We look at the dynamic conditional correlations (DCCs) between oil, natural gas and other non-energy commodity futures markets, obtained from a DCC-GARCH model over the period 1998-2014. They are positive and display a sharp increase around year 2008 and a subsequent decrease. The DCCs between energy and metals are larger than the energy-agriculture ones. To understand how macroeconomic and financial factors, as well as speculative activity, influence them, we estimate an ARDL(1,1) model, adopting a pooled mean group (PMG) estimator. We observe that macroeconomic and financial variables are significantly correlated with the energy-agriculture and energy-metals DCCs. Speculative activity contributes to explain the energy-agriculture DCCs but not those of the energy-metals.
AlquistR.GervaisO. (2013). “The Role of Financial Speculation in Driving the Price of Crude Oil.” The Energy Journal34(3): 35-54. https://doi.Org/10.5547/01956574.34.3.3
2.
AruobaS.B.DieboldF.X.ScottiC. (2009). “Real-Time Measurement of Business Conditions.” Journal of Business and Economic Statistics27(4): 417-27. https://doi.org/10.1198/jbes.2009.07205
3.
BhardwajG.GortonG.RouwenhorstG. (2015). “Facts and Fantasies about Commodity Futures Ten Years Later.” NBER Working Paper No. 21243. https://doi.org/10.3386/w21243
4.
BaruníkJ.KocendaE.VáchaL. (2015). “Volatility Spillovers Across Petroleum Markets.” The Energy Journal36(3). https://doi.org/10.5547/01956574.36.3.jbar
5.
BasakS.PavlovaA. (2016). “A Model of Financialization of Commodities.” Journal of Finance71(4): 1511-1556. https://doi.org/10.1111/jofi.12408
6.
BattenJ.A.CinerC.LuceyB.M. (2010). “The macroeconomic determinants of volatility in precious metals markets.” Resources Policy35(2): 65-71. https://doi.org/10.1016/j.resourpol.2009.12.002
7.
BauwensL.LaurentS.RomboutsJ.V.K.(2006). “Multivariate GARCH models: A survey.” Journal of Applied Econometrics21: 79-109 https://doi.org/10.1002/jae.842
8.
BessembinderH.ChanK. (1992). “Time-varying risk premia and forecastable returns in futures markets.” Journal of Financial Economics32(2): 169-193. https://doi.org/10.1016/0304-405X(92)90017-R
9.
BloomN., (2014). “Fluctuations in uncertainty.” Journal of Economic Perspectives28: 153-176. https://doi.org/10.1257/jep.28.2.153
10.
Büyüksahin B., M.A. Robe (2014). “Speculators, Commodities and Cross-Market Linkages.” Journal of International Money and Finance42: 38-70. https://doi.org/10.1016/j.jimonfin.2013.08.004
11.
BunnD.ChevallierJ.Le PenY.SeviB.(2017). “Fundamental and Financial Influences on the Co-movement of Oil and Gas Prices.” The Energy Journal38(2): 201-228. https://doi.org/10.5547/01956574.38.2.dbun
12.
CaporinM.McAleerM. (2012). “Do we really need both BEKK and DCC? A tale of two multivariate GARCH models.” Journal of Economic Surveys26(4): 736-751. https://doi.org/10.1111/j.1467-6419.2011.00683.x
13.
ChangT.H.SuH.M. (2010). “The substitutive effect of biofuels on fossil fuel in the lower and higher crude oil price periods.” Energy35: 2807-2813. https://doi.org/10.1016/j.energy.2010.03.006
14.
CharlotP.MarimoutouV. (2014). “On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree.” Energy Economics44: 456-467. https://doi.org/10.1016/j.eneco.2014.04.021
15.
ChengI.H.XiongW. (2014). “Financialization of commodity markets.” Annual Review of Financial Economics6: 419-441. https://doi.org/10.1146/annurev-financial-110613-034432
16.
CheungC.S.MiuP. (2010). “Diversification benefits of commodity futures.” Journal of International Financial Markets, Institutions &Money20(5): 451-474. https://doi.org/10.1016/j.intfin.2010.06.003
17.
ChoiK.HammoudehS. (2010). “Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment.” Energy Policy38: 4388-4399. https://doi.org/10.1016/j.enpol.2010.03.067
18.
