Monte Carlo Methods in Financial Engineering / Edition 1

Monte Carlo Methods in Financial Engineering / Edition 1

by Paul Glasserman
ISBN-10:
1441918221
ISBN-13:
9781441918222
Pub. Date:
11/19/2010
Publisher:
Springer New York
ISBN-10:
1441918221
ISBN-13:
9781441918222
Pub. Date:
11/19/2010
Publisher:
Springer New York
Monte Carlo Methods in Financial Engineering / Edition 1

Monte Carlo Methods in Financial Engineering / Edition 1

by Paul Glasserman
$64.99
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Overview

Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques.

This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency. The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios.

The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of shastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential.

The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry.

Mathematical Reviews, 2004: "... this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context."


Product Details

ISBN-13: 9781441918222
Publisher: Springer New York
Publication date: 11/19/2010
Series: Stochastic Modelling and Applied Probability , #53
Edition description: Softcover reprint of hardcover 1st ed. 2003
Pages: 596
Product dimensions: 6.10(w) x 9.20(h) x 1.30(d)

Table of Contents

1 Foundations.- 2 Generating Random Numbers and Random Variables.- 3 Generating Sample Paths.- 4 Variance Reduction Techniques.- 5 Quasi-Monte Carlo.- 6 Discretization Methods.- 7 Estimating Sensitivities.- 8 Pricing American Options.- 9 Applications in Risk Management.- A Appendix: Convergence and Confidence Intervals.- A.1 Convergence Concepts.- A.2 Central Limit Theorem and Confidence Intervals.- B Appendix: Results from Shastic Calculus.- B.1 Itô’s Formula.- B.2 Shastic Differential Equations.- B.3 Martingales.- B.4 Change of Measure.- C Appendix: The Term Structure of Interest Rates.- C.1 Term Structure Terminology.- C.2 Interest Rate Derivatives.- References.
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