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Local Transformation Kernel Density Estimation of Loss Distributions

Gustafsson, J.
Hagmann, M.
Nielsen, J. P.
Published in Journal of business & economic statistics. 2009, vol. 27, no. 2, p. 161-175
Abstract We develop a tailor made semiparametric asymmetric kernel density estimator for the es- timation of actuarial loss distributions. The estimator is obtained by transforming the data with the generalized Champernowne distribution initially fitted to the data. Then the den- sity of the transformed data is estimated by use of local asymmetric kernel methods to obtain superior estimation properties in the tails. We find in a vast simulation study that the pro- posed semiparametric estimation procedure performs well relative to alternative estimators. An application to operational loss data illustrates the proposed method.
Keywords Actuarial loss modelsTransformationChampernowne distri- butionAsymmetric kernelsLocal likelihood estimation
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Research group Geneva Finance Research Institute (GFRI)
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GUSTAFSSON, J. et al. Local Transformation Kernel Density Estimation of Loss Distributions. In: Journal of business & economic statistics, 2009, vol. 27, n° 2, p. 161-175. doi: 10.1198/jbes.2009.0011 https://archive-ouverte.unige.ch/unige:79875

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Deposited on : 2016-01-22

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