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 InfoPaper provided by Banque de France in its series Working papers with number 79.
Length: 27 pages
Date of creation: 2001
Date of revision:
Semi-nonparametric estimation ; Time-varying skewness and kurtosis ; GARCH.;
Other versions of this item:
- Rockinger, Michael & Jondeau, Eric, 2002. "Entropy densities with an application to autoregressive conditional skewness and kurtosis," Journal of Econometrics, Elsevier, vol. 106(1), pages 119-142, January.
- 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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