Andere Kunden interessierten sich auch für
![The Fascination of Probability, Statistics and their Applications]( "The Fascination of Probability, Statistics and their Applications")
The Fascination of Probability, Statistics and their Applications74,99 €![Mathematical Risk Analysis]( "Mathematical Risk Analysis")
Mathematical Risk Analysis63,99 €![Scenario Logic and Probabilistic Management of Risk in Business and Engineering]( "Scenario Logic and Probabilistic Management of Risk in Business and Engineering")
Scenario Logic and Probabilistic Management of Risk in Business and Engineering74,99 €![Backward Stochastic Differential Equations]( "Backward Stochastic Differential Equations")
Backward Stochastic Differential Equations66,99 €![Scenario Logic and Probabilistic Management of Risk in Business and Engineering]( "Scenario Logic and Probabilistic Management of Risk in Business and Engineering")
Scenario Logic and Probabilistic Management of Risk in Business and Engineering77,99 €![Stochastic Integration in Banach Spaces]( "Stochastic Integration in Banach Spaces")
Stochastic Integration in Banach Spaces52,99 €![Derivative Security Pricing]( "Derivative Security Pricing")
Derivative Security Pricing132,99 €
This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions.
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.
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.
"This is a very nicely written book on tempered stable distributions. The exposition is careful and very readable. ... The book will be a very helpful source for researchers working in the area of tempered stable distributions and for all that want to apply them." (Alexander Lindner, zbMATH 1361.60003, 2017)