
Introduction to the Mathematics of Finance
R. J. Williams(Author)
American Mathematical Society (Publisher)
Will be published approx. on 31. January 2006
Book
Paperback/Softback
150 pages
978-1-4704-6038-9 (ISBN)
Description
The modern subject of mathematical finance has undergone considerable development, both in theory and practice, since the seminal work of Black and Scholes appeared a third of a century ago. This book is intended as an introduction to some elements of the theory that will enable students and researchers to go on to read more advanced texts and research papers.
The book begins with the development of the basic ideas of hedging and pricing of European and American derivatives in the discrete (i.e., discrete time and discrete state) setting of binomial tree models. Then a general discrete finite market model is introduced, and the fundamental theorems of asset pricing are proved in this setting. Tools from probability such as conditional expectation, filtration, (super)martingale, equivalent martingale measure, and martingale representation are all used first in this simple discrete framework. This provides a bridge to the continuous (time and state) setting, which requires the additional concepts of Brownian motion and stochastic calculus. The simplest model in the continuous setting is the famous Black-Scholes model, for which pricing and hedging of European and American derivatives are developed. The book concludes with a description of the fundamental theorems for a continuous market model that generalizes the simple Black-Scholes model in several directions.
The book begins with the development of the basic ideas of hedging and pricing of European and American derivatives in the discrete (i.e., discrete time and discrete state) setting of binomial tree models. Then a general discrete finite market model is introduced, and the fundamental theorems of asset pricing are proved in this setting. Tools from probability such as conditional expectation, filtration, (super)martingale, equivalent martingale measure, and martingale representation are all used first in this simple discrete framework. This provides a bridge to the continuous (time and state) setting, which requires the additional concepts of Brownian motion and stochastic calculus. The simplest model in the continuous setting is the famous Black-Scholes model, for which pricing and hedging of European and American derivatives are developed. The book concludes with a description of the fundamental theorems for a continuous market model that generalizes the simple Black-Scholes model in several directions.
Reviews / Votes
"This monograph gives a far-reaching and easily readable advanced introduction to the mathematical modelling of the absence of riskless financial profits, as well as to the connected topic of pricing and risk-protecting-replication/hedging of securities whose value depend on an underlying asset. ...The book's style is pragmatic, precise, concise, with smoothly and fast increasing technical level including the quotation of mathematical subtleties." - Wolfgang Stummer"The text is clearly written and well-arranged and most of the results are proved in detail. Each chapter is completed with exercises, which makes the textbook very comprehensive." - EMS Newsletter
More details
Series
Language
English
Place of publication
Providence
United States
Target group
Professional and scholarly
ISBN-13
978-1-4704-6038-9 (9781470460389)
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Schweitzer Classification
Person
R. J. Williams, University of California, San Diego, La Jolla, CA.
Content
Financial markets and derivatives
Binomial model
Finite market model
Black-Scholes model
Multi-dimensional Black-Scholes model
Conditional expectation and $L^p$-spaces
Discrete time stochastic processes
Continuous time stochastic processes
Brownian motion and stochastic integration
Bibliography
Index
Binomial model
Finite market model
Black-Scholes model
Multi-dimensional Black-Scholes model
Conditional expectation and $L^p$-spaces
Discrete time stochastic processes
Continuous time stochastic processes
Brownian motion and stochastic integration
Bibliography
Index