A monotonically converging algorithm for the severity of ruin in a discrete semi-markov risk model
This paper deals with the severity of ruin in a discrete semi-Markov risk model. It is shown that the work of Reinhard and Snoussi (Stochastic Models, 18) can be extended to cover the case where the premium is an integer value and no restriction on the annual result is imposed. In particular, it is...
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Veröffentlicht in: | Scandinavian actuarial journal 2004-09, Vol.2004 (5), p.336-354 |
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container_title | Scandinavian actuarial journal |
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description | This paper deals with the severity of ruin in a discrete semi-Markov risk model. It is shown that the work of Reinhard and Snoussi (Stochastic Models, 18) can be extended to cover the case where the premium is an integer value and no restriction on the annual result is imposed. In particular, it is shown that the severity of ruin without initial surplus is solution of a system of equations. It can be obtained by a monotonically converging algorithm when the claims are bounded. |
doi_str_mv | 10.1080/03461230410019024 |
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M.</creatorcontrib><creatorcontrib>Snoussi, M.</creatorcontrib><title>A monotonically converging algorithm for the severity of ruin in a discrete semi-markov risk model</title><title>Scandinavian actuarial journal</title><description>This paper deals with the severity of ruin in a discrete semi-Markov risk model. It is shown that the work of Reinhard and Snoussi (Stochastic Models, 18) can be extended to cover the case where the premium is an integer value and no restriction on the annual result is imposed. In particular, it is shown that the severity of ruin without initial surplus is solution of a system of equations. It can be obtained by a monotonically converging algorithm when the claims are bounded.</description><subject>Actuarial science</subject><subject>Algorithms</subject><subject>Markov analysis</subject><subject>monotonically converging algorithm</subject><subject>Probability of ruin</subject><subject>recursive calculation</subject><subject>Risk assessment</subject><subject>severity of ruin</subject><subject>stable algorithm</subject><subject>Studies</subject><issn>0346-1238</issn><issn>1651-2030</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><recordid>eNqFUMtOBCEQJEYT18cHeCPePIw2MA8m8WKMr8TEi54Jy8CKzoA2rLp_L5v1ZqKkCelUVRddhBwxOGUg4QxE3TIuoGYArAdeb5EZaxtWcRCwTWZrvCoEuUv2UnoBgLaT7YzML-gUQ8wxeKPHcUVNDB8WFz4sqB4XEX1-nqiLSPOzpckWzOcVjY7i0gdaStPBJ4M2r-HJV5PG1_hB0afXMnqw4wHZcXpM9vDn3SdP11ePl7fV_cPN3eXFfWUEh1xpEENT97x0DROsa-ZDDbq1TeNq5rph3jspNeedGebaCO3asi10zlopbNla7JPjzdw3jO9Lm7J6iUsMxVJxYI3sZd0UEtuQDMaU0Dr1hr58eaUYqHWS6leSRXOy0YSIGrMq15vRJtWXw1nbt6zvJPDiUrjnG64PJbRJf0YcB5X1aozoUAfjkxJ_WXX_yn-pVP7K4huzIJfa</recordid><startdate>20040901</startdate><enddate>20040901</enddate><creator>Reinhard, J. M.</creator><creator>Snoussi, M.</creator><general>Taylor & Francis</general><general>Taylor & Francis Ltd</general><scope>3HL</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20040901</creationdate><title>A monotonically converging algorithm for the severity of ruin in a discrete semi-markov risk model</title><author>Reinhard, J. 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It is shown that the work of Reinhard and Snoussi (Stochastic Models, 18) can be extended to cover the case where the premium is an integer value and no restriction on the annual result is imposed. In particular, it is shown that the severity of ruin without initial surplus is solution of a system of equations. It can be obtained by a monotonically converging algorithm when the claims are bounded.</abstract><cop>Stockholm</cop><pub>Taylor & Francis</pub><doi>10.1080/03461230410019024</doi><tpages>19</tpages></addata></record> |
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subjects | Actuarial science Algorithms Markov analysis monotonically converging algorithm Probability of ruin recursive calculation Risk assessment severity of ruin stable algorithm Studies |
title | A monotonically converging algorithm for the severity of ruin in a discrete semi-markov risk model |
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