Clustering of financial instruments using jump tail dependence coefficient

Chen Yang (), Wenjun Jiang (), Jiang Wu (), Xin Liu () and Zhichuan Li ()
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Chen Yang: Wuhan University
Wenjun Jiang: University of Western Ontario
Jiang Wu: Central University of Finance and Economics
Xin Liu: University of Western Ontario
Zhichuan Li: University of Western Ontario

Statistical Methods & Applications, 2018, vol. 27, issue 3, No 7, 513 pages

Abstract: 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 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10260-017-0411-1

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