Applied Diffusion Processes From Engineering To Finance

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Applied Diffusion Processes from Engineering to Finance

Applied Diffusion Processes from Engineering to Finance
Author :
Publisher : John Wiley & Sons
Total Pages : 412
Release :
ISBN-10 : 9781118578346
ISBN-13 : 1118578341
Rating : 4/5 (341 Downloads)

Book Synopsis Applied Diffusion Processes from Engineering to Finance by : Jacques Janssen

Download or read book Applied Diffusion Processes from Engineering to Finance written by Jacques Janssen and published by John Wiley & Sons. This book was released on 2013-04-08 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to promote interaction between engineering, finance and insurance, as these three domains have many models and methods of solution in common for solving real-life problems. The authors point out the strict inter-relations that exist among the diffusion models used in engineering, finance and insurance. In each of the three fields, the basic diffusion models are presented and their strong similarities are discussed. Analytical, numerical and Monte Carlo simulation methods are explained with a view to applying them to obtain the solutions to the different problems presented in the book. Advanced topics such as nonlinear problems, Lévy processes and semi-Markov models in interactions with the diffusion models are discussed, as well as possible future interactions among engineering, finance and insurance. Contents 1. Diffusion Phenomena and Models. 2. Probabilistic Models of Diffusion Processes. 3. Solving Partial Differential Equations of Second Order. 4. Problems in Finance. 5. Basic PDE in Finance. 6. Exotic and American Options Pricing Theory. 7. Hitting Times for Diffusion Processes and Stochastic Models in Insurance. 8. Numerical Methods. 9. Advanced Topics in Engineering: Nonlinear Models. 10. Lévy Processes. 11. Advanced Topics in Insurance: Copula Models and VaR Techniques. 12. Advanced Topics in Finance: Semi-Markov Models. 13. Monte Carlo Semi-Markov Simulation Methods.


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