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Binomial Models in Finance (Springer Finance), by John van der Hoek, Robert J Elliott
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This book describes the modelling of prices of ?nancial assets in a simple d- crete time, discrete state, binomial framework. By avoiding the mathematical technicalitiesofcontinuoustime?nancewehopewehavemadethematerial accessible to a wide audience. Some of the developments and formulae appear here for the ?rst time in book form. We hope our book will appeal to various audiences. These include MBA s- dents,upperlevelundergraduatestudents,beginningdoctoralstudents,qu- titative analysts at a basic level and senior executives who seek material on new developments in ?nance at an accessible level. The basic building block in our book is the one-step binomial model where a known price today can take one of two possible values at a future time, which might, for example, be tomorrow, or next month, or next year. In this simple situation “risk neutral pricing” can be de?ned and the model can be applied to price forward contracts, exchange rate contracts and interest rate derivatives. In a few places we discuss multinomial models to explain the notions of incomplete markets and how pricing can be viewed in such a context, where unique prices are no longer available. The simple one-period framework can then be extended to multi-period m- els.TheCox-Ross-RubinsteinapproximationtotheBlackScholesoptionpr- ing formula is an immediate consequence. American, barrier and exotic - tions can all be discussed and priced using binomial models. More precise modelling issues such as implied volatility trees and implied binomial trees are treated, as well as interest rate models like those due to Ho and Lee; and Black, Derman and Toy.
- Sales Rank: #3373803 in Books
- Published on: 2005-12-08
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x .75" w x 6.14" l, 1.23 pounds
- Binding: Hardcover
- 306 pages
Review
From the reviews:
"Overall, this is an excellent 'workbook' for practitioners who seek to understand and apply financial asset price models by working through a comprehensive collection of both theoretical and dataset-driven numerical examples, follwoed by up to 15 end-of-chapter exercises with elaborated parts taht help clarify the mathematical and computational aspects of the chapter." Wai F. Chiu for the Journal of the American Statistical Association, December 2006
"This is a textbook on the mathematics of pricing and hedging financial derivatives with discrete stochastic models. It is directed towards a readership that is interested in the principles and applications of mathematical finance … . A nice feature is the very clear descriptions of financial terms, which, on the one hand, are often missing in more mathematics-oriented books and, on the other hand, can be somewhat imprecise in textbooks aiming at the business community." (A. Schied, Short Book Reviews, Vol. 26 (2), 2006)
"The book is written by leading specialists in modern stochastic financial modeling. … The book is well written, with a good balance between mathematical tools and arguments and financial topics. It is nice to see proofs of several important properties of financial characteristics and rules for option pricing. Specific numerical examples are given to illustrate ideas and rules. … Without any reservations the book can be strongly recommended not only to institutional libraries but also to anybody working or with interests in stochastic financial modeling." (Jordan M. Stoyanov, Zentralblatt MATH, Vol. 1107 (9), 2007)
From the Back Cover
This book deals with many topics in modern financial mathematics in a way that does not use advanced mathematical tools and shows how these models can be numerically implemented in a practical way. The book is aimed at undergraduate students, MBA students, and executives who wish to understand and apply financial models in the spreadsheet computing environment.
The basic building block is the one-step binomial model where a known price today can take one of two possible values at the next time. In this simple situation, risk neutral pricing can be defined and the model can be applied to price forward contracts, exchange rate contracts, and interest rate derivatives. The simple one-period framework can then be extended to multi-period models. The authors show how binomial tree models can be constructed for several applications to bring about valuations consistent with market prices. The book closes with a novel discussion of real options.
John van der Hoek is Senior Lecturer in Applied Mathematics at the University of Adelaide. He has developed courses in finance for a number of years at various levels and is a regular plenary speaker at major conferences on Quantitative Finance.
Robert J. Elliott is RBC Financial Group Professor of Finance at the Haskayne School of Business at the University of Calgary. He is the author of over 300 research papers and several books, including Mathematics of Financial Markets, Second Edition (with P. Ekkehard Kopp), Stochastic Calculus and Applications, Hidden Markov Models (with Lahkdar Aggoun and John Moore) and Measure Theory and Filtering: Theory and Applications (with Lakhdar Aggoun). He is an Associate Editor of Mathematical Finance, Stochastics and Stochastics Reports, Stochastic Analysis and Applications, and the Canadian Applied Mathematics Quarterly.
Most helpful customer reviews
0 of 4 people found the following review helpful.
appendix needs correction
By A Reader from New Jersey
This is not a thorough review. I just want to point out a correction in the appendix on linear programming. At the very end, the authors give a linear programming formulation for computing a super-hedging price for a contingent claim using a linear programming formulation under proportional transaction costs. Since this introduces a non-linearity due to an absolute value term, they propose to replace this by complementarity constraints or equivalently by binary variables and linear inequalities leading to mixed-integer LPs of increased difficulty. All this is unnecessary. There are modeling tricks to reformulate the problem as a linear program by adding auxiliary variables and constraints. It suffices to check the paper by Edirisinghe, Naik and Uppal, JFQA 1993.
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