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Fluctuations of Levy Processes with Applications Andreas E. Kyprianou

Fluctuations of Levy Processes with Applications By Andreas E. Kyprianou

Fluctuations of Levy Processes with Applications by Andreas E. Kyprianou


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Summary

This book examines the theory and application of Levy processes from the perspective of their path fluctuations. It covers the decomposition of paths in terms of excursions from the running maximum as well as an understanding of short- and long-term behaviour.

Fluctuations of Levy Processes with Applications Summary

Fluctuations of Levy Processes with Applications: Introductory Lectures by Andreas E. Kyprianou

Levy processes are the natural continuous-time analogue of random walks and form a rich class of stochastic processes around which a robust mathematical theory exists. Their application appears in the theory of many areas of classical and modern stochastic processes including storage models, renewal processes, insurance risk models, optimal stopping problems, mathematical finance, continuous-state branching processes and positive self-similar Markov processes.

This textbook is based on a series of graduate courses concerning the theory and application of Levy processes from the perspective of their path fluctuations. Central to the presentation is the decomposition of paths in terms of excursions from the running maximum as well as an understanding of short- and long-term behaviour.

The book aims to be mathematically rigorous while still providing an intuitive feel for underlying principles. The results and applications often focus on the case of Levy processes with jumps in only one direction, for which recent theoretical advances have yielded a higher degree of mathematical tractability.

The second edition additionally addresses recent developments in the potential analysis of subordinators, Wiener-Hopf theory, the theory of scale functions and their application to ruin theory, as well as including an extensive overview of the classical and modern theory of positive self-similar Markov processes. Each chapter has a comprehensive set of exercises.


Fluctuations of Levy Processes with Applications Reviews

The book grew out of lectures pitched at an advanced undergraduate or beginning graduate audience, the prerequisite being a course on abstract Lebesgue integration and a good foundation in probability theory . Fluctuations of Levy processes is an interesting book and it is currently the best introduction for the novice to this important topic. (Rene L. Schilling, Mathematical Reviews, April, 2015)

About Andreas E. Kyprianou

Andreas Kyprianou has a degree in Mathematics from the University of Oxford and a Ph.D. in Probability Theory from The University of Sheffield. He is currently a Professor of Probability at the University of Bath, having held academic positions in Mathematics and Statistics Departments at the London School of Economics, Edinburgh University, Utrecht University and Heriot-Watt University, besides working for nearly two years as a research mathematician in the oil industry. His research is focused on pure and applied probability.

Table of Contents

Levy Processes and Applications.- The LevyIto Decomposition and Path Structure.- More Distributional and Path-Related Properties.- General Storage Models and Paths of Bounded Variation.- Subordinators at First Passage and Renewal Measures.- The WienerHopf Factorisation.- Levy Processes at First Passage.- Exit Problems for Spectrally Negative Processes.- More on Scale Functions.- Ruin Problems and Gerber-Shiu Theory.- Applications to Optimal Stopping Problems.- Continuous-State Branching Processes.- Positive Self-similar Markov Processes.- Epilogue.- Hints for Exercises.- References.- Index.

Additional information

NPB9783642376313
9783642376313
3642376312
Fluctuations of Levy Processes with Applications: Introductory Lectures by Andreas E. Kyprianou
New
Paperback
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
2014-01-20
455
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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