IDEAS home Printed from https://ideas.repec.org/p/cqe/wpaper/6317.html
   My bibliography  Save this paper

Examining the Common Dynamics of Commodity Futures Prices

Author

Listed:
  • Christian Gross

Abstract

We investigate the extent and dynamic nature of co-movement in daily futures prices of 18 non-energy commodities over the period 1994-2016. Our analysis provides evidence that co-movement between individual commodities and between commodities and outside financial markets varies strongly over time and that economic events play a key role in shaping the dynamics of co-movement. Our main findings suggest a steady rise in the co-movement of commodity returns between 2004 and 2010, with clear peaks during the period of global financial turmoil, but a steep decline in co-movement after 2013. We also find that overall connectedness of commodity futures markets to shocks in financial markets shows an increasing trend after 2004. Using several risk measures we show that financial investors' risk aversion affects the systematic component of commodity futures returns.

Suggested Citation

  • Christian Gross, 2017. "Examining the Common Dynamics of Commodity Futures Prices," CQE Working Papers 6317, Center for Quantitative Economics (CQE), University of Muenster.
  • Handle: RePEc:cqe:wpaper:6317
    as

    Download full text from publisher

    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/cqe_wp_63_2017.pdf
    File Function: Version of July 2017
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cornelis Gardebroek & Manuel A. Hernandez & Miguel Robles, 2016. "Market interdependence and volatility transmission among major crops," Agricultural Economics, International Association of Agricultural Economists, vol. 47(2), pages 141-155, March.
    2. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    3. Hirshleifer, David, 1990. "Hedging Pressure and Futures Price Movements in a General Equilibrium Model," Econometrica, Econometric Society, vol. 58(2), pages 411-428, March.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Jian Yang & David A. Bessler & David J. Leatham, 2001. "Asset storability and price discovery in commodity futures markets: A new look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 279-300, March.
    7. Baffes, John & Haniotis, Tassos, 2010. "Placing the 2006/08 commodity price boom into perspective," Policy Research Working Paper Series 5371, The World Bank.
    8. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    9. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    10. Gerlach, Stefan & Schulz, Alexander & Wolff, Guntram B., 2010. "Banking and sovereign risk in the euro area," Discussion Paper Series 1: Economic Studies 2010,09, Deutsche Bundesbank.
    11. Bessler, Wolfgang & Wolff, Dominik, 2015. "Do commodities add value in multi-asset portfolios? An out-of-sample analysis for different investment strategies," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 1-20.
    12. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    13. Pindyck, Robert S & Rotemberg, Julio J, 1990. "The Excess Co-movement of Commodity Prices," Economic Journal, Royal Economic Society, vol. 100(403), pages 1173-1189, December.
    14. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
    15. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    16. Vansteenkiste, Isabel, 2009. "How important are common factors in driving non-fuel commodity prices? A dynamic factor analysis," Working Paper Series 1072, European Central Bank.
    17. Yin, Libo & Han, Liyan, 2015. "Co-movements in commodity prices: Global, sectoral and commodity-specific factors," Economics Letters, Elsevier, vol. 126(C), pages 96-100.
    18. Ing-Haw Cheng & Andrei Kirilenko & Wei Xiong, 2015. "Convective Risk Flows in Commodity Futures Markets," Review of Finance, European Finance Association, vol. 19(5), pages 1733-1781.
    19. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    20. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    21. Jeffrey A. Frankel, 2008. "The Effect of Monetary Policy on Real Commodity Prices," NBER Chapters, in: Asset Prices and Monetary Policy, pages 291-333, National Bureau of Economic Research, Inc.
    22. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    23. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    24. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    25. Alois Geyer & Stephan Kossmeier & Stefan Pichler, 2004. "Measuring Systematic Risk in EMU Government Yield Spreads," Review of Finance, European Finance Association, vol. 8(2), pages 171-197.
    26. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    27. Irwin, Scott H. & Sanders, Dwight R. & Merrin, Robert P., 2009. "Devil or Angel? The Role of Speculation in the Recent Commodity Price Boom (and Bust)," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(2), pages 377-391, August.
