Efficient and robust estimation for financial returns: an approach based on q-entropy
AbstractWe 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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Bibliographic InfoPaper provided by University of Modena and Reggio E., Faculty of Economics "Marco Biagi" in its series Department of Economics with number 0623.
Length: pages 38
Date of creation: Feb 2010
Date of revision:
q-entropy; robust estimation; power-divergence; _nancial returns;
Other versions of this item:
- Davide Ferrari & Sandra Paterlini, 2010. "Efficient and robust estimation for financial returns: an approach based on q-entropy," Center for Economic Research (RECent) 041, University of Modena and Reggio E., Dept. of Economics.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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