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The rank effect for commodities

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  • Ricardo T. Fernholz
  • Christoffer Koch

Abstract

We uncover a large and significant low-minus-high rank effect for commodities across two centuries. There is nothing anomalous about this anomaly, nor is it clear how it can be arbitraged away. Using nonparametric econometric methods, we demonstrate that such a rank effect is a necessary consequence of a stationary relative asset price distribution. We confirm this prediction using daily commodity futures prices and show that a portfolio consisting of lower-ranked, lower-priced commodities yields 23% higher annual returns than a portfolio consisting of higher-ranked, higher-priced commodities. These excess returns have a Sharpe ratio nearly twice as high as the U.S. stock market yet are uncorrelated with market risk. In contrast to the extensive literature on asset pricing factors and anomalies, our results are structural and rely on minimal and realistic assumptions for the long-run properties of relative asset prices.

Suggested Citation

  • Ricardo T. Fernholz & Christoffer Koch, 2016. "The rank effect for commodities," Working Papers 1607, Federal Reserve Bank of Dallas.
    • Handle: RePEc:fip:feddwp:1607
    DOI: 10.24149/wp1607
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    References listed on IDEAS

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    1. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    2. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
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    5. van Dijk, Mathijs A., 2011. "Is size dead? A review of the size effect in equity returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3263-3274.
    6. Nielsen, Lars Tyge, 1999. "Pricing and Hedging of Derivative Securities," OUP Catalogue, Oxford University Press, number 9780198776192.
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    More about this item

    Keywords

    Commodity prices; nonparametric methods; asset pricing anomalies; asset pricing factors; efficient markets;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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