Risk Modelling in General Insurance :: From Principles to Practice.
A wide range of topics to give students a firm foundation in statistical and actuarial concepts and their applications.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge :
Cambridge University Press,
2012.
|
| Schriftenreihe: | International series on actuarial science.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | A wide range of topics to give students a firm foundation in statistical and actuarial concepts and their applications. |
| Beschreibung: | 1 online resource (410 pages) |
| Bibliographie: | Includes bibliographical references (pages 386-388) and index. |
| ISBN: | 9781139516556 1139516558 9781139518406 1139518402 9781139033756 1139033751 9780521682527 0521682525 1107225787 9781107225787 1280775076 9781280775079 9786613685469 6613685461 1139517473 9781139517478 1139514903 9781139514903 1139513974 9781139513975 |
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| 100 | 1 | |a Gray, Roger J. |0 http://id.loc.gov/authorities/names/n2012016952 | |
| 245 | 1 | 0 | |a Risk Modelling in General Insurance : |b From Principles to Practice. |
| 260 | |a Cambridge : |b Cambridge University Press, |c 2012. | ||
| 300 | |a 1 online resource (410 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 490 | 1 | |a International Series on Actuarial Science | |
| 505 | 0 | |a Cover; Risk Modelling in General Insurance; Series Page; Title; Copyright; Contents; Preface; 1: Introduction; 1.1 The aim of this book; 1.2 Notation and prerequisites; 1.2.1 Probability; 1.2.2 Statistics; 1.2.3 Simulation; 1.2.4 The statistical software package R; 2: Models for claim numbers and claim sizes; 2.1 Distributions for claim numbers; 2.1.1 Poisson distribution; 2.1.2 Negative binomial distribution; 2.1.3 Geometric distribution; 2.1.4 Binomial distribution; 2.1.5 A summary note on R; 2.2 Distributions for claim sizes; 2.2.1 A further summary note on R. | |
| 505 | 8 | |a 2.2.2 Normal (Gaussian) distribution2.2.3 Exponential distribution; 2.2.4 Gamma distribution; 2.2.5 Fat-tailed distributions; 2.2.6 Lognormal distribution; 2.2.7 Pareto distribution; 2.2.8 Weibull distribution; 2.2.9 Burr distribution; 2.2.10 Loggamma distribution; 2.3 Mixture distributions; 2.4 Fitting models to claim-number and claim-size data; 2.4.1 Fitting models to claim numbers; 2.4.2 Fitting models to claim sizes; Exercises; 3: Short term risk models; 3.1 The mean and variance of a compound distribution; 3.2 The distribution of a random sum. | |
| 505 | 8 | |a 3.2.1 Convolution series formula for a compound distribution3.2.2 Moment generating function of a compound distribution; 3.3 Finite mixture distributions; 3.4 Special compound distributions; 3.4.1 Compound Poisson distributions; 3.4.2 Compound mixed Poisson distributions; 3.4.3 Compound negative binomial distributions; 3.4.4 Compound binomial distributions; 3.5 Numerical methods for compound distributions; 3.5.1 Panjer recursion algorithm; 3.5.2 The fast Fourier transform algorithm; 3.6 Approximations for compound distributions; 3.6.1 Approximations based on a few moments. | |
| 505 | 8 | |a 3.6.2 Asymptotic approximations3.7 Statistics for compound distributions; 3.8 The individual risk model; 3.8.1 The mean and variance for the individual risk model; 3.8.2 The distribution function and moment generating function for the individual risk model; 3.8.3 Approximations for the individual risk model; Exercises; 4: Model based pricing -- setting premiums; 4.1 Premium calculation principles; 4.1.1 The expected value principle (EVP); 4.1.2 The standard deviation principle (SDP); 4.1.3 The variance principle (VP); 4.1.4 The quantile principle (QP); 4.1.5 The zero utility principle (ZUP). | |
