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Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches

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  • Zhenghui Li

    (Guangzhou Institute of International Finance, Guangzhou University, Guangzhou 510006, China)

  • Zhiming Ao

    (Institute of Finance, Jinan University, Guangzhou 510632, China)

  • Bin Mo

    (Guangzhou Institute of International Finance, Guangzhou University, Guangzhou 510006, China)

Abstract

We employ the quantile-coherency approach and causality-in-quantile method to revisit the roles of Bitcoin, U.S. dollar, crude oil and gold for USA, Chinese, UK, and Japanese stock markets. The main results show that the impact of global financial assets varies across different investment horizons and quantiles. We find that in most cases, the correlation between global financial assets and stock indexes is not significant or is weakly positive. From the perspective of investment horizons (frequency domain), the correlation in the short term is mostly manifested in Bitcoin, while in the medium and long term it is shifted to dollar assets. At the same time, the relationships are significantly higher in the medium and long term than in the short term. From the point of view of quantiles, it shows a weak positive correlation at the lower quantile. However, the correlation between the two is not significant at the median quantile. At the high quantiles, there is a weak negative linkage. According to the causality-in-quantiles approach results, in most cases global financial assets have different degrees of predictive capacity for the selected stock markets. Especially around the median quantile, the predictive ability was strongest.

Suggested Citation

  • Zhenghui Li & Zhiming Ao & Bin Mo, 2021. "Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:15:p:1750-:d:600906
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