Tools for Computational Finance
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Beschreibung
This book offers a snapshot of computational issues arising in financial mathematics. The new third edition is thoroughly revised and extended, adding a new section on analytic methods. This is a must-to-have for everyone working in the world of financial engineering.
Basic principles underlying the transactions of financial markets are tied to probability and statistics. Accordingly it is natural that books devoted to mathematical finance are dominated by stochastic methods. Only in recent years, spurred by the enormous economical success of financial derivatives, a need for sophisticated computational technology has developed. For ex ample, to price an American put, quantitative analysts have asked for the numerical solution of a free-boundary partial differential equation. Fast and accurate numerical algorithms have become essential tools to price financial derivatives and to manage portfolio risks. The required methods aggregate to the new field of Computational Finance. This discipline still has an aura of mysteriousness; the first specialists were sometimes called rocket scientists. So far, the emerging field of computational finance has hardly been discussed in the mathematical finance literature. This book attempts to fill the gap. Basic principles of computational finance are introduced in a monograph with textbook character. The book is divided into four parts, arranged in six chapters and seven appendices. The general organization is Part I (Chapter 1): Financial and Stochastic Background Part II (Chapters 2, 3): Tools for Simulation Part III (Chapters 4, 5, 6): Partial Differential Equations for Options Part IV (Appendices A1 ... A7): Further Requisits and Additional Material.
Covers on an introductory level the very important issue of computational aspects of derivative pricing
People with a solid background of stochastics, numerics and derivative pricing will gain an immediate profit
This easy-to-read book offers a snapshot of computational issues arising in financial mathematics. The new third edition is thoroughly revised and significantly extended. The largest addition is a new section on analytic methods, focused mainly on interpolation approach and quadratic approximation. New sections and subsections are devoted to risk-neutrality, early-exercise curves, multidimensional Black-Scholes models, the integral representation of options and the derivation of the Black-Scholes equation. New figures, numerous exercises, and the addition of more background material make this guide a real must-to-have for everyone working in the world of financial engineering.
Autor*in
Rüdiger U. Seydel
Themen in »Tools for Computational Finance«
Derivative pricing Finance Numerical integration Optionen Stochastic Differential Equations derivatives differential equation exotische Optionen financial markets finite element method mathematical finance numerics probability rating statistics
Stimmen zu »Tools for Computational Finance«
"In an increasingly crowded field of financial engineering titles, Seydel's Tools for Computational Finance stands out as filling an unmet need. It is an intermediate level text with an extremely practical focus. ... This is the kind of book you can read quickly, gaining a broad understanding of practical techniques of financial engineering. On the other hand, you can go through it slowly, working through all the examples and exercises in order to gain indepth practical knowledge you can use on the job. "
www.riskbook.com
"Remarkably, Seydel addresses students of both mathematics and business, presumes only minimal background in either subject, yet ventures deep into the subject in little more than 200 pages. Compare the longer books Mathematics of Financial Markets, by R.J. Elliott and P.E. Kopp (1999), or Methods of Mathematical Finance, by I. Karatzas and S.E. Shreve (1998), which presume research-level preparation in probability theory, delve deeper into theoretical issues, but ignore numerics. On the mathematical side, Seydel covers stochastic processes, random number generation, stochastic differential equations, finite differences, and finite elements. On the financial side, he treats put and call options of so-called American, European, and Asian types. A Web site provides additional material, including colored figures. Summing Up: Highly recommended. "
CHOICE
"Seydel has sought a compromise between justifying his results and avoiding formal proofs. I think he has struck a healthy balance, and I enjoyed reading the book.
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Hull´s book teaches how to write the equations and Seydel´s teaches how to solve them"
Physics Today
"In my opinion, this book is mainly tailored to financial researchers and practitioners with an applied mathematics or engineering background. Various methods are introduced from a problem-solving point of view, been eventually formulated and summarised as algorithms which are offered for straightforward implementation in computer programmes. This expository style, which is similar to Kloeden´s and Platen´s 'Numerical Solutions of SDEs through computer experiments', makes the book unique among others and will definitely attract a broad range of readers coming from the financial academia or practice.
Quant Notes
"This book is very easy to read and one can gain a quick snapshot of computational issues arising in financial mathematics. Researchers or students of the mathematical sciences with an interest in finance will find this book a very helpful and gentle guide to the world of financial engineering."
SIAM review (46, 2004)
From the reviews of the third edition:
"Tools for Computational Finance is a book on numerical methods for pricing financial derivative products. … the author concentrates on how to provide numerical solutions to the problem of pricing. Exercises are provided at the end of each chapter and they follow and complement the text very well. In my opinion the book is more for practitioners … . it does guide us in a right direction and I think it could be valuable even for an academic." (Ita Cirovic Doney, MathDL-online, October, 2006)
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