Nonparametric inferences for kurtosis and conditional kurtosis

DOI10.1007/s11741-009-0306-2zbMath1212.62051OpenAlexW1982516955MaRDI QIDQ3572648

Youhua He, Xiaoheng Xie

Publication date: 8 July 2010

Published in: Journal of Shanghai University (English Edition) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11741-009-0306-2

zbMATH Keywords

kernel estimatesheavy tailsconditional probability density functions

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Cites Work

• Unnamed Item
• More on the estimation of distribution densities
• Experimental analysis of nonparametric probability density estimates and of methods for smoothing them
• Conditional volatility, skewness, and kurtosis: Existence, persistence, and comovements
• Some thoughts on empirical Bayes estimation
• A simple general approach to inference about the tail of a distribution
• Transformed estimates of densities of heavy-tailed distributions and classification
• Generalized autoregressive conditional heteroscedasticity
• A note on the use of \(V\) and \(U\) statistics in nonparametric models of regression
• Statistical Inference Procedures for Bivariate Archimedean Copulas
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle

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