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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

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File URL: http://hdl.handle.net/10.1007/s10108-003-0075-x
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Bibliographic Info

Article provided by Springer in its journal Spanish Economic Review.

Volume (Year): 6 (2004)
Issue (Month): 1 (April)
Pages: 77-96

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Handle: RePEc:spr:specre:v:6:y:2004:i:1:p:77-96

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Related research

Keywords: Multivariate densities; Edgeworth-Sargan and Student’s t distributions; financial data; conditional heteroskedasticity;

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Cited by:
  1. 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.
  2. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2008. "Multivariate Gram-Charlier Densities," MPRA Paper 29073, University Library of Munich, Germany.
  3. 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.
  4. Withers, Christopher S. & Nadarajah, Saralees, 2014. "The dual multivariate Charlier and Edgeworth expansions," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 76-85.
  5. 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.

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