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.

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 2011This 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 2011This 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

• Introduction and User Guide. Generating Random Numbers. The Monte Carlo Method: Basic Principles and Improvements. Simulating Continuous-Time Stochastic Processes with Continuous Paths. Simulating Financial Models and Pricing of Derivatives: Continuous Paths. Simulating Continuous-Time Stochastic Processes: Discontinuous Paths. Simulating Financial Models: Discontinuous Paths. Simulating Actuarial Models. References. Index.

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.

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 2011This 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 2011This 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

• Introduction and User Guide. Generating Random Numbers. The Monte Carlo Method: Basic Principles and Improvements. Simulating Continuous-Time Stochastic Processes with Continuous Paths. Simulating Financial Models and Pricing of Derivatives: Continuous Paths. Simulating Continuous-Time Stochastic Processes: Discontinuous Paths. Simulating Financial Models: Discontinuous Paths. Simulating Actuarial Models. References. Index.