    28. West, Kenneth D. & Wong, Ka-Fu, 2014. "A factor model for co-movements of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 289-309.
    29. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
    30. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    31. Beckmann, Joscha & Czudaj, Robert, 2014. "Volatility transmission in agricultural futures markets," Economic Modelling, Elsevier, vol. 36(C), pages 541-546.
    32. Alois Geyer & Stephan Kossmeier & Stefan Pichler, 2004. "Measuring Systematic Risk in EMU Government Yield Spreads," Review of Finance, Springer, vol. 8(2), pages 171-197.
    33. Daskalaki, Charoula & Skiadopoulos, George, 2011. "Should investors include commodities in their portfolios after all? New evidence," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2606-2626, October.
    34. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    35. Adams, Zeno & Glueck, Thorsten, 2014. "Financialization in Commodity Markets: A Passing Trend or the New Normal?," Working Papers on Finance 1413, University of St. Gallen, School of Finance, revised Aug 2015.
    36. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rehman, Mobeen Ur & Zeitun, Rami & Mardani, Abbas & Vo, Xuan Vinh & Eraslan, Veysel, 2022. "Asymmetric pass through of energy commodities to US sectoral returns," Resources Policy, Elsevier, vol. 76(C).
    2. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amar, Amine Ben & Goutte, Stéphane & Isleimeyyeh, Mohammad & Benkraiem, Ramzi, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    2. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.
    3. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    4. Duc Huynh, Toan Luu & Burggraf, Tobias & Nasir, Muhammad Ali, 2020. "Financialisation of natural resources & instability caused by risk transfer in commodity markets," Resources Policy, Elsevier, vol. 66(C).
    5. Liu, Lu & Zhang, Xiang, 2019. "Financialization and commodity excess spillovers," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 195-216.
    6. Chen, Peng & He, Limin & Yang, Xuan, 2021. "On interdependence structure of China's commodity market," Resources Policy, Elsevier, vol. 74(C).
    7. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    8. Huifu Nong, 2024. "Connectedness and risk transmission of China’s stock and currency markets with global commodities," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-24, February.
    9. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    10. Bakas, Dimitrios & Triantafyllou, Athanasios, 2018. "The impact of uncertainty shocks on the volatility of commodity prices," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 96-111.
    11. Abricha, Amal & Ben Amar, Amine & Bellalah, Makram, 2024. "Commodity futures markets under stress and stress-free periods: Further insights from a quantile connectedness approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 229-246.
    12. Grosche, Stephanie & Heckelei, Thomas, 2014. "Directional Volatility Spillovers between Agricultural, Crude Oil, Real Estate and other Financial Markets," Discussion Papers 166079, University of Bonn, Institute for Food and Resource Economics.
    13. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).
    14. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2015. "Does the euro area macroeconomy affect global commodity prices? Evidence from a SVAR approach," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 485-503.
    15. Hachicha, Néjib & Ben Amar, Amine & Ben Slimane, Ikrame & Bellalah, Makram & Prigent, Jean-Luc, 2022. "Dynamic connectedness and optimal hedging strategy among commodities and financial indices," International Review of Financial Analysis, Elsevier, vol. 83(C).
    16. Dahl, Roy Endré & Jonsson, Erlendur, 2018. "Volatility spillover in seafood markets," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 44-59.
    17. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    18. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    19. Chatziantoniou, Ioannis & Filippidis, Michail & Filis, George & Gabauer, David, 2021. "A closer look into the global determinants of oil price volatility," Energy Economics, Elsevier, vol. 95(C).
    20. Zhang, Dayong & Broadstock, David C., 2020. "Global financial crisis and rising connectedness in the international commodity markets," International Review of Financial Analysis, Elsevier, vol. 68(C).

    More about this item

    Keywords

    Commodity futures markets; connectedness; co-movement; financialization; common factors;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F30 - International Economics - - International Finance - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cqe:wpaper:6317. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Susanne Deckwitz (email available below). General contact details of provider: https://edirc.repec.org/data/cqmuede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.