ChowG.JacquierE.KritzmanM.LowryK. (1999). “Optimal portfolios in good and bad times.” Financial Analyst Journal55(3): 65-73. https://doi.org/10.2469/faj.v55.n3.2273
19.
ColacitoR.EngleR.F.GhyselsE. (2011). “A Component Model for Dynamic Correlations.” Journal of Econometrics164: 45-59. https://doi.org/10.1016/j.jeconom.2011.02.013
20.
DaskalakiC.SkiadopoulosG. (2011). “Should investors include commodities in their portfolios after all? New evidence.” Journal of Banking &Finance35(10): 2606-2626. https://doi.org/10.1016/j.jbankfin.2011.02.022
21.
DeatonA.LaroqueG. (1992). “On the Behaviour of Commodity Prices.” Review of Economic Studies59(1): 1-23. https://doi.org/10.2307/2297923
22.
DeatonA.LaroqueG. (1996). “Competitive Storage and Commodity Price Dynamics.” Journal of Political Economy104(5): 896-923. https://doi.org/10.1086/262046
23.
DickeyD. A.FullerW.A. (1979). “Distribution of the estimators for autoregressive time series with a Unit Root.” Journal of the American Statistical Association74: 427-431.
24.
DuX.YuC.L.HayesD.J. (2011). “Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis.” Energy Economics33: 497-503. https://doi.org/10.1016/j.eneco.2010.12.015
25.
DuX.McPhailL.L. (2012). “Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets.” The Energy Journal33(2): 171-194. https://doi.org/10.5547/01956574.33.2.8
26.
EngleR.F., (2002). “Dynamic conditional correlation - a simple class of multivariate GARCH models.” Journal of Business and Economic Statistics20(3): 339-350. https://doi.org/10.1198/073500102288618487
27.
EngleR.F., (2009). Anticipating correlations. A new paradigm for risk management. Princeton University Press.
28.
EngleR.GhyselsE.SohnB. (2013). “On the Economic Sources of Stock Market Volatility.” The Review of Economics and Statistics95: 776-797. https://doi.org/10.1162/REST_a_00300
EwingB.TMalikF. (2013). “Volatility transmission between gold and oil futures under structural breaks.” International Review of Economics &Finance25: 113-121. https://doi.org/10.1016/j.iref.2012.06.008
31.
FAO (2008). “Soaring food prices: facts, perspectives, impacts and actions required.” Proceedings of the high-level conference on world food security, Rome.
32.
FrankelJ.A. (2006). “The Effect of Monetary Policy on Real Commodity Prices” in Campbell J. Y. (Ed.), Asset Prices and Monetary Policy, University of Chicago Press, 291-333.
33.
GardebroekC.HernandezM.A. (2013). “Do energy prices stimulate food price volatility? Examining volatility transmission between US oil, ethanol and corn markets.” Energy Economics40: 119-129. https://doi.org/10.1016/j.eneco.2013.06.013
34.
GortonG.RouwenhorstK. (2006). “Facts and fantasies about commodity futures.” Financial Analyst Journal62: 47-68. https://doi.org/10.2469/faj.v62.n2.4083
35.
HammoudehS.YuanY. (2008). “Metal volatility in presence of oil and interest rate shocks.” Energy Economics30:606620. https://doi.org/10.1016/j.eneco.2007.09.004
36.
HartleyP. R.Medlock IIIK.B., (2014). “The Relationship between Crude Oil and Natural Gas Prices: The Role of the Exchange Rate.” The Energy Journal35(2): 25-44. https://doi.org/10.5547/01956574.35.2.2
37.
HongH.YogoM. (2012). “What does futures market interest tell us about the macroeconomy and asset prices?” Journal of Financial Economics105: 473-490. https://doi.org/10.1016/j.jfineco.2012.04.005
38.
IrwinS.H.SandersD.R. (2012). “Testing the masters hypothesis in commodity futures markets.” Energy Economics34: 256-269. https://doi.org/10.1016/j.eneco.2011.10.008
JoëtsM.MignonV.RazafindrabecR. (2017). “Does the volatility of commodity prices reflect macroeconomic uncertainty?” Energy Economics68: 313-326. https://doi.org/10.1016/j.eneco.2017.09.017
41.
