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The Variance Gamma (V.G.) Model for Share Market Returns
The Journal of Business, 1990A new stochastic process, termed the variance gamma process, is proposed as a model for the uncertainty underlying security prices. The unit period distribution is normal conditional on a variance that is distributed as a gamma variate. Its advantages include long tailedness, continuous-time specification, finite moments of all orders, elliptical ...
Madan, Dilip B, Seneta, Eugene
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An empirical test of the variance gamma option pricing model
Pacific-Basin Finance Journal, 2002Abstract In this paper, we test the three-parameter symmetric variance gamma (SVG) option pricing model and the four-parameter asymmetric variance gamma (AVG) option pricing model empirically. Prices of the Hang Seng Index call options, which are of European style, are used as the data for the empirical test.
Lee, MC, Chang, EC, Lam, K
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Option Pricing Using Variance Gamma Markov Chains
Review of Derivatives Research, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Konikov, Mikhail, Madan, Dilip B.
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Variance-Gamma and Monte Carlo
2007The Variance-Gamma (VG) process was introduced by Dilip B. Madan and Eugene Seneta as a model for asset returns in a paper that appeared in 1990, and subsequently used for option pricing in a 1991 paper by Dilip and Frank Milne. This paper serves as a tutorial overview of VG and Monte Carlo, including three methods for sequential simulation of the ...
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Pricing American options under variance gamma
The Journal of Computational Finance, 2003We derive a form of the partial integro-differential equation (PIDE) for pricing American options under variance gamma (VG) process. We then develop a numerical algorithm to solve for values of American options under variance gamma model. In this study, we compare the exercise boundary and early exercise premia between geometric VG law and geometric ...
Ali Hirsa, Dilip Madan
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A Mixture of Variance-Gamma Factor Analyzers
2017The mixture of factor analyzers model is extended to variance-gamma mixtures to facilitate flexible clustering of high-dimensional data. The formation of the variance-gamma distribution utilized is a special and limiting case of the generalized hyperbolic distribution.
Sharon M. McNicholas +2 more
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On risk measuring in the variance-gamma model
Statistics & Risk Modeling, 2017Abstract In this paper, we discuss the problem of calculating the primary risk measures in the variance-gamma model. A portfolio of investments in a one-period setting is considered. It is supposed that the investment returns are dependent on each other.
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On the numerical evaluation of option prices in the variance gamma model
International Journal of Computer Mathematics, 2009Because the pricing equations in Levy models contain integrals, it is difficult to develop rapid numerical methods for solving them. Although the integrals are not periodic, the standard evaluation methods use the FFT, and therefore require large computational regions to ensure accuracy.
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Inference for Variance-Gamma Driven Stochastic Systems
2023 26th International Conference on Information Fusion (FUSION), 2023Joseph Johnson +2 more
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The Early Years of the Variance-Gamma Process
2007Dilip Madan and I worked on stochastic process models with stationary independent increments for the movement of log-prices at the University of Sydney in the period 1980–1990, and completed the 1990 paper [21] while respectively at the University of Maryland and the University of Virginia.
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