The three volumes of Interest Rate Modeling present a comprehensive and up-to-date treatment of techniques and models used in the pricing and risk management of fixed income securities. Written by two leading practitioners and seasoned industry veterans, this unique series combines finance theory, numerical methods, and approximation techniques to provide the reader with an integrated approach to the process of designing and implementing industrial-strength models for fixed income security valuation and hedging. Aiming to bridge the gap between advanced theoretical models and real-life trading applications, the pragmatic, yet rigorous, approach taken in this book will appeal to students, academics, and professionals working in quantitative finance. Volume I provides the theoretical and computational foundations for the series, emphasizing the construction of efficient grid- and simulation-based methods for contingent claims pricing. The second part of Volume I is dedicated to local-stochastic volatility modeling and to the construction of vanilla models for individual swap and Libor rates. Although the focus is eventually turned toward fixed income securities, much of the material in this volume applies to generic financial markets and will be of interest to anybody working in the general area of asset pricing. Interest rate modeling piterbarg pdf - so do eat interest rate modeling piterbarg Leif B G. Andersen, Vladimir V. Piterbarg Vladimir rate volume leif is. Interest Rate Modeling. Volume 3: Products and Risk Management – Leif B.G. Andersen & Vladimir V. Interest Rate Modeling. Volume 3: Products and Risk Management Leif B.G. Andersen, Vladimir V. Piterbarg Type: eBook Released: 2010 Publisher: Atlantic Financial Press Page Count: 548 Format: pdf Language: English ISBN-10: ISBN-13: 128 Review Andersen and Piterbarg have written a Landau and Lifschitz of fixed income analytics. --Alexander Lipton-Lifschitz, Co-Head of the Global Quantitative Group, Bank of America Merrill Lynch The authors bring a matchless combination of theoretical and practical expertise to these volumes. The result is a masterwork: truly insightful, inexhaustible in rigor, and terrifyingly complete in scope. --Tom Hyer, Head of Quant Analytics, UBS Written by two of the sharpest mathematical minds in the industry, the theoretical presentation is precise, the scope is comprehensive, and the implementation details reflect ample experience --Steven Shreve, Professor of Mathematics, Carnegie Mellon From the Author From PrefaceFor quantitative researchers working in an investment bank, the process of writing a fixed income model usually has two stages. First, a theoretical framework for yield curve dynamics is specified, using the language of mathematics (especially stochastic calculus) to ensure that the underlying model is well-specified and internally consistent. Second, in order to use the model in practice, the equations arising from the first step need to be turned into a working implementation on a computer. While specification of the theoretical model may be seen as the difficult part, in quantitative finance applications the second step is technically and intellectually often more challenging than the first. In the implementation phase, not only does one need to translate abstract ideas into computer code, one also needs to ensure that the resulting numbers being produced are meaningful to a trading desk, are stable and robust, are in line with market observations, and are produced in a timely manner. Many of these requirements are, as it turns out, extremely challenging, and not only demand a strong knowledge of actual market practices (which tend to deviate in significant ways from ``textbook' theory), but also require application of a large arsenal of techniques from applied mathematics, chiefly approximation methods and numerical techniques. While there are many good introductory books on fixed income derivatives on the market, when we hire people who have read them we find that they still require significant training before they become productive members of our quantitative research teams.
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