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The anatomy of portfolio skewness and kurtosis

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Abstract

This article re-examines portfolio higher moments, skewness and kurtosis, to see whether this information can be used to improve portfolio construction and to diagnose any mis-specification of models for portfolio returns. In common with most discussion of quantitative portfolio risk, we assume a linear factor model framework, and some empirical calculations using data from the components of the Dow Jones Industrial Index are carried out. The major insight that we glean from this exercise is that a well-diversified portfolio of skewed stocks can have a symmetric distribution unless we pay some attention to the third moment structure. These ideas are likely to have some potential application to fund of fund construction and the matching of bespoke portfolios to the risk attributes of high-net worth investors.

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  • Anthony D Hall & Stephen E Satchell, 2013. "The anatomy of portfolio skewness and kurtosis," Published Paper Series 2013-7, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    • Handle: RePEc:uts:ppaper:2013-7
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    File URL: https://link.springer.com/article/10.1057/jam.2013.18
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    6. Campbell Harvey & John Liechty & Merrill Liechty & Peter Muller, 2010. "Portfolio selection with higher moments," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 469-485.
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    2. Gkillas, Konstantinos & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2022. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 398-406.
    3. Deng Xiong & Liu Yanli, 2018. "A High-Moment Trapezoidal Fuzzy Random Portfolio Model with Background Risk," Journal of Systems Science and Information, De Gruyter, vol. 6(1), pages 1-28, February.
    4. Emenike, Kalu O., 2010. "Modelling Stock Returns Volatility In Nigeria Using GARCH Models," MPRA Paper 22723, University Library of Munich, Germany.

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