Quantitative Business Tool with Application

Praise for Quantitative Methods in Derivatives Pricing "Tavella’ s text is ideal for a course on computational methods in finance. I cannot think of a better book for the purpose. The writing is clear and intuitive. The marriage of mathematical methods and financial applications is just right for a first course on the topic, especially with the excellent working examples for Monte Carlo and finite-difference methods." -Darrell Duffie, Professor of Finance Stanford University "This is a masterful and detailed survey of the fundamental tools and techniques available to financial engineers." -Francis Longstaff, Professor of Finance, UCLA "Quantitative Methods in Derivatives Pricing is a valuable addition to the books available to the beginning graduate student or practitioner. As well as containing a nice treatment of the theoretical principles of modern financial derivatives, it is the first to stress the fundamentals of the wide variety of computational algorithms used for pricing and hedging. Unlike many of its competitors, it is succinct and clearly written." -M. A. H. Dempster, Professor of Finance and Director Centre for Financial Research, Cambridge University "This textbook provides a superb introduction to quantitative derivative pricing techniques that is a must read for MFE students. Domingo Tavella develops a uniform framework for derivative valuation in terms of computing expectations. He then analyzes the pricing theory and practice using simulation and finite differences. Readers will find unique insights into implementation issues associated with these state-of-the-art pricing techniques.

Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations. The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.

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