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Stable Distribution of Multivariate Data

Author

Listed:
  • Phuc Ho Dang

    (a:1:{s:5:"en_US";s:36:"Hanoi Institute of Mathematics, VAST";})

  • Truc Giang Vo Thi

    (Tien Giang University, Vietnam)

Abstract

The main theorem of the paper states that every stable random vector with marginal skewness parameters different from ±1 can be turned into a sub-Gaussian random vector by using an appropriately tailored transformation in multidimensional space. The theorem is used to create a formula on probability density function of stable random vector and to perform a procedure of testing the stable distribution of multivariate data. A dataset collected from the Nasdaq stock market is used to illustrate the proposed procedure.

Suggested Citation

Handle: RePEc:epw:ejmath:v:4:y:2023:i:4:id:14160
DOI: 10.24018/ejmath.2023.4.4.160
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