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Inversions of Lévy Measures and the Relation Between Long and Short Time Behavior of Lévy Processes

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  • Michael Grabchak

    (The University of North Carolina at Charlotte)

Abstract

The inversion of a Lévy measure was first introduced (under a different name) in Sato (ALEA Lat Am J Probab Math Stat 3:67–110, 2007). We generalize the definition and give some properties. We then use inversions to derive a relationship between weak convergence of a Lévy process to an infinite variance stable distribution when time approaches zero and weak convergence of a different Lévy process as time approaches infinity. This allows us to get self-contained conditions for a Lévy process to converge to an infinite variance stable distribution as time approaches zero. We formulate our results both for general Lévy processes and for the important class of tempered stable Lévy processes. For this latter class, we give detailed results in terms of their Rosiński measures.

Suggested Citation

  • Michael Grabchak, 2015. "Inversions of Lévy Measures and the Relation Between Long and Short Time Behavior of Lévy Processes," Journal of Theoretical Probability, Springer, vol. 28(1), pages 184-197, March.
    • Handle: RePEc:spr:jotpro:v:28:y:2015:i:1:d:10.1007_s10959-012-0476-6
    DOI: 10.1007/s10959-012-0476-6
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    References listed on IDEAS

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    1. Jurek, Zbigniew J., 2007. "Random integral representations for free-infinitely divisible and tempered stable distributions," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 417-425, February.
    2. Michael Grabchak & Gennady Samorodnitsky, 2010. "Do financial returns have finite or infinite variance? A paradox and an explanation," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 883-893.
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