This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Semiparametric Multivariate Density Estimation for Positive Data Using Copulas

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Taoufik Bouezmarni
Jeroen V.K. Rombouts () (IEA, HEC Montréal)

Additional information is available for the following registered author(s):

Abstract

In this paper we estimate density functions for positive multivariate data. We propose a semiparametric approach. The estimator combines gamma kernels or local linear kernels, also called boundary kernels, for the estimation of the marginal densities with semiparametric copulas to model the dependence. This semiparametric approach is robust both to the well known boundary bias problem and the curse of dimensionality problem. We derive the mean integrated squared error properties, including the rate of convergence, the uniform strong consistency and the asymptotic normality. A simulation study investigates the finite sample performance of the estimator. We find that univariate least squares cross validation, to choose the bandwidth for the estimation of the marginal densities, works well and that the estimator we propose performs very well also for data with unbounded support. Applications in the field of finance are provided.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www2.hec.ca/iea/cahiers/2007/iea0708_jrombouts.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by HEC Montréal, Institut d'économie appliquée in its series Cahiers de recherche with number 07-08.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 32 pages
Date of creation: Jul 2007
Date of revision:
Handle: RePEc:iea:carech:0708

Contact details of provider:
Postal: Institut d'économie appliquée HEC Montréal 3000, Chemin de la Côte-Sainte-Catherine Montréal, Québec H3T 2A7
Phone: (514) 340-6463
Fax: (514) 340-6469
Email:
Web page: http://www2.hec.ca/iea/
More information through EDIRC

Order Information:
Postal: Institut d'économie appliquée HEC Montréal 3000, Chemin de la Côte-Sainte-Catherine Montréal, Québec H3T 2A7
Email:

For technical questions regarding this item, or to correct its listing, contact: (Patricia Power).

Related research
Keywords: Asymptotic properties; asymmetric kernels; boundary bias; copula; curse of dimension; least squares cross validation.;

Other versions of this item:

This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Lejeune, Michel & Sarda, Pascal, 1992. "Smooth estimators of distribution and density functions," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 457-471, November. [Downloadable!] (restricted)
  2. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée. [Downloadable!]
    Other versions:
  3. Cho, Myeong-Hyeon, 1998. "Ownership structure, investment, and the corporate value: an empirical analysis," Journal of Financial Economics, Elsevier, vol. 47(1), pages 103-121, January. [Downloadable!] (restricted)
  4. H. G. Müller & U. Stadtmüller, 1999. "Multivariate boundary kernels and a continuous least squares principle," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 439-458. [Downloadable!] (restricted)
  5. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March. [Downloadable!] (restricted)
  6. Sancetta, Alessio & Satchell, Stephen, 2004. "The Bernstein Copula And Its Applications To Modeling And Approximations Of Multivariate Distributions," Econometric Theory, Cambridge University Press, vol. 20(03), pages 535-562, June. [Downloadable!]
  7. Song Chen, 2000. "Probability Density Function Estimation Using Gamma Kernels," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 471-480, September. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? All top Economics journals are listed on RePEc.

This page was last updated on 2009-11-26.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.