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The Dynamic Relationships between the Baltic Dry Index and the BRICS Stock Markets: A Wavelet Analysis

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  • Pao-Lan Kuo
  • Chien-Liang Chiu
  • Chan-Sheng Chen
  • Mei-Chih Wang

Abstract

This paper studies the dynamic relationships between the Baltic Dry Index (BDI) and the BRICS stock markets by wavelet analysis for the period from January 1996 to March 2019. Compared to the causality based on linearity and the choosing of the period of lags, as well as given the significant evidence of nonlinearity, we used wavelet analysis to analyze the dynamic relationships between the two series in both time and frequency domains, which helped us to demonstrate the causality across different horizons. Due to wavelet analysis, we found that the BDI and the Brazilian stock market had a significantly positive relationship from 2002 to 2011 in the medium term and that the Brazilian stock market led the BDI from 2002 to 2004 and from 2009 to 2011. The wavelet analysis showed that the Russian and Indian stock markets dominated the BDI from 2005 to 2016 in the long term and from 2002 to 2011 in the medium term, respectively. The South African stock market and the BDI had a medium term, positive, and co-movement relationships. The empirical results of Brazil and South African indicated that commodity import- and export- related countries have similar interactions. Lastly, wavelet analysis revealed that the BDI lead the Chinese stock market from 1996 to 1998 in the medium term, while the Chinese stock market turned to dominate the BDI from 2001 to 2011, both in the medium and long term.

Suggested Citation

  • Pao-Lan Kuo & Chien-Liang Chiu & Chan-Sheng Chen & Mei-Chih Wang, 2020. "The Dynamic Relationships between the Baltic Dry Index and the BRICS Stock Markets: A Wavelet Analysis," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(3), pages 340-351.
    • Handle: RePEc:asi:aeafrj:v:10:y:2020:i:3:p:340-351:id:1928
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    Cited by:

    1. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1181-1200, September.
    2. Adewuyi, Adeolu O. & Adeleke, Musefiu A. & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel, 2023. "Dynamic linkages between shipping and commodity markets: Evidence from a novel asymmetric time-frequency method," Resources Policy, Elsevier, vol. 83(C).

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