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Portfolio selection: An extreme value approach

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  • DiTraglia, Francis J.
  • Gerlach, Jeffrey R.

Abstract

We show theoretically that lower tail dependence (χ), a measure of the probability that a portfolio will suffer large losses given that the market does, contains important information for risk-averse investors. We then estimate χ for a sample of DJIA stocks and show that it differs systematically from other risk measures including variance, semi-variance, skewness, kurtosis, beta, and coskewness. In out-of-sample tests, portfolios constructed to have low values of χ outperform the market index, the mean return of the stocks in our sample, and portfolios with high values of χ. Our results indicate that χ is conceptually important for risk-averse investors, differs substantially from other risk measures, and provides useful information for portfolio selection.

Suggested Citation

  • DiTraglia, Francis J. & Gerlach, Jeffrey R., 2013. "Portfolio selection: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 305-323.
  • Handle: RePEc:eee:jbfina:v:37:y:2013:i:2:p:305-323
    DOI: 10.1016/j.jbankfin.2012.08.022
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    3. Asgar Ali & K. N. Badhani, 2023. "Tail risk, beta anomaly, and demand for lottery: what explains cross-sectional variations in equity returns?," Empirical Economics, Springer, vol. 65(2), pages 775-804, August.
    4. Yong-Jun Liu & Wei-Guo Zhang, 2019. "Possibilistic Moment Models for Multi-period Portfolio Selection with Fuzzy Returns," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1657-1686, April.
    5. Lorne N. Switzer & Jun Wang & Seungho Lee, 2017. "Extreme risk and small investor behavior in developed markets," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 457-475, October.
    6. Salisu, Afees A. & Adediran, Idris & Omoke, Philip C. & Tchankam, Jean Paul, 2023. "Gold and tail risks," Resources Policy, Elsevier, vol. 80(C).
    7. Vohra, Suprita & Fabozzi, Frank J., 2019. "Effectiveness of developed and emerging market FX options in active currency risk management," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 130-146.
    8. Montshioa, Keitumetse & Muteba Mwamba, John Weirstrass & Bonga-Bonga, Lumengo, 2021. "Asset allocation in extreme market conditions: a comparative analysis between developed and emerging economies," MPRA Paper 106248, University Library of Munich, Germany.
    9. Rhee, S. Ghon & Wu, Feng (Harry), 2020. "Conditional extreme risk, black swan hedging, and asset prices," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 412-435.
    10. Mainik, Georg & Mitov, Georgi & Rüschendorf, Ludger, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 115-134.
    11. Long, Huaigang & Jiang, Yuexiang & Zhu, Yanjian, 2018. "Idiosyncratic tail risk and expected stock returns: Evidence from the Chinese stock markets," Finance Research Letters, Elsevier, vol. 24(C), pages 129-136.
    12. Georg Mainik & Georgi Mitov & Ludger Ruschendorf, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Papers 1505.04045, arXiv.org.
    13. De Luca Giovanni & Zuccolotto Paola, 2017. "A double clustering algorithm for financial time series based on extreme events," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 1-12, June.
    14. R. P. C. Leal & B. V. M. Mendes, 2013. "Assessing the effect of tail dependence in portfolio allocations," Applied Financial Economics, Taylor & Francis Journals, vol. 23(15), pages 1249-1256, August.
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    More about this item

    Keywords

    Portfolio selection; Extreme value theory; Tail dependence;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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