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Entropy densities with an application to autoregressive conditional skewness and kurtosis

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  • Rockinger, Michael
  • Jondeau, Eric

Abstract

The 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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  • 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.
    • Handle: RePEc:eee:econom:v:106:y:2002:i:1:p:119-142
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    References listed on IDEAS

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    JEL classification:

    • 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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