Frank Fabozzi – författare

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.

The definitive guide to fixed income securities―updated and revised with everything you need to succeed in today’s market

The Handbook of Fixed Income Securities has been the most trusted resource for fixed income investing for decades, providing everything sophisticated investors need to analyze, value, and manage fixed income instruments and their derivatives. 

But this market has changed dramatically since the last edition was published, so the author has revised and updated his classic guide to put you ahead of the curve. With chapters written by the leading experts in their fields, The Handbook of Fixed Income Securities, Ninth Edition provides expert discussions about:

The Handbook of Fixed Income Securities is the most inclusive, up-to-date source available for fixed income facts and analyses. Its invaluable perspective and insights will help you enhance investment returns and avoid poor performance in the fixed income market.

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:

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)