Monte Carlo Methods in Finance / Edition 1

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Monte Carlo Methods in Finance is an important reference for thoseworking in investment banks, insurance and strategic managementconsultancy. Of particular importance are the many known variancereduction methods, and they are duly covered, not only in their ownright, but also with respect to their potential combinations, andin the direct context of realistic applications. Most notably, theissue of the reliability of low-discrepancy numbers in highdimensions is discussed in detail. The book also contains anintroduction to the theory of copulæ as an extension to themodelling of correlation of financial securities. An entire chapteris dedicated to the evaluation of interest rate derivatives in theBrace-Gatarek-Musiela/Jamshidian framework by the aid offast-convergence Monte Carlo simulations. What's more, for thefirst time, this book also gives a description of the constructionof non-recombining trees. Whilst non-recombining trees are usuallynot viable in a production environment, they often are the verytool of last resort when Monte Carlo approximations to problemssuch as Bermudan swaptions are to be tested, and the tricks for theconstruction of non-recombining trees presented in this book areinvaluable for that purpose.

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Product Details

  • ISBN-13: 9780471497417
  • Publisher: Wiley
  • Publication date: 3/26/2002
  • Series: Wiley Finance Series , #5
  • Edition description: BOOK & CD
  • Edition number: 1
  • Pages: 238
  • Product dimensions: 6.99 (w) x 9.92 (h) x 0.82 (d)

Meet the Author

Peter Jäckel currently works at Commerzbank Securities inLondon as a quant in the front office product development andderivatives modelling group. Prior to that he worked within theNatWest Group/Royal Bank of Scotland Quantitative Research Centre.He started his career in finance with his employment at NikkoSecurities' London operation.

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Table of Contents



Mathematical Notation


The Mathematics Behind Monte Carlo Methods

Stochastic Dynamics

Process-driven Sampling

Correlation and Co-movement

Salvaging a Linear Correlation Matrix

Pseudo-random Numbers

Low-discrepancy Numbers

Non-uniform Variates

Variance Reduction Techniques


Monte Carlo in the BGM/J Framework

Non-recombining Trees




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