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008 130405s2013 gw | s |||| 0|eng d
020 _a9783642313929
_9978-3-642-31392-9
024 7 _a10.1007/978-3-642-31392-9
_2doi
050 4 _aHB135-147
072 7 _aKF
_2bicssc
072 7 _aMAT003000
_2bisacsh
072 7 _aBUS027000
_2bisacsh
082 0 4 _a519
_223
100 1 _aWüthrich, Mario V.
_eauthor.
245 1 0 _aFinancial Modeling, Actuarial Valuation and Solvency in Insurance
_h[electronic resource] /
_cby Mario V. Wüthrich, Michael Merz.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXIV, 432 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Finance,
_x1616-0533
505 0 _a1.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 _aRisk 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.
650 0 _aMathematics.
650 0 _aEconomics, Mathematical.
650 0 _aActuarial science.
650 0 _aStatistics.
650 1 4 _aMathematics.
650 2 4 _aQuantitative Finance.
650 2 4 _aActuarial Sciences.
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
700 1 _aMerz, Michael.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642313912
830 0 _aSpringer Finance,
_x1616-0533
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-31392-9
912 _aZDB-2-SMA
942 _2Dewey Decimal Classification
_ceBooks
999 _c46035
_d46035