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Efficient and robust estimation for financial returns: an approach based on q-entropy


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  • Davide Ferrari


  • Sandra Paterlini



We consider a new robust parametric estimation procedure, which minimizes an empirical version of the Havrda-Charv_at-Tsallis entropy. The resulting estimator adapts according to the discrepancy between the data and the assumed model by tuning a single constant q, which controls the trade-o_ between robustness and e_ciency. The method is applied to expected re- turn and volatility estimation of _nancial asset returns under multivariate normality. Theoretical properties, ease of implementability and empirical re- sults on simulated and _nancial data make it a valid alternative to classic robust estimators and semi-parametric minimum divergence methods based on kernel smoothing

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Paper provided by University of Modena and Reggio E., Faculty of Economics "Marco Biagi" in its series Department of Economics with number 0623.

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Length: pages 38
Date of creation: Feb 2010
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Handle: RePEc:mod:depeco:0623

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Keywords: q-entropy; robust estimation; power-divergence; _nancial returns;

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