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The multivariate Edgeworth-Sargan density

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  • Javier Perote

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Abstract

The Edgeworth-Sargan density has been shown capable of capturing empirical regularities of financial data (thick tails and asymmetries). When compared to other densities used in applied finance, it has the advantage of its analytical simplicity, and the ability to improve data fits by adding more parameters in a natural way. This paper develops an explicit form for the multivariate Edgeworth-Sargan density and compare its performance to the multivariate Student’s t. The comparison is carried out with daily financial observations, spanning 25 years of data for several financial variables that include stock markets indices and interest and exchange rates for several countries. Copyright Springer-Verlag Berlin/Heidelberg 2004

Suggested Citation

  • Javier Perote, 2004. "The multivariate Edgeworth-Sargan density," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(1), pages 77-96, April.
  • Handle: RePEc:spr:specre:v:6:y:2004:i:1:p:77-96
    DOI: 10.1007/s10108-003-0075-x
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    File URL: http://hdl.handle.net/10.1007/s10108-003-0075-x
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    Citations

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    Cited by:

    1. Trino-Manuel Niguez & Javier Perote, 2004. "Forecasting the density of asset returns," STICERD - Econometrics Paper Series 479, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. repec:spr:comaot:v:23:y:2017:i:3:d:10.1007_s10588-016-9231-3 is not listed on IDEAS
    3. Withers, Christopher S. & Nadarajah, Saralees, 2014. "The dual multivariate Charlier and Edgeworth expansions," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 76-85.
    4. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2008. "Multivariate Gram-Charlier Densities," MPRA Paper 29073, University Library of Munich, Germany.
    5. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "Semi-nonparametric VaR forecasts for hedge funds during the recent crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 330-343.
    6. Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2017. "Measuring firm size distribution with semi-nonparametric densities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 35-47.
    7. repec:eee:ememar:v:31:y:2017:i:c:p:96-115 is not listed on IDEAS
    8. Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2017. "Multivariate approximations to portfolio return distribution," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 347-361, September.
    9. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364.
    10. Del Brio, Esther B. & Perote, Javier, 2012. "Gram–Charlier densities: Maximum likelihood versus the method of moments," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 531-537.
    11. Juan Arismendi, 2014. "A Multi-Asset Option Approximation for General Stochastic Processes," ICMA Centre Discussion Papers in Finance icma-dp2014-03, Henley Business School, Reading University.

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