Results 231 to 240 of about 40,778 (262)

Derivative pricing using multivariate affine generalized hyperbolic distributions

Journal of Banking & Finance, 2010
Abstract In this paper we use multivariate affine generalized hyperbolic (MAGH) distributions, introduced by Schmidt et al. (2006) , to show how to price multidimensional derivatives when the underlying asset follows a MAGH distribution. We also illustrate the approach using market data from the BOVESPA (Sao Paulo Stock Exchange) and the exchange ...
Fajardo, José, Farias, Aquiles
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The Generalized Hyperbolic Skew Student's t-Distribution

Journal of Financial Econometrics, 2006
In this article we argue for a special case of the generalized hyperbolic (GH) family that we denote as the GH skew Student’s t-distribution. This distribution has the important property that one tail has polynomial and the other exponential behavior. Further, it is the only subclass of the GH family of distributions having this property.
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Classes of skew generalized hyperbolic secant distributions [PDF]

, 2002
A generalization of the hyperbolic secant distribution which allows both for skewness and for leptokurtosis was given by Morris (1982). Recently, Vaughan (2002) proposed another flexible generalization of the hyperbolic secant distribution which has a lot of nice properties but is not able to allow for skewness.
Fischer, Matthias J., Vaughan, David
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On random variate generation for the generalized hyperbolic secant distributions

Statistics and Computing, 1993
We give random variate generators for the generalized hyperbolic secant distribution and related families such as Morris's skewed generalized hyperbolic secant family and a family introduced by Laha and Lukacs. The rejection method generators are uniformly fast over the parameter space and are based upon a complex function representation of the ...
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Optimal Portfolio Selection Based on Expected Shortfall Under Generalized Hyperbolic Distribution

Asia-Pacific Financial Markets, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Surya, Budhi Arta, Kurniawan, Ryan
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Infinite divisibility of the hyperbolic and generalized inverse Gaussian distributions

Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1977
(~'/z)~/2 x~-le --~':~-~+~ (x>0) , (1) 2 K ~ ( ] / ~ ) has the property of infinite divisibility. It follows simply from this that any mixture of the r-dimensional normal distributions Nr(~, X) determined by setting ~ = # + ~ 2 f i A and X=a2A (2) and letting o -2 follow the distribution (1) is infinitely divisible; here #, fl and A are new parameters,
Barndorff-Nielsen, O., Halgreen, Christian   +1 more
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THE GENERALIZED SECANT HYPERBOLIC DISTRIBUTION AND ITS PROPERTIES

Communications in Statistics - Theory and Methods, 2002
The properties of a family of distributions generalizing the secant hyperbolic are developed. This family consists of symmetric distributions, with kurtosis ranging from 1.8 to infinity, and includes the logistic as a special case, the uniform as a limiting case, and closely approximates the normal and Student's t-distributions with corresponding ...
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A Review of Generalized Hyperbolic Distributions

Computational Economics, 2023
Xiao Jiang, Saralees Nadarajah, Thomas Hitchen   +2 more
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Generalized Hyperbolic Distributions: Empirical Evidence on Bucharest Stock Exchange [PDF]

The Review of Finance and Banking, 2015
Onfive of the most liquid and important equities of the Romanian stock market together with the market index is investigated the fit of the generalized hyperbolic distributions. The parameters of the hyperbolic distribution, Variance- Gamma, Normal Inverse Gaussian, skewed t Student and generalized hyperbolic are estimated using the maximum likelihood ...
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Tail Behaviour and Tail Dependence of Generalized Hyperbolic Distributions

2016
Generalized hyperbolic distributions have been well established in finance during the last two decades. However, their application, in particular the computation of distribution functions and quantiles, is numerically demanding. Moreover, they are, in general, not stable under convolution which makes the computation of quantiles in factor models driven
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