Financial Modeling, Actuarial Valuation and Solvency in Insurance

Risk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there are many new developments in this area in the financial and insurance industry (Basel III and Solve...

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Bibliographic Details
Main Authors: W<U+00fc>thrich, Mario V. (Author), Merz, Michael. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Series:Springer Finance,
Subjects:
Online Access:View fulltext via EzAccess
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505 0 # |a 1.Introduction -- Part I: Financial Valuation Principles -- 2.State price deflators and stochastic discounting -- 3.spot rate models -- 4.Stochastic forward rate and yield curve modeling -- 5.Pricing of financial assets -- Part II: Actuarial Valuation and Solvency -- 6.Actuarial and financial modeling -- 7.Valuation portfolio -- 8.Protected valuation portfolio -- 9.Solvency -- 10.Selected topics and examples -- Part III: Appendix -- 11.Auxiliary considerations -- References -- Index. 
520 # # |a Risk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there are many new developments in this area in the financial and insurance industry (Basel III and Solvency II), but none of these developments provides a fully consistent and comprehensive framework for the analysis of solvency questions. Merz and W<U+00fc>thrich combine ideas from financial mathematics (no-arbitrage theory, equivalent martingale measure), actuarial sciences (insurance claims modeling, cash flow valuation) and economic theory (risk aversion, probability distortion) to provide a fully consistent framework. Within this framework they then study solvency questions in incomplete markets, analyze hedging risks, and study asset-and-liability management questions, as well as issues like the limited liability options, dividend to shareholder questions, the role of re-insurance, etc. This work embeds the solvency discussion (and long-term liabilities) into a scientific framework and is intended for researchers as well as practitioners in the financial and actuarial industry, especially those in charge of internal risk management systems. Readers should have a good background in probability theory and statistics, and should be familiar with popular distributions, stochastic processes, martingales, etc. 
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