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Monte Carlo Methods in Finance
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Monte Carlo Methods in Finance Hardcover - 2002

by Peter Jaeckel

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Details

  • Title Monte Carlo Methods in Finance
  • Author Peter Jaeckel
  • Binding Hardcover
  • Edition Har/Com
  • Condition Used - Acceptable
  • Pages 238
  • Language ENG
  • Publisher Wiley, Somerset, New Jersey, U.S.A.
  • Date April 11, 2002
  • Features Bibliography, Index
  • Bookseller's Inventory # A047149741X
  • ISBN 9780471497417

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From the publisher

Dieses Buch ist ein handlicher und praktischer Leitfaden zur Monte Carlo Simulation (MCS). Er gibt eine Einfhrung in Standardmethoden und fortgeschrittene Verfahren, um die zunehmende Komplexitt derivativer Portfolios besser zu erfassen. Das hier behandelte Spektrum von MCS-Anwendungen reicht von der Preisbestimmung komplexerer Derivate, z.B. von amerikanischen und asiatischen Optionen, bis hin zur Messung des Value at Risk und zur Modellierung komplexer Marktdynamik. Anhand einer Vielzahl praktischer Beispiele wird erlutert, wie man Monte Carlo Methoden einsetzt. Dabei gehen die Autoren zunchst auf die Grundlagen und danach auf fortgeschrittene Techniken ein. Darber hinaus geben sie ntzliche Tipps und Hinweise fr das Entwickeln und Arbeiten mit MCS-Methoden. Die Autoren sind Experten auf dem Gebiet der Monte Carlo Simulation und verfgen ber langjhrige Erfahrung im Umgang mit MCS-Methoden. Die Begleit-CD enthlt Excel Muster Spreadsheets sowie VBA und C++ Code Snippets, die der Leser installieren und so mit den im Buch beschriebenen Beispiele frei experimentieren kann. "Monte Carlo Methods in Finance" - ein unverzichtbares Nachschlagewerk fr quantitative Analysten, die bei der Bewertung von Optionspreisen und Riskmanagement auf Modelle zurckgreifen mssen.

First line

We are on the verge of a new era of financial computing.

From the jacket flap

Monte Carlo Methods in Finance is an important reference for those working in investment banks, insurance and strategic management consultancy. Of particular importance are the many known variance reduction methods, and they are duly covered, not only in their own right, but also with respect to their potential combinations, and in the direct context of realistic applications. Most notably, the issue of the reliability of low-discrepancy numbers in high dimensions is discussed in detail. The book also contains an introduction to the theory of copule as an extension to the modelling of correlation of financial securities. An entire chapter is dedicated to the evaluation of interest rate derivatives in the Brace-Gatarek-Musiela/Jamshidian framework by the aid of fast-convergence Monte Carlo simulations. What's more, for the first time, this book also gives a description of the construction of non-recombining trees. Whilst non-recombining trees are usually not viable in a production environment, they often are the very tool of last resort when Monte Carlo approximations to problems such as Bermudan swaptions are to be tested, and the tricks for the construction of non-recombining trees presented in this book are invaluable for that purpose.

About the author

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

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