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Multivariate extremality measure

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  • Laniado Rodas, Henry

Abstract

We propose a new multivariate order based on a concept that we will call extremality". Given a unit vector, the extremality allows to measure the "farness" of a point with respect to a data cloud or to a distribution in the vector direction. We establish the most relevant properties of this measure and provide the theoretical basis for its nonparametric estimation. We include two applications in Finance: a multivariate Value at Risk (VaR) with level sets constructed through extremality and a portfolio selection strategy based on the order induced by extremality.

Suggested Citation

  • Laniado Rodas, Henry, 2010. "Multivariate extremality measure," DES - Working Papers. Statistics and Econometrics. WS ws101908, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:ws101908
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    Citations

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    Cited by:

    1. Ra'ul Torres & Rosa E. Lillo & Henry Laniado, 2015. "A Directional Multivariate Value at Risk," Papers 1502.00908, arXiv.org.
    2. Pellerey, Franco & Laniado Rodas, Henry, 2012. "Portfolio selection through and extremality stochastic order," DES - Working Papers. Statistics and Econometrics. WS ws121812, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Torres, Raúl & Lillo, Rosa E. & Laniado, Henry, 2015. "A directional multivariate value at risk," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 111-123.
    4. Michele, Carlo de & Laniado Rodas, Henry, 2016. "Directional multivariate extremes in environmental phenomena," DES - Working Papers. Statistics and Econometrics. WS 23419, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Beck, Nicholas & Di Bernardino, Elena & Mailhot, Mélina, 2021. "Semi-parametric estimation of multivariate extreme expectiles," Journal of Multivariate Analysis, Elsevier, vol. 184(C).

    More about this item

    Keywords

    Extremality;

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