Description
Book SynopsisFixed Income Modelling offers a unified presentation of dynamic term structure models and their applications to the pricing and risk management of fixed income securities. It explains the basic fixed income securities and their properties and uses as well as the relations between those securities. The book presents and compares the classical affine models, Heath-Jarrow-Morton models, and LIBOR market models, and demonstrates how to apply those models for the pricing of various widely traded fixed income securities. It offers a balanced presentation with both formal mathematical modelling and economic intuition and understanding. The book has a number of distinctive features including a thorough and accessible introduction to stochastic processes and the stochastic calculus needed for the modern financial modelling approach used in the book, as well as a separate chapter that explains how the term structure of interest rates relates to macro-economic variables and to what extent the con
Trade ReviewI enjoyed reading the book. Claus Munk manages to present many demanding topics in a very clear and understandable way. The book is well suited as a textbook on fixed income for advanced finance students. I also recommend reading to researchers and finance professionals. * Antje Mahayni, Journal of Economics October 2012, Volume 107, Issue 2, pp 195-197 *
Table of ContentsPreface ; 1. Introduction and overview ; 2. Extracting Yield Curves from Bond Prices ; 3. Stochastic Processes and Stochastic Calculus ; 4. A Review of General Asset Pricing Theory ; 5. The Economics of the Term Structure of Interest Rates ; 6. Fixed Income Securities ; 7. One-factor Diffusion Models ; 8. Multi-factor Diffusion Models ; 9. Calibration of Diffusion Models ; 10. Heath-Jarrow-Morton Models ; 11. Market models ; 12. The Measurement and Management of Interest Rate Risk ; 13. Defaultable Bonds and Credit Derivatives ; 14. Mortgages and Mortgage-backed Securities ; 15. Stock and Currency Derivatives when Interest Rates are Stochastic ; 16. Numerical Techniques ; Appendix: Results on the Lognormal Distribution
