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The method of simulated quantiles

  • Dominicy, Yves
  • Veredas, David

We introduce the Method of Simulated Quantiles, or MSQ, an indirect inference method based on quantile matching that is useful for situations where the density function does not have a closed form and/or moments do not exist. Functions of theoretical quantiles, which depend on the parameters of the assumed probability law, are matched with the sample counterparts, which depend on the observations. Since the theoretical quantiles may not be available analytically, the optimization is based on simulations. We illustrate the method with the estimation of α-stable distributions. A thorough Monte Carlo study and an illustration to 22 financial indexes show the usefulness of MSQ.

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File URL: http://www.sciencedirect.com/science/article/pii/S0304407612001947
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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 172 (2013)
Issue (Month): 2 ()
Pages: 235-247

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Handle: RePEc:eee:econom:v:172:y:2013:i:2:p:235-247
DOI: 10.1016/j.jeconom.2012.08.010
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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