Credibility theory based on trimming
The classical credibility theory proposed by Bühlmann has been widely used in general insurance applications. In this paper we propose a credibility theory via truncation of the loss data, or the trimmed mean. The proposed framework contains the classical credibility theory as a special case and is...
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Veröffentlicht in: | Insurance, mathematics & economics mathematics & economics, 2013-07, Vol.53 (1), p.36-47 |
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description | The classical credibility theory proposed by Bühlmann has been widely used in general insurance applications. In this paper we propose a credibility theory via truncation of the loss data, or the trimmed mean. The proposed framework contains the classical credibility theory as a special case and is based on the idea of varying the trimming threshold level to investigate the sensitivity of the credibility premium. After showing that the trimmed mean is not a coherent risk measure, we investigate some related asymptotic properties of the structural parameters in credibility. Later a numerical illustration shows that the proposed credibility models can successfully capture the tail risk of the underlying loss model, thus providing a better landscape of the overall risk that insurers assume.
•In this paper we propose a credibility theory via truncation of the loss data.•The proposed framework contains the classical credibility theory as a special case.•It is shown that the trimmed mean is not a coherent risk measure.•Some related asymptotic properties are established.•A numerical illustration is provided. |
doi_str_mv | 10.1016/j.insmatheco.2013.03.012 |
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•In this paper we propose a credibility theory via truncation of the loss data.•The proposed framework contains the classical credibility theory as a special case.•It is shown that the trimmed mean is not a coherent risk measure.•Some related asymptotic properties are established.•A numerical illustration is provided.</description><subject>Actuarial science</subject><subject>Asymptotic methods</subject><subject>Credibility</subject><subject>Economic models</subject><subject>Financial risks</subject><subject>Insurance</subject><subject>Insurance applications</subject><subject>Insurance premiums</subject><subject>L-estimator</subject><subject>Losses</subject><subject>Numerical analysis</subject><subject>Risk assessment</subject><subject>Risk measure</subject><subject>Risk theory</subject><subject>Statistical models</subject><subject>Structural analysis</subject><subject>Studies</subject><subject>Trimmed mean</subject><issn>0167-6687</issn><issn>1873-5959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkE9LxDAQxYMouK5-h4IevLRmkjRpj7r4Dxa87D2k6VRT2mZNusJ-e7OsIHgRBgaG33vMe4RkQAugIO_6wk1xNPMHWl8wCrygaYCdkAVUiudlXdanZJFQlUtZqXNyEWNPKYVaqgW5WQVsXeMGN--zZOLDPmtMxDbzUzYHN45uer8kZ50ZIl797CXZPD1uVi_5-u35dXW_zq0QfM6FaAVUhjZ1Z6gsGWuaUnHRWlVL26GhQkmebtA1ZYdCsRZqtE3J2g5BWb4kt0fbbfCfO4yzHl20OAxmQr-LGoQEKYADJPT6D9r7XZjSc4milRSC8jpR1ZGywccYsNPblMiEvQaqD-3pXv-2pw_taZoGWJI-HKWY8n45DDpah5NNZQW0s269-9_kG_oBfGM</recordid><startdate>20130701</startdate><enddate>20130701</enddate><creator>Kim, Joseph H.T.</creator><creator>Jeon, Yongho</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope></search><sort><creationdate>20130701</creationdate><title>Credibility theory based on trimming</title><author>Kim, Joseph H.T. ; Jeon, Yongho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c443t-44d418a0b9fa06522bb5734dc796cfea04763bb51fb5fe472d19ecb52dfe17c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Actuarial science</topic><topic>Asymptotic methods</topic><topic>Credibility</topic><topic>Economic models</topic><topic>Financial risks</topic><topic>Insurance</topic><topic>Insurance applications</topic><topic>Insurance premiums</topic><topic>L-estimator</topic><topic>Losses</topic><topic>Numerical analysis</topic><topic>Risk assessment</topic><topic>Risk measure</topic><topic>Risk theory</topic><topic>Statistical models</topic><topic>Structural analysis</topic><topic>Studies</topic><topic>Trimmed mean</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Joseph H.T.</creatorcontrib><creatorcontrib>Jeon, Yongho</creatorcontrib><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Computer Science Collection</collection><jtitle>Insurance, mathematics & economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Joseph H.T.</au><au>Jeon, Yongho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Credibility theory based on trimming</atitle><jtitle>Insurance, mathematics & economics</jtitle><date>2013-07-01</date><risdate>2013</risdate><volume>53</volume><issue>1</issue><spage>36</spage><epage>47</epage><pages>36-47</pages><issn>0167-6687</issn><eissn>1873-5959</eissn><coden>IMECDX</coden><abstract>The classical credibility theory proposed by Bühlmann has been widely used in general insurance applications. In this paper we propose a credibility theory via truncation of the loss data, or the trimmed mean. The proposed framework contains the classical credibility theory as a special case and is based on the idea of varying the trimming threshold level to investigate the sensitivity of the credibility premium. After showing that the trimmed mean is not a coherent risk measure, we investigate some related asymptotic properties of the structural parameters in credibility. Later a numerical illustration shows that the proposed credibility models can successfully capture the tail risk of the underlying loss model, thus providing a better landscape of the overall risk that insurers assume.
•In this paper we propose a credibility theory via truncation of the loss data.•The proposed framework contains the classical credibility theory as a special case.•It is shown that the trimmed mean is not a coherent risk measure.•Some related asymptotic properties are established.•A numerical illustration is provided.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.insmatheco.2013.03.012</doi><tpages>12</tpages></addata></record> |
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subjects | Actuarial science Asymptotic methods Credibility Economic models Financial risks Insurance Insurance applications Insurance premiums L-estimator Losses Numerical analysis Risk assessment Risk measure Risk theory Statistical models Structural analysis Studies Trimmed mean |
title | Credibility theory based on trimming |
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