200,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in über 4 Wochen
payback
100 °P sammeln
  • Gebundenes Buch

Monte Carlo simulation is a universal tool that can be applied in nearly every area of financial and actuarial modeling if one fully understands simulation. This book introduces financial and actuarial models via mathematical simulation. It gives a rigorous introduction to Monte Carlo simulation, including random number generation, basic methods, convergence, and variance reduction. The authors describe financial and actuarial models and show how simulation techniques can be applied to these models to solve problems in finance, including option pricing, derivatives pricing, risk, and asset liability management.…mehr

Produktbeschreibung
Monte Carlo simulation is a universal tool that can be applied in nearly every area of financial and actuarial modeling if one fully understands simulation. This book introduces financial and actuarial models via mathematical simulation. It gives a rigorous introduction to Monte Carlo simulation, including random number generation, basic methods, convergence, and variance reduction. The authors describe financial and actuarial models and show how simulation techniques can be applied to these models to solve problems in finance, including option pricing, derivatives pricing, risk, and asset liability management.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Autorenporträt
Ralf Korn is a professor of financial mathematics at the University of Kaiserslautern and a member of the scientific advisory board of Fraunhofer ITWM in Kaiserslautern, Germany. Elke Korn is an independent financial mathematics consultant in Kaiserslautern, Germany. Gerald Kroisandt is a financial mathematician at Fraunhofer ITWM, in Kaiserslautern, Germany.
Rezensionen
The collection of topics covered is quite impressive. ... this book should serve as a valuable reference provided that one has sufficient background in finance, probability theory, and stochastic processes. It is self contained, and the formal background for each model is carefully described. This work also does an excellent job of providing an accessible source for many of the most recent financial models and latest Monte Carlo methods for their application.
-Maria L. Rizzo, The American Statistician, November 2011

This book is a comprehensive canter through the various Monte Carlo methods and their application in numerous financial models before rounding off with a high level assessment of their role within the insurance industry. The book covers a wide range of methods and models from old favourites like the Black-Scholes model to recent developments such as the multilevel Monte Carlo method. ... the authors cleverly weave in example algorithms throughout the book which allows the user to mock up simple examples of the method. ... a good reference book which was comprehensive in its coverage of the methods and financial models available. The book certainly brought to my attention methods and applications I was unaware of with discussion of some very recent developments. ... what stood out about the book for me (apart from the wide coverage) was the use of example algorithms and numbers by the authors.
-Annals of Actuarial Science, Vol. 5, June 2011

This book takes a straightforward line to discuss Monte Carlo experiments with financial and insurance applications, offering a step-by-step approach to Monte Carlo methods with extensive description of the algorithms required. ... this book includes a rigorous and concise description of numerous financial models and offers an up-to-date survey of this literature. This thorough book can be seen as a handbook on Monte Carlo methods and models for practitioners in finance and can be used in graduate courses on simulation models, numerical methods, financial mathematics, actuarial models and financial econometrics. It is certainly a toolkit of models and their corresponding Monte Carlo algorithms for practitioners and researchers in finance and insurance.
-Journal of the Royal Statistical Society: Series A, July 2011

…mehr