The definitive guide to fixed income securities-updated and revised with everything you need to succeed in today's market For nearly 40 years, The Handbook of Fixed Income Securities has been providing comprehensive, current, reliable information on everything investors like you need to stay on top of the market and ahead of the curve. The fixed income market has changed dramatically in the past decade. This updated classic brings you fully up to date for a much-changed world of finance, where central banks play a bigger role, interest is low (and sometimes even in negative territory), regulations are more complex, and new types of securities have been created. Brand-new chapters cover: Relative value trades Muni analytics Financial data science Building and maintaining a bond portfolio Factor investing Relative value trades Smart beta fixed income Infrastructure and green bonds Sovereign bond markets One of the world's leading experts on fixed income securities, Frank Fabozzi has gathered a peerless team of global experts who provide the newest and best techniques for winning in today's markets. Fixed Income Securities, Ninth Edition is a matchless, one-stop resource for all your professional needs.

This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit theorems and generally in assessing the quality of approximations to a given probabilistic model. The method of metric distances is developed to study stability problems and reduces to the selection of an ideal or the most appropriate metric for the problem under consideration and a comparison of probability metrics. After describing the basic structure of probability metrics and providing an analysis of the topologies in the space of probability measures generated by different types of probability metrics, the authors study stability problems by providing a characterization of the ideal metrics for a given problem and investigating the main relationships between different types of probability metrics. The presentation is provided in a general form, although specific cases are considered as they arise in the process of finding supplementary bounds or in applications to important special cases. Svetlozar T. Rachev is the Frey Family Foundation Chair of Quantitative Finance, Department of Applied Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of Finanlytica, USA. Lev B. Klebanov is a Professor in the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC Business School and Head of Research, EDHEC-Risk Institute-Asia (Singapore). Frank J. Fabozzi is a Professor at EDHEC Business School. (USA)

This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit theorems and generally in assessing the quality of approximations to a given probabilistic model. The method of metric distances is developed to study stability problems and reduces to the selection of an ideal or the most appropriate metric for the problem under consideration and a comparison of probability metrics. After describing the basic structure of probability metrics and providing an analysis of the topologies in the space of probability measures generated by different types of probability metrics, the authors study stability problems by providing a characterization of the ideal metrics for a given problem and investigating the main relationships between different types of probability metrics. The presentation is provided in a general form, although specific cases are considered as they arise in the process of finding supplementary bounds or in applications to important special cases. Svetlozar T. Rachev is the Frey Family Foundation Chair of Quantitative Finance, Department of Applied Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of Finanlytica, USA. Lev B. Klebanov is a Professor in the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC Business School and Head of Research, EDHEC-Risk Institute-Asia (Singapore). Frank J. Fabozzi is a Professor at EDHEC Business School. (USA)

The brand-new edition of this classic guide for high-level investors covers the latest tools and techniques for dealing with all aspects of fixed-income portfolio management Fixed Income Mathematics is known around the world as the leading guide to understanding the concepts and evaluative methodologies for bonds, mortgage-backed securities, asset-backed securities, and other fixed income instruments-and the fifth edition gets you up to date on the newest analytical frameworks. 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 numerous 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, Descriptive Measures, 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 The concepts and methodologies for evaluating fixed income securities have changed dramatically over the past 15 years. This edition explains the numbers behind these changes and provides the knowledge you need to consistently control both the cost and risk of investing in debt.

A contributed handbook on the complexities of portfolio management that includes the most up-to-date findings from leading practitioners in the fixed income securities market.

Fractional Calculus and Fractional Processes with Applications to Financial Economics presents the theory and application of fractional calculus and fractional processes to financial data. Fractional calculus dates back to 1695 when Gottfried Wilhelm Leibniz first suggested the possibility of fractional derivatives. Research on fractional calculus started in full earnest in the second half of the twentieth century. The fractional paradigm applies not only to calculus, but also to stochastic processes, used in many applications in financial economics such as modelling volatility, interest rates, and modelling high-frequency data. The key features of fractional processes that make them interesting are long-range memory, path-dependence, non-Markovian properties, self-similarity, fractal paths, and anomalous diffusion behaviour. In this book, the authors discuss how fractional calculus and fractional processes are used in financial modelling and finance economic theory. It provides a practical guide that can be useful for students, researchers, and quantitative asset and risk managers interested in applying fractional calculus and fractional processes to asset pricing, financial time-series analysis, stochastic volatility modelling, and portfolio optimization.