| 505 | 8 | |a 4.1.6 The exponential premium principle (EPP)4.1.7 Some desirable properties of premium calculation principles; 4.1.8 Other premium calculation principles; 4.2 Maximum and minimum premiums; 4.3 Introduction to credibility theory; 4.4 Bayesian estimation; 4.4.1 The posterior distribution; 4.4.2 The wider context of decision theory; 4.4.3 The binomial/beta model; 4.4.4 The Poisson/gamma model; 4.4.5 The normal/normal model; 4.5 Bayesian credibility theory; 4.5.1 Bayesian credibility estimates under the Poisson/gamma model; 4.5.2 Bayesian credibility premiums under the normal/normal model. | |
| 520 | |a A wide range of topics to give students a firm foundation in statistical and actuarial concepts and their applications. | ||
| 588 | 0 | |a Print version record. | |
| 504 | |a Includes bibliographical references (pages 386-388) and index. | ||
| 546 | |a English. | ||
| 650 | 0 | |a Risk (Insurance) |x Mathematical models. | |
| 650 | 6 | |a Risque (Assurance) |x Modèles mathématiques. | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Insurance |x Risk Assessment & Management. |2 bisacsh | |
| 650 | 7 | |a Gestión del riesgo |2 embne | |
| 650 | 7 | |a Economía |x Evaluación de riesgos |2 embne | |
| 650 | 7 | |a Risk (Insurance) |x Mathematical models |2 fast | |
| 700 | 1 | |a Pitts, Susan M. |0 http://id.loc.gov/authorities/names/n2012016950 | |
| 758 | |i has work: |a Risk Modelling in General Insurance (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFBt9rF8R3cbRkc6DyKHfm |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Gray, Roger J. |t Risk Modelling in General Insurance : From Principles to Practice. |d Cambridge : Cambridge University Press, ©2012 |z 9780521863940 |
| 830 | 0 | |a International series on actuarial science. |0 http://id.loc.gov/authorities/names/n2004090956 | |
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| adam_text | |
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| author | Gray, Roger J. |
| author2 | Pitts, Susan M. |
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| author_GND | http://id.loc.gov/authorities/names/n2012016952 http://id.loc.gov/authorities/names/n2012016950 |
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| bvnumber | localFWS |
| callnumber-first | H - Social Science |
| callnumber-label | HG8054 |
| callnumber-raw | HG8054.5 .G735 2012 |
| callnumber-search | HG8054.5 .G735 2012 |
| callnumber-sort | HG 48054.5 G735 42012 |
| callnumber-subject | HG - Finance |
| collection | ZDB-4-EBU |
| contents | Cover; Risk Modelling in General Insurance; Series Page; Title; Copyright; Contents; Preface; 1: Introduction; 1.1 The aim of this book; 1.2 Notation and prerequisites; 1.2.1 Probability; 1.2.2 Statistics; 1.2.3 Simulation; 1.2.4 The statistical software package R; 2: Models for claim numbers and claim sizes; 2.1 Distributions for claim numbers; 2.1.1 Poisson distribution; 2.1.2 Negative binomial distribution; 2.1.3 Geometric distribution; 2.1.4 Binomial distribution; 2.1.5 A summary note on R; 2.2 Distributions for claim sizes; 2.2.1 A further summary note on R. 2.2.2 Normal (Gaussian) distribution2.2.3 Exponential distribution; 2.2.4 Gamma distribution; 2.2.5 Fat-tailed distributions; 2.2.6 Lognormal distribution; 2.2.7 Pareto distribution; 2.2.8 Weibull distribution; 2.2.9 Burr distribution; 2.2.10 Loggamma distribution; 2.3 Mixture distributions; 2.4 Fitting models to claim-number and claim-size data; 2.4.1 Fitting models to claim numbers; 2.4.2 Fitting models to claim sizes; Exercises; 3: Short term risk models; 3.1 The mean and variance of a compound distribution; 3.2 The distribution of a random sum. 3.2.1 Convolution series formula for a compound distribution3.2.2 Moment generating function of a compound distribution; 3.3 Finite mixture distributions; 3.4 Special compound distributions; 3.4.1 Compound Poisson distributions; 3.4.2 Compound mixed Poisson distributions; 3.4.3 Compound negative binomial distributions; 3.4.4 Compound binomial distributions; 3.5 Numerical methods for compound distributions; 3.5.1 Panjer recursion algorithm; 3.5.2 The fast Fourier transform algorithm; 3.6 Approximations for compound distributions; 3.6.1 Approximations based on a few moments. 