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"The latest volume in the Springer Handbooks of Computational Statistics series covers the full range of finance, including the modern class of financial tools, computational efficient algorithms, the pricing of complex products, risk behavior and much more. "

"Like its three predecessors, this fourth volume in its series covers cutting-edge natural computing and agent-based methodologies in computational finance and economics, option model calibration, financial trend reversal detection, algorithmic trading and more."

"This book is very easy to read and one can gain a quick snapshot of computational issues arising in financial mathematics. SIAM review (46, 2004). The fourth edition is thoroughly revised and extended. Major revisions concern topics like calibration, Monte Carlo Methods, American options, exotic options and Algorithms for Bermuda Options. New figures, more exercises, more background material make this guide to the world of financial engineering a real must-to-have for everyone working in FE. "

"An introduction to the mathematics of finance : a deterministic approach, offers a highly illustrated introduction to mathematical finance, with a special emphasis on interest rates. This revision of the McCutcheon-Scott classic follows the core subjects covered by the first professional exam required of UK actuaries, the CT1 exam. It realigns the table of contents with the CT1 exam and includes sample questions from past exams of both The Actuarial Profession and the CFA Institute. With a wealth of solved problems and interesting applications, An Introduction to the Mathematics of Finance stands alone in its ability to address the needs of its primary target audience, the actuarial student."

"Based on presentations given at the workshop Numerical methods in finance held at the INRIA Bordeaux (France) on June 1-2, 2010, this book provides an overview of the major new advances in the numerical treatment of instruments with American exercises. Naturally it covers the most recent research on the mathematical theory and the practical applications of optimal stopping problems as they relate to financial applications. By extension, it also provides an original treatment of Monte Carlo methods for the recursive computation of conditional expectations and solutions of BSDEs and generalized multiple optimal stopping problems and their applications to the valuation of energy derivatives and assets. The book is geared toward quantitative analysts, probabilists, and applied mathematicians interested in financial applications."

"This book concentrates on discrete derivative pricing models, culminating in a careful and complete derivation of the Black-Scholes option pricing formulas as a limiting case of the Cox-Ross-Rubinstein discrete model. In this edition the material on probability has been condensed into fewer chapters, and the material on the capital asset pricing model has been removed. The mathematics is not watered down, but it is appropriate for the intended audience. Previous knowledge of measure theory is not needed and only a small amount of linear algebra is required. All necessary probability theory is developed throughout the book on a "need-to-know" basis. No background in finance is required, since the book contains a chapter on options. "