000 03131nam a22005295i 4500
001 978-3-642-15609-0
003 DE-He213
005 20140220083747.0
007 cr nn 008mamaa
008 110202s2011 gw | s |||| 0|eng d
020 _a9783642156090
_9978-3-642-15609-0
024 7 _a10.1007/978-3-642-15609-0
_2doi
050 4 _aHG1-9999
050 4 _aHG4501-6051
050 4 _aHG1501-HG3550
072 7 _aKFF
_2bicssc
072 7 _aKFFK
_2bicssc
072 7 _aBUS027000
_2bisacsh
072 7 _aBUS004000
_2bisacsh
082 0 4 _a657.8333
_223
082 0 4 _a658.152
_223
100 1 _aSchlösser, Anna.
_eauthor.
245 1 0 _aPricing and Risk Management of Synthetic CDOs
_h[electronic resource] /
_cby Anna Schlösser.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2011.
300 _aXII, 288p. 90 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Economics and Mathematical Systems,
_x0075-8442 ;
_v646
505 0 _aIntroduction -- Part I Fundamentals: Credit Derivatives and Markets -- Mathematical Preliminaries -- Part II Static Models: One Factor Gaussian Copula Model -- Normal Inverse Gaussian Factor Copula Model -- Part III: Term-Structure Models -- Large Homogeneous Cell Approximation for Factor Copula Models -- Regime-Switching Extension of the NIG Factor Copula Model -- Simulation Framework -- Conclusion.
520 _aThis book considers the one-factor copula model for credit portfolios that are used for pricing synthetic CDO structures as well as for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors and the inclusion of CDO structures in a portfolio context. For this objective, it is especially important to have a computationally fast model that can also be used in a scenario simulation framework. The well known Gaussian copula model is extended in various ways in order to improve its drawbacks of correlation smile and time inconsistency. Also the application of the large homogeneous cell assumption, that allows to differentiate between rating classes, makes the model convenient and powerful for practical applications. The Crash-NIG extension introduces an important regime-switching feature allowing the possibility of a market crash that is characterized by a high-correlation regime.
650 0 _aEconomics.
650 0 _aMathematics.
650 0 _aFinance.
650 1 4 _aEconomics/Management Science.
650 2 4 _aFinance/Investment/Banking.
650 2 4 _aQuantitative Finance.
650 2 4 _aApplications of Mathematics.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642156083
830 0 _aLecture Notes in Economics and Mathematical Systems,
_x0075-8442 ;
_v646
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-15609-0
912 _aZDB-2-SBE
999 _c107069
_d107069