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Pure -Jump Levy Processes and Self-decomposability in Financial Modeling
Author(s) -
Ömer Önalan
Publication year - 2011
Publication title -
journal of mathematics research
Language(s) - English
Resource type - Journals
eISSN - 1916-9809
pISSN - 1916-9795
DOI - 10.5539/jmr.v3n2p41
Subject(s) - mathematics , lévy process , stable process , pure mathematics , generalization , self similarity , estimator , limit (mathematics) , jump , quadratic equation , type (biology) , jump process , quadratic variation , stochastic process , mathematical analysis , brownian motion , statistics , ecology , physics , biology , geometry , quantum mechanics

In this study, we review the connections between L'{e}vy processes with jumps and self-decomposable laws. Self-decomposable laws constitute a subclass of infinitely divisible laws. L'{e}vy processes additive processes and independent increments can be related using self-similarity property. Sato (1991) defined additive processes as a generalization of L'{e}vy processes. In this way, additive processes are those processes with inhomogeneous (in general) and independent increments and L'{e}vy processes correspond with the particular case in which the increments are time homogeneous. Hence L'{e}vy processes are considerable as a particular type. Self-decomposable distributions occur as limit law an Ornstein-Uhlenbeck type process associated with a background driving L'{e}vy process. Finally as an application, asset returns are representing by a normal inverse Gaussian process. Then to test applicability of this representation, we use the nonparametric threshold estimator of the quadratic variation, proposed by Cont and Mancini (2007).

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