An invaluable resource for quantitative analysts who need to run models that assist in option pricing and risk management. This concise, practical hands on guide to Monte Carlo simulation introduces standard and advanced methods to the increasing complexity of derivatives portfolios. Ranging from pricing more complex derivatives, such as American and Asian options, to measuring Value at Risk, or modelling complex market dynamics, simulation is the only method general enough to capture the complexity and Monte Carlo simulation is the best pricing and risk management method available.
The book is packed with numerous examples using real world data and is supplied with a CD to aid in the use of the examples.
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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.
"There is no book on the market to compare with Dr Jackel's. All the techniques, the tricks, the pitfalls of this important methodology are covered in detail and with great insight. This is no book on abstract theory, Dr Jackel is a practitioner who has implemented every single one of these ideas. He has done all the hard work, so you don't have to." -Paul Wilmott
"Few expert practitioners also have the academic expertise to match Peter Jackel's in this area, let alone take the trouble to write a most accessible, comprehensive and yet self contained text. This book is a delight to read and contains a wealth of information that is essential for anyone involved with implementing Monte Carlo methods in finance." -Professor Carol Alexander, ISMA Centre, University of Reading, UK
" This book is a very welcome addition to the growing literature on applied quantitative methods in finance. Dr Jackel has done the field a service in combining both a thorough review of 'standard' material with techniques that were learned on the job as a quant at top financial institutions." -Michael Curran, Quantin' Leap
Based on the author's own experience, Monte Carlo Methods in Finance adopts a practical flavour throughout, the emphasis being on financial modelling and derivatives pricing. Numerous real world examples help the reader foster an intuitive grasp of the mathematical and numerical techniques needed to solve particular financial problems. At the same time, the book tries to give a detailed explanation of the theoretical foundations of the various methods and algorithms presented.
Monte Carlo methods have been used in the financial community for many years for addressing complex financial calculations. Recent advances by both practitioners and academic researchers in the area of fast convergence methods, together with the improvements achieved by the manufacturers of computer hardware, make Monte Carlo simulations more and more frequently the method of choice. In this long needed book on modern Monte Carlo methods in finance, Peter Jackel provides an introduction to many of the leading edge techniques available.
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.
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