Financial Modeling Actuarial Valuation And Solvency In Insurance

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Financial Modeling, Actuarial Valuation and Solvency in Insurance

Financial Modeling, Actuarial Valuation and Solvency in Insurance
Author :
Publisher : Springer Science & Business Media
Total Pages : 438
Release :
ISBN-10 : 9783642313929
ISBN-13 : 3642313922
Rating : 4/5 (922 Downloads)

Book Synopsis Financial Modeling, Actuarial Valuation and Solvency in Insurance by : Mario V. Wüthrich

Download or read book Financial Modeling, Actuarial Valuation and Solvency in Insurance written by Mario V. Wüthrich and published by Springer Science & Business Media. This book was released on 2013-04-04 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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