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

Davide Ferrari and Sandra Paterlini

Department of Economics from University of Modena and Reggio E., Faculty of Economics "Marco Biagi"

Abstract: 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

Keywords: q-entropy; robust estimation; power-divergence; _nancial returns (search for similar items in EconPapers)
JEL-codes: C13 G11 (search for similar items in EconPapers)
Pages: pages 38
Date: 2010-02
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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Working Paper: Efficient and robust estimation for financial returns: an approach based on q-entropy (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:mod:depeco:0623

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