Fixed Income Mathematics, Fifth Edition: Analytical and Statistical Techniques
Language: English
Published by McGraw Hill, 2022
- Hardcover
- New
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- Title
- Fixed Income Mathematics, Fifth Edition: Analytical and Statistical Techniques
- Author
- Fabozzi, Frank J.; Fabozzi, Francesco
- Publisher
- McGraw Hill
- Publication year
- 2022
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1264258275
- ISBN 13
- 9781264258277
- Edition
- 5th or later Edition
The standard reference for fixed income portfolio managers―fully updated with new analytical frameworks
Fixed Income Mathematics is known around the world as the leading guide to understanding the concepts, valuation models for bonds with embedded option, mortgage-backed securities, asset-backed securities, and other fixed income instruments, and portfolio analytics.
Fixed Income Mathematics begins with basic concepts of the mathematics of finance, then systematically builds on them to reveal state-of-the-art methodologies for evaluating them and managing fixed-income portfolios. Concepts are illustrated with numerical examples and graphs, and you need only a basic knowledge of elementary algebra to understand them.
This new edition includes several entirely new chapters―Risk-Adjusted Returns, Empirical Duration, Analysis of Floating-Rate Securities, Holdings-Based Return Attribution Analysis, Returns-Based Style Attribution Analysis, Measuring Bond Liquidity, and Machine Learning―and provides substantially revised chapters on:
- Interest rate modeling
- Probability theory
- Optimization models and applications to bond portfolio management
- Historical return measures
- Measuring historical return volatility
"Synopsis" may belong to another edition of this title.
About the Author
Francesco A. Fabozzi is the managing editor of The Journal of Financial Data Science and the director of Data Science for the CFA Institute Research Foundation. He has worked as a research associate at NYU’s Courant Institute in the Department of Mathematical Finance and is on the Curriculum Board of the Financial Data Professionals Institution. He has coauthored several books on asset management. He earned an undergraduate degree in economics from Princeton University, a master’s degree in Financial Analytics from the Stevens Institute of Technology, where he is an ABD doctoral student in data science.
"About the title" may belong to another edition of this title.
Ria Christie Collections
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