Portfolio risk analysis of excess of loss reinsurance

Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which e...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Tang, Qihe [verfasserIn] Tong, Zhiwei [verfasserIn] Xun, Li [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	Versicherungsökonomik / Versicherungsmathematik
Schlagwörter:	Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures

Übergeordnetes Werk:	Enthalten in: Insurance - Amsterdam : North Holland Publ. Co., 1982, 102, Seite 91-110
Übergeordnetes Werk:	volume:102 ; pages:91-110

DOI / URN:	10.1016/j.insmatheco.2021.11.004

Katalog-ID:	ELV00723001X

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100	1		\|a Tang, Qihe \|e verfasserin \|0 (orcid)0000-0002-5985-8939 \|4 aut
245	1	0	\|a Portfolio risk analysis of excess of loss reinsurance
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337			\|a Computermedien \|b c \|2 rdamedia
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520			\|a Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters.
650		7	\|8 1.1\x \|a Versicherungsökonomik \|0 (DE-2867)18741-3 \|2 stw
650		7	\|8 1.2\x \|a Versicherungsmathematik \|0 (DE-2867)13823-5 \|2 stw
650		4	\|a Mixture
650		4	\|a Solvency capital requirement
650		4	\|a Retention
650		4	\|a Law of large numbers
650		4	\|a Distortion risk measures
700	1		\|a Tong, Zhiwei \|e verfasserin \|4 aut
700	1		\|a Xun, Li \|e verfasserin \|0 (orcid)0000-0003-1704-6841 \|4 aut
773	0	8	\|i Enthalten in \|t Insurance \|d Amsterdam : North Holland Publ. Co., 1982 \|g 102, Seite 91-110 \|h Online-Ressource \|w (DE-627)319290484 \|w (DE-600)2010248-3 \|w (DE-576)093890818 \|7 nnns
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912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2011
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912			\|a GBV_ILN_2122
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936	b	k	\|a 31.99 \|j Mathematik: Sonstiges
936	b	k	\|a 83.03 \|j Methoden und Techniken der Volkswirtschaft
936	b	k	\|a 83.70 \|j Banken \|j Versicherungen
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952			\|d 102 \|h 91-110

