Generalized Hyperbolic Distribution
![]() Generalized hyperbolic distributions were introduced by Barndorff–Nielsen [1]. They generalize many previously known distributions in addition to being a source of many new ones. As they are infinitely divisible, Lévy and other stochastic processes can be based on them. Such processes were first applied in finance by Eberlein and Keller [2]. Being normal variance-mean mixtures, GH distributions possess semi-heavy tails and allow for a natural definition of volatility models by replacing the mixing generalized the inverse Gaussian (GIG) distribution by appropriate volatility processes. ![]() "Generalized Hyperbolic Distribution" from The Wolfram Demonstrations Project http://demonstrations.wolfram.com/GeneralizedHyperbolicDistribution/ Contributed by: Andrzej Kozlowski | ||||||||||||||
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