The Variance Gamma (V.G.) Model for Share Market Returns

By Dilip B Madan 5, Eugene Seneta. 1990

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Citations in the corpus

Realistic Statistical Modelling of Financial Data (2000, background): “In Madan and Seneta (1990), Madan and Milne (1991) and Madan and Chang (1996) the variance gamma (V.G.) model, which is a normal gamma Lévy process, is studied as a model for share market returns.”
Variance-Gamma and Monte Carlo (2007, methodology): “The Variance-Gamma (VG) process was introduced to the finance community as a model for asset returns (log-price increments) and options pricing in Madan and Seneta [ 20 ], with further significant developments in Madan and Milne [19] and Madan et al. [18].”
Dam rain and cumulative gain (2007, methodology): “The gamma process has been used as the basis of a number of different asset pricing models; see, for example, Madan & Seneta (1990), Madan and Milne (1991), Heston (1995), Madan et al. (1998), Carr et al. (2002), and Baxter (2007).”
Fitting the variance-gamma model to financial data (2004, methodology): “The original variance-gamma (VG) model (Madan and Seneta (1990)) is the restricted case where () == 0, and is called the 'symmetric variance-gamma' model by Madan et al. (1998), the 'log variance gamma model' by Hurst et al. (1997), and 'The Madan and Seneta log variance gamma model' by Hurst and…”
On the Distributional Characterization of Daily Log‐Returns of a World Stock Index (2006, background): “…t (Praetz, 1972; Blattberg and Gonedes, 1974), the normal inverse Gaussian, (Barndorff-Nielsen, 1995), the hyperbolic (Eberlein and Keller, 1995; Küchler et al., 1995), the variance gamma (Madan and Seneta, 1990) and the symmetric generalized hyperbolic distribution (Barndorff-Nielsen, 1978).”
A Jump-Diffusion Model for Option Pricing (2002, unknown): “…generalized hyperbolic models, including log t model and log hyperbolic model; see, for example, Barndorff-Nielsen and Shephard (2001), Blattberg and Gonedes (1974); (c) time-changed Brownian motions; see, for example , Clark (1973), Madan and Seneta (1990), Madan et al. (1998), and Heyde (2000).”
Generalized z-Distributions and Related Stochastic Processes (2001, methodology): “When β = µ = χ = 0a ndγ = ψ> 0, the mixing distribution is the gamma distribution and the mixtures are called Variance Gamma (V.G.) distributions (see [ 23 ], [24]).”
Hyperbolic Processes in Finance (2003, methodology): “The other class with this important property is the class of variance-gamma (VG) distributions, which is obtained when is equal to 0. This is only possible when > 0 and > j j. The variance-gamma distributions (with = 0) were introduced in the nancial literature by Madan & Seneta (1990) .”
The Variance-Gamma Distribution: A Review (2023, unknown): “Seneta [77], and has since become widely used in financial modelling; see, for example, Madan, Carr and Chang [73], Madan and Milne [74] and Seneta [108].”
A semi-parametric approach to risk management (2003, unknown): “For background, see Madan and Seneta (1990) and Carr et al (1998).”
Convergence of a discretization scheme for jump-diffusion processes with state–dependent intensities (2004, methodology): “Specific models of this type (in which the Brownian component is dropped altogether) have been developed by Barndorff-Nielsen (1998) and Madan & Seneta (1990).”
Chapter 2 Jump-Diffusion Models for Asset Pricing in Financial Engineering (2007, background): “See, for example, Clark (1973), Madan and Seneta (1990), Madan et al. (1998), Heyde (2000), Carr et al. (2003).”