3.6.2 Asymptotic approximations3.7 Statistics for compound distributions; 3.8 The individual risk model; 3.8.1 The mean and variance for the individual risk model; 3.8.2 The distribution function and moment generating function for the individual risk model; 3.8.3 Approximations for the individual risk model; Exercises; 4: Model based pricing -- setting premiums; 4.1 Premium calculation principles; 4.1.1 The expected value principle (EVP); 4.1.2 The standard deviation principle (SDP); 4.1.3 The variance principle (VP); 4.1.4 The quantile principle (QP); 4.1.5 The zero utility principle (ZUP). 4.1.6 The exponential premium principle (EPP)4.1.7 Some desirable properties of premium calculation principles; 4.1.8 Other premium calculation principles; 4.2 Maximum and minimum premiums; 4.3 Introduction to credibility theory; 4.4 Bayesian estimation; 4.4.1 The posterior distribution; 4.4.2 The wider context of decision theory; 4.4.3 The binomial/beta model; 4.4.4 The Poisson/gamma model; 4.4.5 The normal/normal model; 4.5 Bayesian credibility theory; 4.5.1 Bayesian credibility estimates under the Poisson/gamma model; 4.5.2 Bayesian credibility premiums under the normal/normal model. |
| ctrlnum | (OCoLC)796383847 |
| dewey-full | 368.01 368/.01 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 368 - Insurance |
| dewey-raw | 368.01 368/.01 |
| dewey-search | 368.01 368/.01 |
| dewey-sort | 3368.01 |
| dewey-tens | 360 - Social problems and services; associations |
| discipline | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| id | ZDB-4-EBU-ocn796383847 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-26T14:49:05Z |
| institution | BVB |
| isbn | 9781139516556 1139516558 9781139518406 1139518402 9781139033756 1139033751 9780521682527 0521682525 1107225787 9781107225787 1280775076 9781280775079 9786613685469 6613685461 1139517473 9781139517478 1139514903 9781139514903 1139513974 9781139513975 |
| language | English |
| oclc_num | 796383847 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (410 pages) |
| psigel | ZDB-4-EBU |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Cambridge University Press, |
| record_format | marc |
| series | International series on actuarial science. |
| series2 | International Series on Actuarial Science |
| spelling | Gray, Roger J. http://id.loc.gov/authorities/names/n2012016952 Risk Modelling in General Insurance : From Principles to Practice. Cambridge : Cambridge University Press, 2012. 1 online resource (410 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier International Series on Actuarial Science Cover; Risk Modelling in General Insurance; Series Page; Title; Copyright; Contents; Preface; 1: Introduction; 1.1 The aim of this book; 1.2 Notation and prerequisites; 1.2.1 Probability; 1.2.2 Statistics; 1.2.3 Simulation; 1.2.4 The statistical software package R; 2: Models for claim numbers and claim sizes; 2.1 Distributions for claim numbers; 2.1.1 Poisson distribution; 2.1.2 Negative binomial distribution; 2.1.3 Geometric distribution; 2.1.4 Binomial distribution; 2.1.5 A summary note on R; 2.2 Distributions for claim sizes; 2.2.1 A further summary note on R. 2.2.2 Normal (Gaussian) distribution2.2.3 Exponential distribution; 2.2.4 Gamma distribution; 2.2.5 Fat-tailed distributions; 2.2.6 Lognormal distribution; 2.2.7 Pareto distribution; 2.2.8 Weibull distribution; 2.2.9 Burr distribution; 2.2.10 Loggamma distribution; 2.3 Mixture distributions; 2.4 Fitting models to claim-number and claim-size data; 2.4.1 Fitting models to claim