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Distributional Predictability and Quantile Connectedness of New Energy, Steam Coal, and High-Tech in China

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  • Xiaohong Qi

    (College of Economics and Management, Tianjin University of Science and Technology, Tianjin 300453, China)

  • Guofu Zhang

    (College of Economics and Management, Tianjin University of Science and Technology, Tianjin 300453, China)

  • Yuqi Wang

    (School of International Economics and Trade, Xinjiang University of Finance and Economics, Urumqi 830026, China)

Abstract

From a novel quantile perspective, this paper employs nonparametric quantile causality and quantile connectedness to investigate distributional predictability and spillover effects among new energy, steam coal, and high-tech under normal and tail conditions. We first identify the quantile causality: there is a unidirectional causality between the quantile orders 0.1 and 0.4 from technology high-tech to new energy, indicating that the stock price of technology companies has a predictive power of the stock prices of new energy companies when the latter is relatively low. Next, in terms of quantile connectedness, while the risk shocks to the system do not propagate strongly around the median, there are strong spillover effects in both tails. Moreover, high-tech and new energy contribute most of the system’s spillovers, and high-tech is the main net shock transmitter to all other variables. We further find that the strength of spillovers may depend on events such as China’s stock market rout of 2015 and the COVID-19 pandemic.

Suggested Citation

  • Xiaohong Qi & Guofu Zhang & Yuqi Wang, 2022. "Distributional Predictability and Quantile Connectedness of New Energy, Steam Coal, and High-Tech in China," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14176-:d:958233
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