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The distribution of the maximum of a variance gamma process and path-dependent option pricing.
Finance Stochastics, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Doklady Mathematics, 2012
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SSRN Electronic Journal, 2012
In this paper we primarily obtain the explicit formulas for the distribution function of the variance gamma process. The formulas are based on values of hypergeometric functions. This result is applied to European option pricing. Basing on the established formulas, we get the prices of binary options, as long as the price of European call which was ...
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In this paper we primarily obtain the explicit formulas for the distribution function of the variance gamma process. The formulas are based on values of hypergeometric functions. This result is applied to European option pricing. Basing on the established formulas, we get the prices of binary options, as long as the price of European call which was ...
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Decisions in Economics and Finance
This paper examines the profit testing of life insurance companies that issue participating policies, type B and type A universal life policies, and variable annuities with guaranteed minimum maturity and death benefits, when investment returns are stochastic and modeled by normal or variance gamma distributions.
Le Courtois, Olivier, Shen, Li
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This paper examines the profit testing of life insurance companies that issue participating policies, type B and type A universal life policies, and variable annuities with guaranteed minimum maturity and death benefits, when investment returns are stochastic and modeled by normal or variance gamma distributions.
Le Courtois, Olivier, Shen, Li
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2017
The multivariate skewed variance gamma (VG) distribution is useful for modelling data with heavy-tails and high density around the location parameter. When the shape parameter is sufficiently small, the density function is unbounded at the location parameter. In this thesis, we proposed three modifications to appropriately bound the likelihood function
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The multivariate skewed variance gamma (VG) distribution is useful for modelling data with heavy-tails and high density around the location parameter. When the shape parameter is sufficiently small, the density function is unbounded at the location parameter. In this thesis, we proposed three modifications to appropriately bound the likelihood function
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Application of the variance gamma distribution for change point detection
Communications in Statistics - Simulation and ComputationMeenu Rani, Bhavesh Garg, Arun Kumar
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The role of the gamma knife in the treatment of malignant primary and metastatic brain tumors
Ca-A Cancer Journal for Clinicians, 1998Ronald F Young
exaly