"The L\u00E9vy models, when used to simulate time series of returns, enable us to model kurtosis and skewness and thus overcome the main drawback of the Brownian motion. In this paper we focus on the two most widely processes from the L\u00E9vy's family of models, a variance gamma and a normal inverse Gaussian model. The variance gamma model can be regarded as a subordinated (geometric) Brownian motion driven by a random time with gamma distribution. In the normal inverse Gaussian model, Brownian motion is driven by the inverse Gaussian distribution. Both of these models have four parameters, which need to be estimated. In the application part parameters for both models are estimated by means of a method of moments and a maximum likelihood method for five stock indices and five foreign exchange rates. Thereafter modeling quality of these estimated models is compared. Comparison is made on the basis of a log-likelihood function and errors of the basic descriptive statistics and quantile measures VaR a cVaR." . . . "The L\u00E9vy models, when used to simulate time series of returns, enable us to model kurtosis and skewness and thus overcome the main drawback of the Brownian motion. In this paper we focus on the two most widely processes from the L\u00E9vy's family of models, a variance gamma and a normal inverse Gaussian model. The variance gamma model can be regarded as a subordinated (geometric) Brownian motion driven by a random time with gamma distribution. In the normal inverse Gaussian model, Brownian motion is driven by the inverse Gaussian distribution. Both of these models have four parameters, which need to be estimated. In the application part parameters for both models are estimated by means of a method of moments and a maximum likelihood method for five stock indices and five foreign exchange rates. Thereafter modeling quality of these estimated models is compared. Comparison is made on the basis of a log-likelihood function and errors of the basic descriptive statistics and quantile measures VaR a cVaR."@en . . . "Mathematical Methods in Economics 2010" . "A modeling quality comparison of estimated L\u00E9vy models"@en . "\u010Cesk\u00E9 Bud\u011Bjovice" . "A modeling quality comparison of estimated L\u00E9vy models"@en . "\u010Cesk\u00E9 Bud\u011Bjovice" . . . "L\u00E9vy process, variance gamma model, normal inverse Gaussian model, parameter estimation"@en . "978-80-7394-218-2" . "Kresta, Ale\u0161" . "[AF6751E507FD]" . . . "1"^^ . . "000287979900063" . . "1"^^ . . . . "6"^^ . "A modeling quality comparison of estimated L\u00E9vy models" . "RIV/61989100:27510/10:10224832" . "University of South Bohemia" . "P(GA402/08/1237), S" . . . "RIV/61989100:27510/10:10224832!RIV11-GA0-27510___" . . "27510" . . "2010-09-08+02:00"^^ . . "A modeling quality comparison of estimated L\u00E9vy models" . "244694" .