000			04346cam a22004454a 4500
007			v| ||||||
008			090608s2009 enka sb 001 0 eng d
010			_a 2009417734
020			_a0123736838
020			_a9780123736833
040			_aOPELS _beng _cOPELS _dDLC
050	0	0	_aHG3751 _b.T78 2009
082	0	4	_a658.88 _222
092	0	4	_a658.88 _bT8666 _221
099			_a04 _a658.88 T8666
100	1		_aTrueck, Stefan.
245	1	0	_aRating based modeling of credit risk: _btheory and application of migration matrices _h[electronic resource] / _cStefan Trueck, Svetlozar T. Rachev.
260			_aLondon _aBurlington, MA : _bAcademic, _cc2009.
300			_axii, 266 p. : _bill. ; _c24 cm.
440		0	_aAcademic Press advanced finance series
504			_aIncludes bibliographical references (p. [249]-258) and index.
505	0		_a1. Introduction: Credit Risk Modeling, Ratings and Migration Matrices -- 2. Rating and Scoring Techniques -- 3. The New Basel Capital Accord -- 4. Rating Based Modeling -- 5. Migration Matrices and the Markov Chain Approach -- 6. Stability of Credit Migrations -- 7. Measures for Comparison of Transition Matrices -- 8. Real World and Risk-Neutral Transition Matrices -- 9. Conditional Credit Migrations: Adjustments and Forecasts -- 10. Dependence Modeling and Credit Migrations -- 11. Credit Derivatives.
520			_aIn the last decade rating-based models have become very popular in credit risk management. These systems use the rating of a company as the decisive variable to evaluate the default risk of a bond or loan. The popularity is due to the straightforwardness of the approach, and to the upcoming new capital accord (Basel II), which allows banks to base their capital requirements on internal as well as external rating systems. Because of this, sophisticated credit risk models are being developed or demanded by banks to assess the risk of their credit portfolio better by recognizing the different underlying sources of risk. As a consequence, not only default probabilities for certain rating categories but also the probabilities of moving from one rating state to another are important issues in such models for risk management and pricing. It is widely accepted that rating migrations and default probabilities show significant variations through time due to macroeconomics conditions or the business cycle. These changes in migration behavior may have a substantial impact on the value-at-risk (VAR) of a credit portfolio or the prices of credit derivatives such as collateralized debt obligations (D+CDOs). In this book the authors develop a much more sophisticated analysis of migration behavior. Their contribution of more sophisticated techniques to measure and forecast changes in migration behavior as well as determining adequate estimators for transition matrices is a major contribution to rating based credit modeling. *Internal ratings-based systems are widely used in banks to calculate their value-at-risk (VAR) in order to determine their capital requirements for loan and bond portfolios under Basel II. One aspect of these ratings systems is credit migrations, addressed in a systematic and comprehensive way for the first time in this book. The book is based on in-depth work by Trueck and Rachev.
533			_aElectronic reproduction. _bAmsterdam : _cElsevier Science & Technology, _d2009. _nMode of access: World Wide Web. _nSystem requirements: Web browser. _nTitle from title screen (viewed on Apr. 10, 2009). _nAccess may be restricted to users at subscribing institutions.
650		0	_aCredit ratings.
650		0	_aCredit _xManagement.
650		0	_aCredit _xManagement _xMathematical models.
650		0	_aRisk management.
655		7	_aElectronic books. _2local
700	1		_aRachev, S. T. _q(Svetlozar Todorov)
710	2		_aScienceDirect (Online service)
776	1		_cOriginal _z9780123736833 _z0123736838 _w(OCoLC)263294158
856	4	0	_3ScienceDirect _uhttp://www.sciencedirect.com/science/book/9780123736833 _zAn electronic book accessible through the World Wide Web; click for information
856	4	2	_3Publisher description _uhttp://www.loc.gov/catdir/enhancements/fy0913/2009417734-d.html
902			_a1
905			_aEman _eRev.
905			_aJamal _eCat.
942			_2ddc _cBK
999			_c122162 _d122162