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Kurtosis-based risk parity: methodology and portfolio effects

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  • M. D. Braga
  • C. R. Nava
  • M. G. Zoia

Abstract

In this paper, a risk parity strategy based on portfolio kurtosis as reference measure is introduced. This strategy allocates the asset weights in a portfolio in a manner that allows an homogeneous distribution of responsibility for portfolio returns' huge dispersion, since portfolio kurtosis puts more weight on extreme outcomes than standard deviation does. Therefore, the goal of the strategy is not the minimization of kurtosis, but rather its ‘fair diversification’ among assets. An original closed-form expression for portfolio kurtosis is devised to set up the optimization problem for this type of risk parity strategy. The latter is then compared with the one based on standard deviation by using data from a global equity investment universe and implementing an out-of-sample analysis. The kurtosis-based risk parity strategy has interesting portfolio effects, with lights and shadows. It outperforms the traditional risk parity according to main risk-adjusted performance measures. In terms of asset allocation solutions, it provides more unbalanced and more erratic portfolio weights (albeit without excluding any component) in comparison to those pertaining the traditional risk parity strategy.

Suggested Citation

  • M. D. Braga & C. R. Nava & M. G. Zoia, 2023. "Kurtosis-based risk parity: methodology and portfolio effects," Quantitative Finance, Taylor & Francis Journals, vol. 23(3), pages 453-469, March.
    • Handle: RePEc:taf:quantf:v:23:y:2023:i:3:p:453-469
    DOI: 10.1080/14697688.2022.2145988
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    1. Gordon Tang & Daniel Choi, 1998. "Impact of diversification on the distribution of stock returns: International evidence," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 22(2), pages 119-127, June.
    2. T. Roncalli & G. Weisang, 2016. "Risk parity portfolios with risk factors," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 377-388, March.
    3. Michaud, Richard O. & Michaud, Robert O., 2008. "Efficient Asset Management: A Practical Guide to Stock Portfolio Optimization and Asset Allocation," OUP Catalogue, Oxford University Press, edition 2, number 9780195331912, Decembrie.
    4. Boudt, Kris & Lu, Wanbo & Peeters, Benedict, 2015. "Higher order comoments of multifactor models and asset allocation," Finance Research Letters, Elsevier, vol. 13(C), pages 225-233.
    5. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    6. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," Journal of Banking & Finance, Elsevier, vol. 126(C).
    7. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    8. Maroua Mhiri & Jean-Luc Prigent, 2010. "International Portfolio Optimization with Higher Moments," Post-Print hal-03679712, HAL.
    9. Eugene F. Fama, 1963. "Mandelbrot and the Stable Paretian Hypothesis," The Journal of Business, University of Chicago Press, vol. 36, pages 420-420.
    10. Magnus, J.R. & Neudecker, H., 1985. "Matrix differential calculus with applications to simple, Hadamard, and Kronecker products," Other publications TiSEM 1b2f1740-bfd1-4ea5-986c-9, Tilburg University, School of Economics and Management.
    11. Kris Boudt & Dries Cornilly & Tim Verdonck, 2020. "A Coskewness Shrinkage Approach for Estimating the Skewness of Linear Combinations of Random Variables [International Asset Allocation with Regime Shifts]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 1-23.
    12. repec:dau:papers:123456789/4688 is not listed on IDEAS
    13. You, Leyuan & Daigler, Robert T., 2010. "Is international diversification really beneficial?," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 163-173, January.
    14. Lionel Martellini & Volker Ziemann, 2010. "Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection," The Review of Financial Studies, Society for Financial Studies, vol. 23(4), pages 1467-1502, April.
    15. Scott, Robert C & Horvath, Philip A, 1980. "On the Direction of Preference for Moments of Higher Order Than the Variance," Journal of Finance, American Finance Association, vol. 35(4), pages 915-919, September.
    16. Zoia, Maria Grazia & Biffi, Paola & Nicolussi, Federica, 2018. "Value at risk and expected shortfall based on Gram-Charlier-like expansions," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 92-104.
    17. Chunhachinda, Pornchai & Dandapani, Krishnan & Hamid, Shahid & Prakash, Arun J., 1997. "Portfolio selection and skewness: Evidence from international stock markets," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 143-167, February.
    18. Best, Michael J & Grauer, Robert R, 1991. "On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results," The Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 315-342.
    19. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
    20. Xi Bai & Katya Scheinberg & Reha Tutuncu, 2016. "Least-squares approach to risk parity in portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 357-376, March.
    21. Helmut Mausser & Oleksandr Romanko, 2018. "Long-only equal risk contribution portfolios for CVaR under discrete distributions," Quantitative Finance, Taylor & Francis Journals, vol. 18(11), pages 1927-1945, November.
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    Cited by:

    1. Gilles Boevi Koumou, 2023. "Risk budgeting using a generalized diversity index," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 443-458, October.
    2. Braga, Maria Debora & Nava, Consuelo Rubina & Zoia, Maria Grazia, 2023. "Kurtosis-based vs volatility-based asset allocation strategies: Do they share the same properties? A first empirical investigation," Finance Research Letters, Elsevier, vol. 54(C).

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