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Nature of Computation and Communication. 7th EAI International Conference, ICTCC 2021, Virtual Event, October 28–29, 2021, Proceedings

Research Article

Stable Random Vector and Gaussian Copula for Stock Market Data

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  • @INPROCEEDINGS{10.1007/978-3-030-92942-8_16,
        author={Truc Giang Vo Thi},
        title={Stable Random Vector and Gaussian Copula for Stock Market Data},
        proceedings={Nature of Computation and Communication. 7th EAI International Conference, ICTCC 2021, Virtual Event, October 28--29, 2021, Proceedings},
        proceedings_a={ICTCC},
        year={2022},
        month={1},
        keywords={Stable distribution Gaussian copula Stock market},
        doi={10.1007/978-3-030-92942-8_16}
    }
    
  • Truc Giang Vo Thi
    Year: 2022
    Stable Random Vector and Gaussian Copula for Stock Market Data
    ICTCC
    Springer
    DOI: 10.1007/978-3-030-92942-8_16
Truc Giang Vo Thi1,*
  • 1: Tien Giang University
*Contact email: vothitrucgiang@tgu.edu.vn

Abstract

A lot of real-world data sets have heavy tailed distribution, while the calculations for these distributions in multidimensional case are complex. The paper shows a method to investigate data of multivariate heavy-tailed distributions. We show that for any given number(\alpha \in (0; 2],)each Gaussian copula is also the copula of an(\alpha )-stable random vector. Simultaneously, every random vector is(\alpha )-stable if its marginals are(\alpha )-stable and its copula is a Gaussian copula. The result is used to build up a formula representing density functions of(\alpha )-stable random vectors with Gaussian copula. Adopting a new tool, the paper points out that in most of cases, vectors of daily returns in stock market data have multivariate stable distributions with Gaussian copulas and we propose a new method to choose an investment portfolio by computing the distribution of linear combination of components of stable random vector. Dataset of 4 stocks on HOSE was analyzed.

Keywords
Stable distribution Gaussian copula Stock market
Published
2022-01-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-92942-8_16
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