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Statistical Methods & Applications

, Volume 27, Issue 3, pp 491–513 | Cite as

Clustering of financial instruments using jump tail dependence coefficient

  • Chen Yang
  • Wenjun Jiang
  • Jiang Wu
  • Xin Liu
  • Zhichuan Li
Original Paper
  • 194 Downloads

Abstract

In this paper, we propose a new clustering procedure for financial instruments. Unlike the prevalent clustering procedures based on time series analysis, our procedure employs the jump tail dependence coefficient as the dissimilarity measure, assuming that the observed logarithm of the prices/indices of the financial instruments are embedded into multidimensional Lévy processes. The efficiency of our proposed clustering procedure is tested by a simulation study. Finally, with the help of the real data of country indices we illustrate that our clustering procedure could help investors avoid potential huge losses when constructing portfolios.

Keywords

Clustering analysis Lévy copula Jump tail dependence coefficient Country index 

Notes

Acknowledgements

The authors are indebted to two anonymous reviewers for comments and suggestions that improved the paper. Jiang Wu is grateful to the support from MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No. 10YJC790280).

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Economics and Management SchoolWuhan UniversityWuhanPeople’s Republic of China
  2. 2.Department of Statistical and Actuarial SciencesUniversity of Western OntarioLondonCanada
  3. 3.School of EconomicsCentral University of Finance and EconomicsBeijingPeople’s Republic of China
  4. 4.Richard Ivey School of BusinessUniversity of Western OntarioLondonCanada

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