Entropy densities with an application to autoregressive conditional skewness and kurtosis
AbstractThe entropy principle yields, for a given set moments, a density that involves the smallest amount of prior information. We first show how entropy densities may be constructed in a numerically efficient way as the minimization of a potential. Next, for the case where the first four moments are given, we characterize the skewness-Kurtosis domain for which densities are defined.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 106 (2002)
Issue (Month): 1 (January)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- Rockinger, M. & Jondeau, E., 2001. "Entropy Densities: with an Application to Autoregressive Conditional Skewness and Kurtosis," Working papers 79, Banque de France.
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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