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Prediction of reserves using multivariate power-normal mixture distribution

Recently, in the area on stochastic loss reserving, there are a number of papers which analyze the individual claims data using the Position Dependent Marked Poisson Process. The present paper instead uses a different type of individual data. For the i-th (1 ≤ i ≤ n) customer, these individual dat...

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Main Authors:	Ang, Siew Ling , Pooi, Ah Hin
格式:	Article
語言:	English
出版:	AIP Publishing 2016
主題:	HA Statistics HG Finance
在線閱讀:	http://eprints.sunway.edu.my/437/1/Pooi%20Ah%20Hin%207.pdf http://eprints.sunway.edu.my/437/ http://aip.scitation.org http://dx.doi.org/10.1063/1.4966093
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id	my.sunway.eprints.437
record_format	eprints
spelling	my.sunway.eprints.4372023-09-25T05:19:14Z http://eprints.sunway.edu.my/437/ Prediction of reserves using multivariate power-normal mixture distribution Ang, Siew Ling * Pooi, Ah Hin * HA Statistics HG Finance Recently, in the area on stochastic loss reserving, there are a number of papers which analyze the individual claims data using the Position Dependent Marked Poisson Process. The present paper instead uses a different type of individual data. For the i-th (1 ≤ i ≤ n) customer, these individual data include the sum insured i s together with the amount paid ij y and the amount ij a reported but not yet paid in the j-th (1 6) j dd development year. A technique based on multivariate power-normal mixture distribution is already available for predicting the future value ( 1 ijy � , 1 ija � ) using the present year value(,) i j i j ya and the sum insured i s . Presently the above technique is improved by the transformation of distribution which is defined on the whole real line to one which is non-negative and having approximately the same first four moments as the original distribution. It is found that, for the dataset considered in this paper, the improved method giveV a better estimate for the reserve when compared with the chain ladder reserve estimate. Furthermore, the method is expected to provide a fairly reliable value for the Provision of Risk Margin for Adverse Deviation (PRAD) AIP Publishing 2016 Article PeerReviewed text en http://eprints.sunway.edu.my/437/1/Pooi%20Ah%20Hin%207.pdf Ang, Siew Ling * and Pooi, Ah Hin * (2016) Prediction of reserves using multivariate power-normal mixture distribution. AIP Conference Proceedings, 1782 (050003). pp. 1-7. ISSN 1551 7616 http://aip.scitation.org http://dx.doi.org/10.1063/1.4966093
institution	Sunway University
building	Sunway Campus Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Sunway University
content_source	Sunway Institutional Repository
url_provider	http://eprints.sunway.edu.my/
language	English
topic	HA Statistics HG Finance
spellingShingle	HA Statistics HG Finance Ang, Siew Ling * Pooi, Ah Hin * Prediction of reserves using multivariate power-normal mixture distribution
description	Recently, in the area on stochastic loss reserving, there are a number of papers which analyze the individual claims data using the Position Dependent Marked Poisson Process. The present paper instead uses a different type of individual data. For the i-th (1 ≤ i ≤ n) customer, these individual data include the sum insured i s together with the amount paid ij y and the amount ij a reported but not yet paid in the j-th (1 6) j dd development year. A technique based on multivariate power-normal mixture distribution is already available for predicting the future value ( 1 ijy � , 1 ija � ) using the present year value(,) i j i j ya and the sum insured i s . Presently the above technique is improved by the transformation of distribution which is defined on the whole real line to one which is non-negative and having approximately the same first four moments as the original distribution. It is found that, for the dataset considered in this paper, the improved method giveV a better estimate for the reserve when compared with the chain ladder reserve estimate. Furthermore, the method is expected to provide a fairly reliable value for the Provision of Risk Margin for Adverse Deviation (PRAD)
format	Article
author	Ang, Siew Ling * Pooi, Ah Hin *
author_facet	Ang, Siew Ling * Pooi, Ah Hin *
author_sort	Ang, Siew Ling *
title	Prediction of reserves using multivariate power-normal mixture distribution
title_short	Prediction of reserves using multivariate power-normal mixture distribution
title_full	Prediction of reserves using multivariate power-normal mixture distribution
title_fullStr	Prediction of reserves using multivariate power-normal mixture distribution
title_full_unstemmed	Prediction of reserves using multivariate power-normal mixture distribution
title_sort	prediction of reserves using multivariate power-normal mixture distribution
publisher	AIP Publishing
publishDate	2016
url	http://eprints.sunway.edu.my/437/1/Pooi%20Ah%20Hin%207.pdf http://eprints.sunway.edu.my/437/ http://aip.scitation.org http://dx.doi.org/10.1063/1.4966093
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score	13.251813

Prediction of reserves using multivariate power-normal mixture distribution

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