Overview
- Provides a thorough survey of tempered stable distributions and their associate Levy processes
- Self-contained discussion and overview makes it perfect for researchers interested in learning about tempered stable distributions
- Many new cutting-edge results of interest to specialists in the area
Part of the book series: SpringerBriefs in Mathematics (BRIEFSMATH)
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About this book
A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.
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Table of contents (8 chapters)
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Bibliographic Information
Book Title: Tempered Stable Distributions
Book Subtitle: Stochastic Models for Multiscale Processes
Authors: Michael Grabchak
Series Title: SpringerBriefs in Mathematics
DOI: https://doi.org/10.1007/978-3-319-24927-8
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Michael Grabchak 2016
Softcover ISBN: 978-3-319-24925-4Published: 10 March 2016
eBook ISBN: 978-3-319-24927-8Published: 26 January 2016
Series ISSN: 2191-8198
Series E-ISSN: 2191-8201
Edition Number: 1
Number of Pages: XII, 118
Topics: Probability Theory and Stochastic Processes, Quantitative Finance