Daniel Duffy, Joerg Kienitz – Monte Carlo Frameworks. Building Customisable High Performance C Applications
ISBN: 978-0-470-06069-8
775 pages
September 2009
Description
This is among the first books that describe all of the steps which are wanted so as to analyze, design and implementMonte Carlo purposes. It discusses the monetary idea in addition to the mathematical and numerical background that’s wanted to put in writing versatile and environment friendly C++ code utilizing state-of-the artwork design and system patterns, object-oriented and generic programming fashions together with commonplace libraries and instruments.
Includes a CD containing the supply code for all examples. It is strongly suggested that you just experiment with the code by compiling it and lengthening it to fit your wants. Support is obtainable by way of a person discussion board on www.datasimfinancial.comthe place you may submit queries and talk with different purchasers of the guide.
This guide is for these professionals who design and develop fashions in computational finance. This guide assumes that you’ve a working data of C ++.
Author Information
DANIEL J. DUFFY has been working with numerical strategies in finance, business and engineering since 1979. He has written 4 books on monetary fashions and numerical strategies and C++ for computational finance and he has additionally developed quite a few new schemes for this area. He is the founding father of Datasim Education and has a PhD in Numerical Analysis from Trinity College, Dublin.
JÖRG KIENITZ is the pinnacle of Quantitative Analysis at Deutsche Postbank AG. He is primarily concerned within the creating and implementation of fashions for pricing of advanced derivatives buildings and for asset allocation. He can be lecturing at college stage on superior monetary modelling and provides programs on ‘Applications of Monte Carlo Methods in Finance’ and on different monetary subjects together with Lévy processes and rate of interest fashions. Joerg holds a Ph.D. in stochastic evaluation and likelihood idea.