000725381 000__ 04992cam\a2200493Ii\4500
000725381 001__ 725381
000725381 005__ 20230306140635.0
000725381 006__ m\\\\\o\\d\\\\\\\\
000725381 007__ cr\cn\nnnunnun
000725381 008__ 150128s2015\\\\sz\a\\\\o\\\\\100\0\eng\d
000725381 019__ $$a903962459
000725381 020__ $$a9783319091143$$qelectronic book
000725381 020__ $$a331909114X$$qelectronic book
000725381 020__ $$z9783319091136
000725381 0247_ $$a10.1007/978-3-319-09114-3$$2doi
000725381 035__ $$aSP(OCoLC)ocn900859867
000725381 035__ $$aSP(OCoLC)900859867$$z(OCoLC)903962459
000725381 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDXCP$$dCOO$$dOCLCF$$dE7B
000725381 049__ $$aISEA
000725381 050_4 $$aHD61
000725381 08204 $$a658.15/5$$223
000725381 24500 $$aInnovations in quantitative risk management$$h[electronic resource] :$$bTU München, September 2013 /$$cKathrin Glau, Matthias Scherer, Rudi Zagst, editors.
000725381 264_1 $$aCham :$$bSpringer,$$c2015.
000725381 300__ $$a1 online resource (xi, 438 pages) :$$billustrations.
000725381 336__ $$atext$$btxt$$2rdacontent
000725381 337__ $$acomputer$$bc$$2rdamedia
000725381 338__ $$aonline resource$$bcr$$2rdacarrier
000725381 4901_ $$aSpringer Proceedings in Mathematics & Statistics,$$x2194-1009 ;$$vvolume 99
000725381 504__ $$aIncludes bibliographical references.
000725381 5050_ $$aPart I Markets, Regulation, and Model Risk -- A Random Holding Period Approach for Liquidity-Inclusive Risk Management -- Regulatory Developments in Risk Management: Restoring Confidence in Internal Models -- Model Risk in Incomplete Markets with Jumps -- Part II Financial Engineering -- Bid-Ask Spread for Exotic Options Under Conic Finance -- Derivative Pricing Under the Possibility of Long Memory in the supOU Stochastic Volatility Model -- A Two-Sided BNS Model for Multicurrency FX Markets -- Modeling the Price of Natural Gas with Temperature and Oil Price as Exogenous Factors -- Copula-Specific Credit Portfolio Modeling -- Implied Recovery Rates?Auctions and Models -- Upside and Downside Risk Exposures of Currency Carry Trades via Tail Dependence -- Part III Insurance Risk and Asset Management -- Participating Life Insurance Contracts Under Risk Based Solvency Frameworks: How to Increase Capital Efficiency by Product Design -- Reducing Surrender Incentives Through Fee Structure in Variable Annuities -- A Variational Approach for Mean-Variance-Optimal Deterministic Consumption and Investment -- Risk Control in Asset Management: Motives and Concepts -- Worst-Case Scenario Portfolio Optimization Given the Probability of a Crash -- Improving Optimal Terminal Value Replicating Portfolios -- Part IV Computational Methods for Risk Management -- Risk and Computation -- Extreme Value Importance Sampling for Rare Event Risk Measurement -- A Note on the Numerical Evaluation of the Hartman?Watson Density and Distribution Function -- Computation of Copulas by Fourier Methods -- Part V Dependence Modelling -- Goodness-of-fit Tests for Archimedean Copulas in High Dimensions -- Duality in Risk Aggregation -- Some Consequences of the Markov Kernel Perspective of Copulas -- Copula Representations for Invariant Dependence Functions -- Nonparametric Copula Density Estimation Using a Petrov?Galerkin Projection.
000725381 506__ $$aAccess limited to authorized users.
000725381 520__ $$aQuantitative models are omnipresent ?but often controversially discussed? in todays risk management practice. New regulations, innovative financial products, and advances in valuation techniques provide a continuous flow of challenging problems for financial engineers and risk managers alike. Designing a sound stochastic model requires finding a careful balance between parsimonious model assumptions, mathematical viability, and interpretability of the output. Moreover, data requirements and the end-user training are to be considered as well. The KPMG Center of Excellence in Risk Management conference Risk Management Reloaded and this proceedings volume contribute to bridging the gap between academia ?providing methodological advances? and practice ?having a firm understanding of the economic conditions in which a given model is used. Discussed fields of application range from asset management, credit risk, and energy to risk management issues in insurance. Methodologically, dependence modeling, multiple-curve interest rate-models, and model risk are addressed. Finally, regulatory developments and possible limits of mathematical modeling are discussed.
000725381 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 28, 2015).
000725381 650_0 $$aFinancial risk management$$vCongresses.
000725381 650_0 $$aQuantitative research$$vCongresses.
000725381 7001_ $$aGlau, Kathrin,$$eeditor.
000725381 7001_ $$aScherer, Matthias,$$eeditor.
000725381 7001_ $$aZagst, Rudi,$$d1961-$$eeditor.
000725381 77608 $$iPrint version:$$z9783319091136
000725381 830_0 $$aSpringer proceedings in mathematics & statistics ;$$v99.
000725381 852__ $$bebk
000725381 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-09114-3$$zOnline Access$$91397441.1
000725381 909CO $$ooai:library.usi.edu:725381$$pGLOBAL_SET
000725381 980__ $$aEBOOK
000725381 980__ $$aBIB
000725381 982__ $$aEbook
000725381 983__ $$aOnline
000725381 994__ $$a92$$bISE