Abstract
The paper discusses the capabilities of the R language for the visualization in modeling Levy processes – processes that currently most closely correspond to the nature of the evolution of stock price movements. R is a programming language and a free software environment for statistical data processing and graphics. Due to the possibility of direct access from R to stock values stored in the Oracle database, modeling Levy processes in the R language is an urgent task. Levy processes are used as processes describing the evolution of the logarithmic returns of financial assets in the exponential Levy model. The article proposes modeling algorithms for some Levy processes that significantly reduce the modeling time of these processes compared to previously known Levy process modeling algorithms. A significant reduction in the simulation time of the indicated processes is confirmed experimentally. A mathematical justification is presented for representing the CGMY process as the difference of two slowly growing stable independent random Levy processes. The efficient algorithm of the CGMY process simulation as a difference of the tempered stable independent Levy is processed and programmed at R language. The efficient algorithm of variance gamma process simulation using variance gamma random variables is processed and programmed at R language.
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