rolling window correlation calculations by CME Economics. Copper - US S&P500: Evolving Correlation Pattern
  45. 45. © 2014 CME Group. All rights reserved. In the Agriculture Sector, Corn and Soybeans Remain Linked 45© 2014 CME Group. All rights reserved. -1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 2004 2006 2008 2010 2012 2014 Rolling1-YearCorrelationCoefficient forDailyPricePercentChanges Source: Daily Price Data from Bloomberg Profressional. Rolling window correlation calculations by CME Economics. Corn - Soybeans: Evolving Correlation Pattern
  46. 46. © 2014 CME Group. All rights reserved. Copper, Gold, and Oil have had the Least Stable Correlation versus the S&P500 46© 2014 CME Group. All rights reserved. -0.50 -0.25 0.00 0.25 0.50 WTI Oil Natural Gas Gold Copper Corn Wheat Soy-beans Correlation Coefficients: Red Dotted = 2014-YTD, Black = 2012-2013. Prices from Bloomberg Professional, Calculations by CME Economics. Correlations vs US S&P500: 2012-13 vs 2014-YTD 2014 YTD 2012-2013
  47. 47. © 2014 CME Group. All rights reserved. Thank you 47© 2014 CME Group. All rights reserved.
  48. 48. © 2014 CME Group. All rights reserved. Acknowledgements 48© 2014 CME Group. All rights reserved. Valuable assistance has been provided by the “Macroeconomics and Trading Volume” CME Group Talent Exchange Team. Blu Putnam, Chief Economist &Team Sponsor: Team Members: Samantha Azzarello, Jesy Beeson, James Brady, Martin Jones, William Gallagher, Chris Harrison, Molly Pluciennik.

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