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Comparing and selecting performance measures for ranking assets

Author

Listed:
  • Massimiliano Caporin

    (University of Padua)

  • Francesco Lisi

    (University of Padua)

Abstract

Within an asset allocation framework, when the number of assets is larger than the sample dimension, mean-variance approaches cannot be used due to the limited number of degrees of freedom. In such a situation, performance measures could be used to rank assets, and then select a subset of them for further analysis. However, the financial economics literature proposes dozens of measures, and there is thus a problem: which measures should be considered? Some authors already discussed this topic. We extend the current literature by enlarging the set of analyzed measures and also by exploiting the possible dynamic evolution of rank correlations. Our analysis is mainly empirical, based on the S&P 1500 constituents, and includes an example of the optimal combination of performance measures for allocating an equity portfolio.

Suggested Citation

  • Massimiliano Caporin & Francesco Lisi, 2009. "Comparing and selecting performance measures for ranking assets," "Marco Fanno" Working Papers 0099, Dipartimento di Scienze Economiche "Marco Fanno".
    • Handle: RePEc:pad:wpaper:0099
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    Citations

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    Cited by:

    1. López, Raquel & Esparcia, Carlos, 2021. "Analysis of the performance of volatility-based trading strategies on scheduled news announcement days: An international equity market perspective," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 32-54.
    2. Marco Taboga, 2014. "The Riskiness of Corporate Bonds," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 693-713, June.
    3. Billio, Monica & Caporin, Massimiliano & Costola, Michele, 2015. "Backward/forward optimal combination of performance measures for equity screening," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 63-83.
    4. 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.
    5. León, Ángel & Moreno, Manuel, 2015. "Lower Partial Moments under Gram Charlier Distribution: Performance Measures and Efficient Frontiers," QM&ET Working Papers 15-3, University of Alicante, D. Quantitative Methods and Economic Theory.
    6. Mohammad Reza Tavakoli Baghdadabad & Paskalis Glabadanidis, 2013. "Average Drawdown Risk and Capital Asset Pricing," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-21.
    7. Anand, Abhinav & Li, Tiantian & Kurosaki, Tetsuo & Kim, Young Shin, 2016. "Foster–Hart optimal portfolios," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 117-130.
    8. 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).

    More about this item

    Keywords

    performance measurement; rank correlations; selecting performance measures; comparing performance measures; combining performance measures.;
    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
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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