The method of simulated quantiles
AbstractWe 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 Î±-stable distributions. A thorough Monte Carlo study and an illustration to 22 financial indexes show the usefulness of MSQ.
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Bibliographic InfoPaper provided by ULB -- Universite Libre de Bruxelles in its series ULB Institutional Repository with number 2013/136280.
Date of creation: 2013
Date of revision:
Publication status: Published in: Journal of econometrics (2013) v.172 n° 2,p.235-247
Other versions of this item:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
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