Indexfelder

author_variant	q t qt z t zt l x lx
matchkey_str	tangqihetongzhiweixunli:2021----:otoirsaayioecsol
hierarchy_sort_str	2021
bklnumber	31.99 83.03 83.70
publishDate	2021
allfields	10.1016/j.insmatheco.2021.11.004 doi (DE-627)ELV00723001X (ELSEVIER)S0167-6687(21)00170-0 DE-627 ger DE-627 rda eng 31.99 bkl 83.03 bkl 83.70 bkl Tang, Qihe verfasserin (orcid)0000-0002-5985-8939 aut Portfolio risk analysis of excess of loss reinsurance 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters. 1.1\x Versicherungsökonomik (DE-2867)18741-3 stw 1.2\x Versicherungsmathematik (DE-2867)13823-5 stw Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures Tong, Zhiwei verfasserin aut Xun, Li verfasserin (orcid)0000-0003-1704-6841 aut Enthalten in Insurance Amsterdam : North Holland Publ. Co., 1982 102, Seite 91-110 Online-Ressource (DE-627)319290484 (DE-600)2010248-3 (DE-576)093890818 nnns volume:102 pages:91-110 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.99 Mathematik: Sonstiges 83.03 Methoden und Techniken der Volkswirtschaft 83.70 Banken Versicherungen SEC-16000 SKW AR 102 91-110
spelling	10.1016/j.insmatheco.2021.11.004 doi (DE-627)ELV00723001X (ELSEVIER)S0167-6687(21)00170-0 DE-627 ger DE-627 rda eng 31.99 bkl 83.03 bkl 83.70 bkl Tang, Qihe verfasserin (orcid)0000-0002-5985-8939 aut Portfolio risk analysis of excess of loss reinsurance 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters. 1.1\x Versicherungsökonomik (DE-2867)18741-3 stw 1.2\x Versicherungsmathematik (DE-2867)13823-5 stw Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures Tong, Zhiwei verfasserin aut Xun, Li verfasserin (orcid)0000-0003-1704-6841 aut Enthalten in Insurance Amsterdam : North Holland Publ. Co., 1982 102, Seite 91-110 Online-Ressource (DE-627)319290484 (DE-600)2010248-3 (DE-576)093890818 nnns volume:102 pages:91-110 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.99 Mathematik: Sonstiges 83.03 Methoden und Techniken der Volkswirtschaft 83.70 Banken Versicherungen SEC-16000 SKW AR 102 91-110
allfields_unstemmed	10.1016/j.insmatheco.2021.11.004 doi (DE-627)ELV00723001X (ELSEVIER)S0167-6687(21)00170-0 DE-627 ger DE-627 rda eng 31.99 bkl 83.03 bkl 83.70 bkl Tang, Qihe verfasserin (orcid)0000-0002-5985-8939 aut Portfolio risk analysis of excess of loss reinsurance 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters. 1.1\x Versicherungsökonomik (DE-2867)18741-3 stw 1.2\x Versicherungsmathematik (DE-2867)13823-5 stw Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures Tong, Zhiwei verfasserin aut Xun, Li verfasserin (orcid)0000-0003-1704-6841 aut Enthalten in Insurance Amsterdam : North Holland Publ. Co., 1982 102, Seite 91-110 Online-Ressource (DE-627)319290484 (DE-600)2010248-3 (DE-576)093890818 nnns volume:102 pages:91-110 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.99 Mathematik: Sonstiges 83.03 Methoden und Techniken der Volkswirtschaft 83.70 Banken Versicherungen SEC-16000 SKW AR 102 91-110
allfieldsGer	10.1016/j.insmatheco.2021.11.004 doi (DE-627)ELV00723001X (ELSEVIER)S0167-6687(21)00170-0 DE-627 ger DE-627 rda eng 31.99 bkl 83.03 bkl 83.70 bkl Tang, Qihe verfasserin (orcid)0000-0002-5985-8939 aut Portfolio risk analysis of excess of loss reinsurance 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters. 1.1\x Versicherungsökonomik (DE-2867)18741-3 stw 1.2\x Versicherungsmathematik (DE-2867)13823-5 stw Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures Tong, Zhiwei verfasserin aut Xun, Li verfasserin (orcid)0000-0003-1704-6841 aut Enthalten in Insurance Amsterdam : North Holland Publ. Co., 1982 102, Seite 91-110 Online-Ressource (DE-627)319290484 (DE-600)2010248-3 (DE-576)093890818 nnns volume:102 pages:91-110 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.99 Mathematik: Sonstiges 83.03 Methoden und Techniken der Volkswirtschaft 83.70 Banken Versicherungen SEC-16000 SKW AR 102 91-110
allfieldsSound	10.1016/j.insmatheco.2021.11.004 doi (DE-627)ELV00723001X (ELSEVIER)S0167-6687(21)00170-0 DE-627 ger DE-627 rda eng 31.99 bkl 83.03 bkl 83.70 bkl Tang, Qihe verfasserin (orcid)0000-0002-5985-8939 aut Portfolio risk analysis of excess of loss reinsurance 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters. 1.1\x Versicherungsökonomik (DE-2867)18741-3 stw 1.2\x Versicherungsmathematik (DE-2867)13823-5 stw Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures Tong, Zhiwei verfasserin aut Xun, Li verfasserin (orcid)0000-0003-1704-6841 aut Enthalten in Insurance Amsterdam : North Holland Publ. Co., 1982 102, Seite 91-110 Online-Ressource (DE-627)319290484 (DE-600)2010248-3 (DE-576)093890818 nnns volume:102 pages:91-110 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.99 Mathematik: Sonstiges 83.03 Methoden und Techniken der Volkswirtschaft 83.70 Banken Versicherungen SEC-16000 SKW AR 102 91-110
language	English
source	Enthalten in Insurance 102, Seite 91-110 volume:102 pages:91-110
sourceStr	Enthalten in Insurance 102, Seite 91-110 volume:102 pages:91-110
format_phy_str_mv	Article
bklname	Mathematik: Sonstiges Methoden und Techniken der Volkswirtschaft Banken Versicherungen
institution	findex.gbv.de
topic_facet	Versicherungsökonomik Versicherungsmathematik Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures
isfreeaccess_bool	false
container_title	Insurance
authorswithroles_txt_mv	Tang, Qihe @@aut@@ Tong, Zhiwei @@aut@@ Xun, Li @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	319290484
id	ELV00723001X
language_de	englisch
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author	Tang, Qihe
spellingShingle	Tang, Qihe bkl 31.99 bkl 83.03 bkl 83.70 stw Versicherungsökonomik stw Versicherungsmathematik misc Mixture misc Solvency capital requirement misc Retention misc Law of large numbers misc Distortion risk measures Portfolio risk analysis of excess of loss reinsurance
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topic_title	31.99 bkl 83.03 bkl 83.70 bkl Portfolio risk analysis of excess of loss reinsurance 1.1\x Versicherungsökonomik (DE-2867)18741-3 stw 1.2\x Versicherungsmathematik (DE-2867)13823-5 stw Mixture Solvency capital requirement Retention Law of large numbers Distortion risk measures
topic	bkl 31.99 bkl 83.03 bkl 83.70 stw Versicherungsökonomik stw Versicherungsmathematik misc Mixture misc Solvency capital requirement misc Retention misc Law of large numbers misc Distortion risk measures
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title	Portfolio risk analysis of excess of loss reinsurance
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title_full	Portfolio risk analysis of excess of loss reinsurance
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title_sort	portfolio risk analysis of excess of loss reinsurance
title_auth	Portfolio risk analysis of excess of loss reinsurance
abstract	Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters.
abstractGer	Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters.
abstract_unstemmed	Consider a catastrophe insurance market in which primary insurers purchase excess of loss reinsurance to transfer their higher-layer losses to a reinsurer. We conduct a portfolio risk analysis for the reinsurer. In doing so, we model the losses to the primary insurers by a mixture structure, which effectively integrates three risk factors: common shock, systematic risk, and idiosyncratic risk. Assume that the reinsurer holds an initial capital C n that is in accordance with its market size n. When expanding its business, the reinsurer needs to comply with a certain VaR-based solvency capital requirement, which determines an infimal retention level r n according to the initial capital C n . As our main results, we find the limit of r n as n → ∞ and then establish a weak convergence for the reinsurance portfolio loss. The latter result is applied to approximate the distortion risk measures of the reinsurance portfolio loss. In our numerical studies, we examine the accuracy of the obtained approximations and conduct various sensitivity tests against some risk parameters.
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title_short	Portfolio risk analysis of excess of loss reinsurance
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