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Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?

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  • He Nie
  • Yonghong Jiang
  • Baoqing Yang

Abstract

This article investigates the linear, nonlinear and time-varying Granger causality between different time horizons in the volatility of US stock market and the China Exchange-Traded Fund (ETF) market. We find evidence of linear causality from the US stock market to the China ETF market, with a bilateral nonlinear causal relationship in the longer term. Bootstrap rolling causality analysis indicates high rejection rates of a noncausal relationship running from the US stock market to the China EFT market. The causality linkage from the China ETF market to the US stock market was determined to be time-horizon-dependent, and the null hypothesis rejection rate of non-Granger causality increased in the longer term.

Suggested Citation

  • He Nie & Yonghong Jiang & Baoqing Yang, 2018. "Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?," Applied Economics Letters, Taylor & Francis Journals, vol. 25(11), pages 747-751, June.
  • Handle: RePEc:taf:apeclt:v:25:y:2018:i:11:p:747-751
    DOI: 10.1080/13504851.2017.1363853
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    Cited by:

    1. Qi, Haozhi & Wu, Tiantian & Chen, Hao & Lu, Xiuling, 2023. "Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
    2. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
    3. Chen, Yanan & Qi, Haozhi, 2024. "COVID-19 pandemic-related news and Chinese commodities futures: Time-frequency connectedness and causality-in-quantiles approaches," Energy, Elsevier, vol. 286(C).
    4. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    5. Chen, Hao & Xu, Chao & Peng, Yun, 2022. "Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China," Resources Policy, Elsevier, vol. 78(C).
    6. Yang, Dong-Xiao & Wu, Bi-Bo & Tong, Jing-Yang, 2021. "Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods," Resources Policy, Elsevier, vol. 74(C).
    7. Mo, Bin & Chen, Cuiqiong & Nie, He & Jiang, Yonghong, 2019. "Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests," Energy, Elsevier, vol. 178(C), pages 234-251.
    8. Mo, Bin & Zeng, Haiyu & Meng, Juan & Ding, Shaokai, 2024. "The connectedness between uncertainty and exchange rates of oil import countries: new evidence from time and frequency perspective," Resources Policy, Elsevier, vol. 88(C).
    9. Jiang, Yonghong & Fu, Yuyuan & Ruan, Weihua, 2019. "Risk spillovers and portfolio management between precious metal and BRICS stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    10. Yutaka Kurihara & Shinichiro Maeda & Akio Fukushima, 2021. "Have the Purchases of ETF Raised Stock Prices? Recent Japanese Case," Bulletin of Applied Economics, Risk Market Journals, vol. 8(1), pages 109-119.

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