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Financial Modeling, Actuarial Valuation and Solvency in Insurance
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Financial Modeling, Actuarial Valuation and Solvency in Insurance

2013 ed.

Book Details

Format Paperback / Softback
Book Series Springer Finance
ISBN-10 3642432964
ISBN-13 9783642432965
Edition 2013 ed.
Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Manufacture GB
Country of Publication GB
Publication Date May 20th, 2015
Print length 432 Pages
Ksh 14,400.00
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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.

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 Wüthrich 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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