Efficient and Robust Estimation for Financial Returns: An Approach Based on q-Entropy
39 Pages Posted: 10 Aug 2011
Date Written: November 2, 2010
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
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