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Detalles de la obra

Título:
Quantitative risk management
Subtítulo:
concepts, techniques and tools
Autor(es):
McNeil, Alexander; Frey, Rüdiger; Embrechts, Paul
Pie de imprenta:
Princeton: Princeton University, c2015
Edición:
rev.ed.
Descripción física:
xix, 699 p. grafs. 26 x 18 cm.
Idioma:
Inglés
ISBN:
978-0-691-16627-8
Resumen:
Contiene: I. An introduction to quantitative risk management. 1 risk in perspective. 1.1. Risk. 1.2. A brief history of risk management. 1.3. The regulatory framework. 1.4. Why manage financial risk? 1.5. Quantitative risk management. 2. Basic concepts in risk management. 2.1. Risk management for a financial firm. 2.2. Modelling value and value change. 2.3. Risk measurement. 3. Empirical properties of financial data. 3.1. Stylized facts of financial return series. 3.2. Multivariate stylized facts.- ii. Methodology. 4. Financial time series. 4.1. Fundamentals of time series analysis. 4.2. GARCH models for changing volatility. 5. Extreme value theory. 5.1. Maxima. 5.2. Threshold exceedances. 5.3. Point process models. 6. Multivariate models. 6.1. Basics of multivariate modeling. 6.2. Normal mixture distributions. 6.3. Spherical and elliptical distributions. 6.4. Dimension-reduction techniques. 7. Copulas and dependence. 7.1. Copulas. 7.2. Dependence concepts and measures. 7.3. Normal mixture copulas. 7.4. Archimedean copulas. 7.5. Fitting copulas to data. 8. Aggregate risk. 8.1. Coherent and convex risk measures. 8.2. Law-invariant coherent risk measures. 8.3. Risk measures for linear portfolios. 8.4. Risk aggregation. 8.5. Capital allocation.- III. Applications. 9. Market risk. 9.1. Risk factors and mapping. 9.2. Market risk measurement. 9.3. Backtesting. 10. Credit risk. 10.1. Credit-risky instruments. 10.2. Measuring credit quality. 10.3. Structural models of default. 10.4. Bond and cds pricing in Hazard rate models. 10.5. Pricing with stochastic Hazard rates. 10.6. Affine models. 11. Portfolio credit risk management. 11.1. Threshold models. 11.2. Mixture models. 11.3. Asymptotics for large portfolios. 11.4. Monte Carlo methods. 11.5. Statistical inference in portfolio credit models. 12. Portfolio credit derivatives. 12.1. Credit portfolio products. 12.2. Copula models. 12.3. Pricing of index derivatives in factor copula models. 13. Operational risk and insurance analytics. 13.1. Operational risk in perspective. 13.2. Elements of insurance analytics.- IV. Special topics. 14. Multivariate time series. 14.1. Fundamentals of multivariate time series. 14.2. Multivariate garch processes. 15. Advanced topics in multivariate modeling. 15.1. Normal mixture and elliptical distributions. 15.2. Advanced Archimedean copula models. 16. Advanced topics in extreme value theory. 16.1. Tails of specific models. 16.2. Self-exciting models for extremes. 16.3. Multivariate maxima. 16.4. Multivariate threshold exceedances. 17. Dynamic portfolio credit risk models and counterparty risk. 17.1. Dynamic portfolio credit risk models. 17.2. Counterparty credit risk management. 17.3. Conditionally independent default times. 17.4. Credit risk models with incomplete information.
Referencias bibliográficas:
Incluye Bibliografía
Título serie:
Princeton series in finance
Ubicación física:
658.155 / MCN - RIESGO
Tipo de material:
[Material Impreso]