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Publication type
Journal article with impact factorPublication Year
2013Journal
Journal of EconometricsPublication Volume
172Publication Issue
2Publication Begin page
235Publication End page
247
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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 -stable distributions. A thorough Monte Carlo study and an illustration to 22 financial indexes show the usefulness of MSQ.Knowledge Domain/Industry
Accounting & Financeae974a485f413a2113503eed53cd6c53
10.1016/j.jeconom.2012.08.010