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Monte Carlo Methods in Financial Engineering

  • Paul¬†Glasserman

Part of the Stochastic Modelling and Applied Probability book series (SMAP, volume 53)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Paul Glasserman
    Pages 1-38
  3. Paul Glasserman
    Pages 79-184
  4. Paul Glasserman
    Pages 185-279
  5. Paul Glasserman
    Pages 281-337
  6. Paul Glasserman
    Pages 339-376
  7. Paul Glasserman
    Pages 377-420
  8. Paul Glasserman
    Pages 421-479
  9. Paul Glasserman
    Pages 481-537
  10. Back Matter
    Pages 539-597

About this book

Introduction

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 stochastic 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.

Keywords

Analysis Measure Monte Carlo Simulation Monte Carlo method Random variable Stochastic Differential Equations Stochastic calculus

Authors and affiliations

  • Paul¬†Glasserman
    • 1
  1. 1.Graduate School of BusinessColumbia UniversityNew YorkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-21617-1
  • Copyright Information Springer-Verlag New York 2003
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-1822-2
  • Online ISBN 978-0-387-21617-1
  • Series Print ISSN 0172-4568
  • Buy this book on publisher's site