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Record Nr. |
UNINA9910254073303321 |
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Titolo |
Modelling in Life Insurance – A Management Perspective / / edited by Jean-Paul Laurent, Ragnar Norberg, Frédéric Planchet |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (XVI, 255 p. 42 illus., 38 illus. in color.) |
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Collana |
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Disciplina |
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Soggetti |
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Economics, Mathematical |
Actuarial science |
Statistics |
Insurance |
Quantitative Finance |
Actuarial Sciences |
Statistics for Business, Management, Economics, Finance, Insurance |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Paradigms in life insurance -- About market consistent valuation in insurance -- Cash flow projection models -- Economic scenario generators -- From internal to ORSA models -- Building a model: practical implementation -- Ex-ante model validation and back-testing -- The threat of model risk for insurance companies -- Meta-models and consistency issues -- Model feeding & Data Quality -- The role of models in management decision making -- Models and behaviour of stakeholders. |
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Sommario/riassunto |
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Focussing on life insurance and pensions, this book addresses various aspects of modelling in modern insurance: insurance liabilities; asset-liability management; securitization, hedging, and investment strategies. With contributions from internationally renowned academics in actuarial science, finance, and management science and key people in major life insurance and reinsurance companies, there is expert coverage of a wide range of topics, for example: models in life insurance and their roles in decision making; an account of the |
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contemporary history of insurance and life insurance mathematics; choice, calibration, and evaluation of models; documentation and quality checks of data; new insurance regulations and accounting rules; cash flow projection models; economic scenario generators; model uncertainty and model risk; model-based decision-making at line management level; models and behaviour of stakeholders. With author profiles ranging from highly specialized model builders to decision makers at chief executive level, this book should prove a useful resource to students and academics of actuarial science as well as practitioners. |
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