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The determinants of extreme commodity prices

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  • Karlygash Kurlbayeva
  • Samuel Malone

Abstract

Fat-tailed commodity price innovations are well-documented in the literature and long recognized as disruptive for consumers and producers, yet little is known about what factors drive such extreme events. Utilizing a wide range of factors from the economics and finance literature and quantile regression techniques, we shed light on this issue. Our models explain more variation in extreme than in median price innovations. Common global financial and demand factors account for a greater proportion of extreme daily spot price variations than do commodity-specific factors such as basis and open interest. Financialization of commodity markets, via significant and increasing co-variation of extreme spot price innovations with US equity market and trade-weighted US dollar returns, appears to be a major driver of extreme events in the 2000-2009 period.

Suggested Citation

  • Karlygash Kurlbayeva & Samuel Malone, 2012. "The determinants of extreme commodity prices," OxCarre Working Papers 096, Oxford Centre for the Analysis of Resource Rich Economies, University of Oxford.
  • Handle: RePEc:oxf:oxcrwp:096
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    References listed on IDEAS

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    1. Angus Deaton & Guy Laroque, 1992. "On the Behaviour of Commodity Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(1), pages 1-23.
    2. Eugene F. Fama & Kenneth R. French, 2015. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 4, pages 79-102, World Scientific Publishing Co. Pte. Ltd..
    3. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    4. Ke Tang & Wei Xiong, 2012. "Index Investment and the Financialization of Commodities," Financial Analysts Journal, Taylor & Francis Journals, vol. 68(6), pages 54-74, November.
    5. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    6. Victor Chernozhukov & Iván Fernández-Val & Alfred Galichon, 2010. "Rearranging Edgeworth–Cornish–Fisher expansions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 42(2), pages 419-435, February.
    7. Gourinchas, Pierre-Olivier & Tornell, Aaron, 2004. "Exchange rate puzzles and distorted beliefs," Journal of International Economics, Elsevier, vol. 64(2), pages 303-333, December.
    8. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    9. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    10. Mr. Shaun K. Roache, 2008. "Commodities and the Market Price of Risk," IMF Working Papers 2008/221, International Monetary Fund.
    11. Len Umantsev & Victor Chernozhukov, 2001. "Conditional value-at-risk: Aspects of modeling and estimation," Empirical Economics, Springer, vol. 26(1), pages 271-292.
    12. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2013. "The Fundamentals of Commodity Futures Returns," Review of Finance, European Finance Association, vol. 17(1), pages 35-105.
    13. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    14. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    15. Michelle L. Barnes & Anthony W. Hughes, 2002. "A quantile regression analysis of the cross section of stock market returns," Working Papers 02-2, Federal Reserve Bank of Boston.
    16. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    17. Meligkotsidou, Loukia & Vrontos, Ioannis D. & Vrontos, Spyridon D., 2009. "Quantile regression analysis of hedge fund strategies," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 264-279, March.
    18. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
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    Cited by:

    1. Karol Szafranek, 2015. "Financialisation of the commodity markets. Conclusions from the VARX DCC GARCH," EcoMod2015 8554, EcoMod.

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    More about this item

    Keywords

    commodities price returns; extreme dependence; quantile regressions;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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