numbers; 2.4.2 Fitting models to claim sizes; Exercises; 3: Short term risk models; 3.1 The mean and variance of a compound distribution; 3.2 The distribution of a random sum. 3.2.1 Convolution series formula for a compound distribution3.2.2 Moment generating function of a compound distribution; 3.3 Finite mixture distributions; 3.4 Special compound distributions; 3.4.1 Compound Poisson distributions; 3.4.2 Compound mixed Poisson distributions; 3.4.3 Compound negative binomial distributions; 3.4.4 Compound binomial distributions; 3.5 Numerical methods for compound distributions; 3.5.1 Panjer recursion algorithm; 3.5.2 The fast Fourier transform algorithm; 3.6 Approximations for compound distributions; 3.6.1 Approximations based on a few moments. 3.6.2 Asymptotic approximations3.7 Statistics for compound distributions; 3.8 The individual risk model; 3.8.1 The mean and variance for the individual risk model; 3.8.2 The distribution function and moment generating function for the individual risk model; 3.8.3 Approximations for the individual risk model; Exercises; 4: Model based pricing -- setting premiums; 4.1 Premium calculation principles; 4.1.1 The expected value principle (EVP); 4.1.2 The standard deviation principle (SDP); 4.1.3 The variance principle (VP); 4.1.4 The quantile principle (QP); 4.1.5 The zero utility principle (ZUP). 4.1.6 The exponential premium principle (EPP)4.1.7 Some desirable properties of premium calculation principles; 4.1.8 Other premium calculation principles; 4.2 Maximum and minimum premiums; 4.3 Introduction to credibility theory; 4.4 Bayesian estimation; 4.4.1 The posterior distribution; 4.4.2 The wider context of decision theory; 4.4.3 The binomial/beta model; 4.4.4 The Poisson/gamma model; 4.4.5 The normal/normal model; 4.5 Bayesian credibility theory; 4.5.1 Bayesian credibility estimates under the Poisson/gamma model; 4.5.2 Bayesian credibility premiums under the normal/normal model. A wide range of topics to give students a firm foundation in statistical and actuarial concepts and their applications. Print version record. Includes bibliographical references (pages 386-388) and index. English. Risk (Insurance) Mathematical models. Risque (Assurance) Modèles mathématiques. MATHEMATICS Applied. bisacsh BUSINESS & ECONOMICS Insurance Risk Assessment & Management. bisacsh Gestión del riesgo embne Economía Evaluación de riesgos embne Risk (Insurance) Mathematical models fast Pitts, Susan M. http://id.loc.gov/authorities/names/n2012016950 has work: Risk Modelling in General Insurance (Text) https://id.oclc.org/worldcat/entity/E39PCFBt9rF8R3cbRkc6DyKHfm https://id.oclc.org/worldcat/ontology/hasWork Print version: Gray, Roger J. Risk Modelling in General Insurance : From Principles to Practice. Cambridge : Cambridge University Press, ©2012 9780521863940 International series on actuarial science. http://id.loc.gov/authorities/names/n2004090956 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=458671 Volltext |
| spellingShingle | Gray, Roger J. Risk Modelling in General Insurance : From Principles to Practice. International series on actuarial science. Cover; Risk Modelling in General Insurance; Series Page; Title; Copyright; Contents; Preface; 1: Introduction; 1.1 The aim of this book; 1.2 Notation and prerequisites; 1.2.1 Probability; 1.2.2 Statistics; 1.2.3 Simulation; 1.2.4 The statistical software package R; 2: Models for claim numbers and claim sizes; 2.1 Distributions for claim numbers; 2.1.1 Poisson distribution; 2.1.2 Negative binomial distribution; 2.1.3 Geometric distribution; 2.1.4 Binomial distribution; 2.1.5 A summary note on R; 2.2 Distributions for claim sizes; 2.2.1 A further summary note on R. 2.2.2 Normal (Gaussian) distribution2.2.3 Exponential distribution; 2.2.4 Gamma distribution; 2.2.5 Fat-tailed distributions; 2.2.6 Lognormal