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001 9781315151687
008 180727t20182019fluab ob 001 0 eng d
020 _a9781315151687
_q(e-book : PDF)
035 _a(OCoLC)1005691339
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050 4 _aHG8054.5
_b.F46 2018
072 7 _aBUS
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072 7 _aKF
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072 7 _aMAT
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072 7 _aMAT
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082 0 4 _a368
_223
100 1 _aFeng, Runhuan,
_eauthor.
245 1 3 _aAn introduction to computational risk management of equity-linked insurance /
_cby Runhuan Feng.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bCRC Press, an imprint of Taylor and Francis,
_c[2018].
264 4 _c©2019.
300 _a1 online resource (402 pages) :
_b30 illustrations.
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
490 1 _aChapman and Hall/CRC financial mathematics series
505 0 _achapter 1 Modeling of Equity-linked Insurance -- chapter 2 Elementary Stochastic Calculus -- chapter 3 Monte Carlo Simulations of Investment Guarantees -- chapter 4 Pricing and Valuation -- chapter 5 Risk Management - Reserving and Capital Requirement -- chapter 6 Risk Management - Dynamic Hedging -- chapter 7 Advanced ComputationalMethods.
520 3 _aThe quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development.Bridges the gap between the latest developments in finance and actuarial literature and the practice of risk management for investment-combined life insuranceFeaturesGives a comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methodsIncludes a collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematiciansProvides a comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance with exercises and programming samplesRunhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow.Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.Summarizes state-of-arts computational techniques for risk management professionalsToday's computational power and technology make it possible for the life insurance industry to develop highly sophisticated models, which were impossible just a decade ago. Nonetheless, as more industrial practices and regulations move towards dependence on stochastic models, the demand for computational power continues to grow. While the industry continues to rely heavily on hardware innovations, trying to make brute force methods faster and more palatable, we are approaching a crossroads about how to proceed. An Introduction to Computational Risk Management of Equity-Linked Insurance provides a resource for students and entry-level professionals to understand the fundamentals of industrial modeling practice, but also to give a glimpse of software methodologies for modeling and computational efficiency.
650 0 _aActuarial Science.
650 0 _aFinance.
650 0 _aFinancial Mathematics.
650 0 _aStatistics for Business, Finance & Economics.
650 0 _aBUSINESSnetBASE/MANAGEMENTnetBASE.
650 0 _aSTATSnetBASE.
650 0 _aHedging.
650 0 _aInsurance
_xMathematical models.
650 0 _aMathematical Finance.
650 0 _aOption Pricing.
650 0 _aRisk (Insurance)
_xMathematical models.
650 0 _aRisk management
_xMathematical models.
650 0 _aRisk Metrics.
650 7 _aMATHEMATICS / General.
_2bisacsh
650 7 _aMATHEMATICS / Probability & Statistics / General.
_2bisacsh
710 2 _aTaylor and Francis.
776 0 8 _iPrint version:
_z9781498742160
_w(DLC) 2018010547
830 0 _aChapman and Hall/CRC financial mathematics series.
856 4 0 _uhttps://www.taylorfrancis.com/books/9781315151687
_zClick here to view.
999 _c129877
_d129877