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On Asymmetric Correlations and Their Applications in Financial Markets

Author

Listed:
  • Linyu Cao

    (College of Mathematics and Information Science, Zhengzhou University of Light Industry, Zhengzhou 450001, China)

  • Ruili Sun

    (College of Mathematics and Information Science, Zhengzhou University of Light Industry, Zhengzhou 450001, China)

  • Tiefeng Ma

    (School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Conan Liu

    (UNSW Business School, University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

Progress on asymmetric correlations of asset returns has recently advanced considerably. Asymmetric correlations can cause problems in hedging effectiveness and overstate the value of diversification. Furthermore, considering the asymmetric correlations in portfolio construction significantly enhances performance. The purpose of this paper is to trace developments and identify areas that require further research. We examine three aspects of asymmetric correlations: first, the existence of asymmetric correlations between asset returns and their significance tests; second, the test on the existence of asymmetric correlations between different markets and financial assets; and third, the root cause analysis of asymmetric correlations. In the first part, the contents of extreme value theory, the H statistic and a model-free test are covered. In the second part, commonly used models such as copula and GARCH are included. In addition to the GARCH and copula formulations, many other methods are included, such as regime switching, the Markov switching model, and the multifractal asymmetric detrend cross-correlation analysis method. In addition, we compare the advantages and differences between the models. In the third part, the causes of asymmetry are discussed, for example, higher common fundamental risk, correlation of individual fundamental risk, and so on.

Suggested Citation

  • Linyu Cao & Ruili Sun & Tiefeng Ma & Conan Liu, 2023. "On Asymmetric Correlations and Their Applications in Financial Markets," JRFM, MDPI, vol. 16(3), pages 1-18, March.
  • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:3:p:187-:d:1092699
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    References listed on IDEAS

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    1. Paul R. Dewick & Shuangzhe Liu & Yonghui Liu & Tiefeng Ma, 2023. "Elliptical and Skew-Elliptical Regression Models and Their Applications to Financial Data Analytics," JRFM, MDPI, vol. 16(7), pages 1-20, June.

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