KaraliB.RamirezO.A. (2014). “Macro determinants of volatility and volatility spillover in energy markets.” Energy Economics46: 413-421. https://doi.org/10.1016/j.eneco.2014.06.004
42.
KilianL.MurphyD.P. (2014). “The Role of Inventories and Speculative Trading in the Global Market for Crude Oil.” Journal of Applied Econometrics29: 454-478. https://doi.org/10.1002/jae.2322
43.
LevinA.LinC.-F.ChuC.-S. J.. (2002). “Unit root tests in panel data: Asymptotic and finite-sample properties.” Journal of Econometrics108: 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7
44.
ManeraM.NicoliniM.VignatiI. (2013). “Financial speculation in energy and agriculture futures markets: a multivariate GARCH approach.” The Energy Journal34(3): 55-81. https://doi.org/10.5547/01956574.34.3.4
45.
ManeraM.NicoliniM.VignatiI. (2016). “Modelling futures price volatility in energy markets: Is there a role for financial speculation?” Energy Economics53: 220-229. https://doi.org/10.1016/j.eneco.2014.07.001
46.
MensiW.HammoudehS.NguyenD.K.YoonS.M. (2014). “Dynamic spillovers among major energy and cereal commodity prices.” Energy Economics43: 225-243. https://doi.org/10.1016/j.eneco.2014.03.004
47.
PaganA., (1984). “Econometric Issues in the Analysis of Regressions with Generated Regressors.” International Economic Review25: 221-247. https://doi.org/10.2307/2648877
PesaranM.H.ShinY. (1999). “An autoregressive distributed lag modeling approach to cointegration analysis.” In: Strom, S. (Ed.), Econometrics and Economic Theory in the Twentieth Century. Cambridge University Press, New York, NY. https://doi.org/10.1017/CCOL521633230.011
50.
PesaranM. H.ShinY.SmithR. (1999). “Pooled mean group estimation of dynamic heterogeneous panels.” Journal of the American Statistical Association94(446): 621-634. https://doi.org/10.1080/01621459.1999.10474156
51.
SandersD.R.IrwinS.H. (2011). “The impact of index funds in commodity futures markets: A systems approach.” The Journal of Alternative Investments14: 40-49. https://doi.org/10.3905/jai.2011.14.1.040
52.
SerraT., (2011). “Volatility spillovers between food and energy markets: A semiparametric approach.” Energy Economics33: 1155-1164. https://doi.org/10.1016/j.eneco.2011.04.003
53.
SilvennoinenA.ThorpS. (2013). “Financialization, crisis and commodity correlation dynamics.” Journal of International Financial Markets, Institutions and Money24: 42-65. https://doi.org/10.1016/j.intfin.2012.11.007
54.
SørensenC., (2002). “Modelling seasonality in agricultural commodity futures.” Journal of Futures Markets22(5): 393426. https://doi.org/10.1002/fut.10017
55.
SuenagaH.SmithA. (2011). “Volatility dynamics and seasonality in energy prices: Implications for crack-spread price risk.” The Energy Journal32(3): 27-58. https://doi.org/10.5547/ISSN0195-6574-EJ-Vol32-No3-2
56.
TangK.XiongW. (2012). “Index investment and the financialization of commodities.” Financial Analyst Journal68(6): 54-74. https://doi.org/10.2469/faj.v68.n6.5
57.
Trujillo-BarreraA.MalloryM.GarciaP. (2012). “Volatility spillovers in the U.S. crude oil, ethanol, and corn futures markets.” Journal of Agricultural and Resource Economics73(2): 247-262.
58.
WorkingH. (1960). “Speculation on hedging markets.” Food Research Institute Studies1: 185-220.
59.
WuH.LiS. (2013). “Volatility spillovers in China’s crude oil, corn and fuel ethanol markets.” Energy Policy62: 878-886. https://doi.org/10.1016/j.enpol.2013.07.026
60.
WuF.GuanZ.MyersR.J. (2011). “Volatility spillover effects and cross hedging in corn and crude oil futures.” Journal of Futures Markets31(11): 1052-1075. https://doi.org/10.1002/fut.20499
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