distribution; 2.2.7 Pareto distribution; 2.2.8 Weibull distribution; 2.2.9 Burr distribution; 2.2.10 Loggamma distribution; 2.3 Mixture distributions; 2.4 Fitting models to claim-number and claim-size data; 2.4.1 Fitting models to claim numbers; 2.4.2 Fitting models to claim sizes; Exercises; 3: Short term risk models; 3.1 The mean and variance of a compound distribution; 3.2 The distribution of a random sum. 3.2.1 Convolution series formula for a compound distribution3.2.2 Moment generating function of a compound distribution; 3.3 Finite mixture distributions; 3.4 Special compound distributions; 3.4.1 Compound Poisson distributions; 3.4.2 Compound mixed Poisson distributions; 3.4.3 Compound negative binomial distributions; 3.4.4 Compound binomial distributions; 3.5 Numerical methods for compound distributions; 3.5.1 Panjer recursion algorithm; 3.5.2 The fast Fourier transform algorithm; 3.6 Approximations for compound distributions; 3.6.1 Approximations based on a few moments. 3.6.2 Asymptotic approximations3.7 Statistics for compound distributions; 3.8 The individual risk model; 3.8.1 The mean and variance for the individual risk model; 3.8.2 The distribution function and moment generating function for the individual risk model; 3.8.3 Approximations for the individual risk model; Exercises; 4: Model based pricing -- setting premiums; 4.1 Premium calculation principles; 4.1.1 The expected value principle (EVP); 4.1.2 The standard deviation principle (SDP); 4.1.3 The variance principle (VP); 4.1.4 The quantile principle (QP); 4.1.5 The zero utility principle (ZUP). 4.1.6 The exponential premium principle (EPP)4.1.7 Some desirable properties of premium calculation principles; 4.1.8 Other premium calculation principles; 4.2 Maximum and minimum premiums; 4.3 Introduction to credibility theory; 4.4 Bayesian estimation; 4.4.1 The posterior distribution; 4.4.2 The wider context of decision theory; 4.4.3 The binomial/beta model; 4.4.4 The Poisson/gamma model; 4.4.5 The normal/normal model; 4.5 Bayesian credibility theory; 4.5.1 Bayesian credibility estimates under the Poisson/gamma model; 4.5.2 Bayesian credibility premiums under the normal/normal model. Risk (Insurance) Mathematical models. Risque (Assurance) Modèles mathématiques. MATHEMATICS Applied. bisacsh BUSINESS & ECONOMICS Insurance Risk Assessment & Management. bisacsh Gestión del riesgo embne Economía Evaluación de riesgos embne Risk (Insurance) Mathematical models fast |
| title | Risk Modelling in General Insurance : From Principles to Practice. |
| title_auth | Risk Modelling in General Insurance : From Principles to Practice. |
| title_exact_search | Risk Modelling in General Insurance : From Principles to Practice. |
| title_full | Risk Modelling in General Insurance : From Principles to Practice. |
| title_fullStr | Risk Modelling in General Insurance : From Principles to Practice. |
| title_full_unstemmed | Risk Modelling in General Insurance : From Principles to Practice. |
| title_short | Risk Modelling in General Insurance : |
| title_sort | risk modelling in general insurance from principles to practice |
| title_sub | From Principles to Practice. |
| topic | Risk (Insurance) Mathematical models. Risque (Assurance) Modèles mathématiques. MATHEMATICS Applied. bisacsh BUSINESS & ECONOMICS Insurance Risk Assessment & Management. bisacsh Gestión del riesgo embne Economía Evaluación de riesgos embne Risk (Insurance) Mathematical models fast |
| topic_facet | Risk (Insurance) Mathematical models. Risque (Assurance) Modèles mathématiques. MATHEMATICS Applied. BUSINESS & ECONOMICS Insurance Risk Assessment & Management. Gestión del riesgo Economía Evaluación de riesgos Risk (Insurance) Mathematical models |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=458671 |
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