Numerical methods in finance has recently emerged as a new discipline at the intersection of probability theory, finance and numerical analysis. This book describes a wide variety of numerical methods used in financial analysis: computation of option prices, especially American option prices, by finite difference and other methods; numerical solution of portfolio management strategies; statistical procedures, identification of models; Monte Carlo methods; and numerical implications of stochastic volatilities. Lucid and concise, it covers both mathematical matters and practical issues in numerical problems. This book is an ideal resource for economists, probabilists and applied mathematicians working in finance.
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Review of the hardback: '... the book can be strongly recommended to economists, probabilists, and applied mathematics working in finance.' European Mathematical Society
Book Description
Numerical Methods in Finance has recently emerged as a new discipline at the intersection of probability theory, finance and numerical analysis. This book describes a wide variety of numerical methods used in financial analysis. Articles have been written in a pedagogic style and made reasonably self-contained, covering both mathematical matters and practical issues in numerical problems. Thus the book has something to offer economists, probabilists and applied mathematicians working in finance, for all of whom this will be the only up-to-date reference on the subject.
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This review is from: Numerical Methods in Finance (Publications of the Newton Institute) (Hardcover)
This is another master piece from the Newton Institute following the Mathematics of Derivative Securities. However, the title is rather misleading as the book offers very few details in computer implementation and techniques.
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Inside This Book
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First Sentence:
The aim of this article is twofold: on one hand, we describe a general convergence result which applies to a wide range of numerical schemes ('monotone schemes') for nonlinear possibly degenerate elliptic (or parabolic) equation; this type of equation arises naturally in Finance Theory as we will show first. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
bearish bounds, pricing delta, active hedge, recursive utility, large deviations approximation, optimal exercise boundary, recursive utilities, backward stochastic differential equations, financing shortfall, binomial method, implicit volatility, viscosity subsolution, dynamic programming principle, lookback options, two intersection points, hedge portfolio, stochastic volatility models, discrete maximum principle, one intersection point, representation formulae, control variate, linear complementarity problem, per put, large deviations theory, comparison theorem Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Springer Verlag, Journal of Finance, Mathematical Finance, Academic Press, Journal of Financial Economics, Mean Rel, Root Mean Sqr, Stock Time, Journal of Derivatives, Mean Abs, Columbia University, Proof of Theorem, Stanford University, Annals of Applied Probability, Applied Mathematics, Cornell University, Graduate School of Business, Journal of Economic Theory, Journal of Political Economy, Lecture Notes, Long Term Put Values, Short Term Put Values, Acta Applzcandae Mathematzcae, Journal of Econometrics New!
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The aim of this article is twofold: on one hand, we describe a general convergence result which applies to a wide range of numerical schemes ('monotone schemes') for nonlinear possibly degenerate elliptic (or parabolic) equation; this type of equation arises naturally in Finance Theory as we will show first. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
bearish bounds, pricing delta, active hedge, recursive utility, large deviations approximation, optimal exercise boundary, recursive utilities, backward stochastic differential equations, financing shortfall, binomial method, implicit volatility, viscosity subsolution, dynamic programming principle, lookback options, two intersection points, hedge portfolio, stochastic volatility models, discrete maximum principle, one intersection point, representation formulae, control variate, linear complementarity problem, per put, large deviations theory, comparison theorem Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Springer Verlag, Journal of Finance, Mathematical Finance, Academic Press, Journal of Financial Economics, Mean Rel, Root Mean Sqr, Stock Time, Journal of Derivatives, Mean Abs, Columbia University, Proof of Theorem, Stanford University, Annals of Applied Probability, Applied Mathematics, Cornell University, Graduate School of Business, Journal of Economic Theory, Journal of Political Economy, Lecture Notes, Long Term Put Values, Short Term Put Values, Acta Applzcandae Mathematzcae, Journal of Econometrics New!
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Front Cover | Front Flap | Table of Contents | First Pages | Back Flap | Back Cover | Surprise Me!
Citations (learn more)
This book cites 32
books:
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25
books
cite this book:
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- Brownian Motion and Stochastic Calculus (Graduate Texts in Mathematics) by Ioannis Karatzas on 4 pages
- Advances in Futures and Options Research, Volume 9 (Advances in Futures and Options Research) (Advances in Futures and Options Research) by Peter Ritchken on page 64, page 65, and page 87
- Difference Methods and Their Extrapolations (Stochastic Modelling and Applied Probability) by G.I. Marchuk on page 64, and page 87
- Applied Stochastic Analysis (Stochastics Monographs) by M. H.a. Davis on page 163, and page 212
- Mathematical Finance (The IMA Volumes in Mathematics and its Applications) by Mark H.A. Davis on page 163, and page 212
See all 32 books this book cites
- Weak Convergence of Financial Markets by Jean-Luc Prigent on 4 pages
- Martingale Methods in Financial Modelling (Stochastic Modelling and Applied Probability) by Marek Musiela in Back Matter (1), Back Matter (2), and Back Matter (3)
- Handbook of Stochastic Analysis & Applications (Statistics: A Series of Textbooks and Monographs) by D. Kannan on page 336, and page 353
- Monte Carlo and Quasi-Monte Carlo Methods 2002: Proceedings of a Conference held at the National University of Singapore, Republic of Singapore, November 25-28, 2002 by Harald Niederreiter on page 125, and page 126
- Essays in Derivatives (Frank J. Fabozzi Series) by Don M. Chance on page 94, and Back Matter
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