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Does the choice of performance measure influence the evaluation of commodity investments?

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  • Auer, Benjamin R.

Abstract

In practice, a wide variety of performance measures is available to evaluate commodity investments. In this article, we show that the most popular of these metrics, i.e., the Sharpe ratio and 12 alternative reward-to-risk ratios based on drawdowns, partial moments and the Value at Risk, yield almost identical rank orderings across futures-based commodity investments in energy, precious metals, industrial metals, agriculture, and livestock. Especially for identifying the best and worst investment opportunities from a set of given alternatives, the choice of performance measure does not crucially influence investment decisions. Interestingly, our results are robust in several dimensions, namely, the dataset, the time period, the return calculation method and the performance measure parametrisation.

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  • Auer, Benjamin R., 2015. "Does the choice of performance measure influence the evaluation of commodity investments?," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 142-150.
    • Handle: RePEc:eee:finana:v:38:y:2015:i:c:p:142-150
    DOI: 10.1016/j.irfa.2014.10.003
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    Cited by:

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    2. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the time-varying dynamics of stock and commodity momentum returns," Finance Research Letters, Elsevier, vol. 46(PB).
    3. Hoang, Thi-Hong-Van & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange," Economic Modelling, Elsevier, vol. 50(C), pages 200-211.
    4. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    5. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    6. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    7. Noureddine Kouaissah & Sergio Ortobelli Lozza & Ikram Jebabli, 2022. "Portfolio Selection Using Multivariate Semiparametric Estimators and a Copula PCA-Based Approach," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 833-859, October.
    8. Anja Vinzelberg & Benjamin R. Auer, 2022. "Unprofitability of food market investments," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2887-2910, October.
    9. Korn, Olaf & Möller, Philipp M. & Schwehm, Christian, 2019. "Drawdown measures: Are they all the same?," CFR Working Papers 19-04, University of Cologne, Centre for Financial Research (CFR).
    10. Potrykus Marcin, 2018. "Comparison of Investment Performance Measures Using the Example of Selected Stock Exchanges," Financial Sciences. Nauki o Finansach, Sciendo, vol. 23(2), pages 30-46, June.
    11. Noureddine Kouaissah & Amin Hocine, 2021. "Forecasting systemic risk in portfolio selection: The role of technical trading rules," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 708-729, July.
    12. Selim baha Yildiz & Abdelbari El khamlichi, 2017. "The Performance Ranking of Emerging Markets Islamic Indices Using Risk Adjusted Performance Measures," Economics Bulletin, AccessEcon, vol. 37(1), pages 63-78.
    13. León, Angel & Moreno, Manuel, 2017. "One-sided performance measures under Gram-Charlier distributions," Journal of Banking & Finance, Elsevier, vol. 74(C), pages 38-50.
    14. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    15. Zhang, Hanxiong & Auer, Benjamin R. & Vortelinos, Dimitrios I., 2018. "Performance ranking (dis)similarities in commodity markets," Global Finance Journal, Elsevier, vol. 35(C), pages 115-137.
    16. Benjamin R. Auer, 2021. "Have trend-following signals in commodity futures markets become less reliable in recent years?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 533-553, December.
    17. Kouaissah, Noureddine, 2021. "Using multivariate stochastic dominance to enhance portfolio selection and warn of financial crises," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 480-493.
    18. Bedi, Prateek & Nashier, Tripti, 2020. "On the investment credentials of Bitcoin: A cross-currency perspective," Research in International Business and Finance, Elsevier, vol. 51(C).
    19. Batten, Jonathan A. & Lucey, Brian M. & Peat, Maurice, 2016. "Gold and silver manipulation: What can be empirically verified?," Economic Modelling, Elsevier, vol. 56(C), pages 168-176.
    20. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.

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    More about this item

    Keywords

    Energy investment; Performance measurement; Rank correlation;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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