Efficient and Robust Estimation for Financial Returns: An Approach Based on q-Entropy

39 Pages Posted: 10 Aug 2011

See all articles by Davide Ferrari

Davide Ferrari

University of Melbourne

Sandra Paterlini

University of Trento - Department of Economics and Management

Date Written: November 2, 2010

Abstract

We consider a new robust parametric estimation procedure, which minimizes an empirical version of the Havrda-Charvat-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-off between robustness and efficiency. The method is applied to expected return and volatility estimation of financial asset returns under multivariate normality. Theoretical properties, ease of implementability and empirical results on simulated and financial 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, financial returns

JEL Classification: C13, G11

Suggested Citation

Ferrari, Davide and Paterlini, Sandra, Efficient and Robust Estimation for Financial Returns: An Approach Based on q-Entropy (November 2, 2010). Available at SSRN: https://ssrn.com/abstract=1906819 or http://dx.doi.org/10.2139/ssrn.1906819

Davide Ferrari

University of Melbourne ( email )

185 Pelham Street
Carlton, Victoria 3053
Australia

Sandra Paterlini (Contact Author)

University of Trento - Department of Economics and Management ( email )

Via Inama 5
Trento, I-38100
Italy

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