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Which time-frequency domain dominates spillover in the Chinese energy stock market?

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  • Sun, Qingru
  • Gao, Xiangyun
  • An, Haizhong
  • Guo, Sui
  • Liu, Xueyong
  • Wang, Ze

Abstract

Previous studies detected the spillover relations among stocks and identified the spillover roles of stocks. However, due to the participants with different dealing frequencies, the spillover effects in the stock market present multiscale features, then which time-frequency domain dominates the spillover in the stock market? Take Chinese energy stocks as an example, this paper examines the return spillover effects of the energy stock market under each time-frequency domain. We find significant return spillover in the Chinese energy stock market under different time scales, and the spillover effect under the time scale of 32–64 days contributes the most to the spillover in the whole energy stock market. Then we take further research on the directional spillovers, spillovers between energy stocks and spillovers between energy industries to detect who plays leading positions under each time scale. We divide the stocks into four roles, and find that it is different role that plays a leading position under each time scale. Furthermore, a small number of spillover relationships between energy stocks carry a large part of the total spillover quantities, and coal and consumable fuel-related stocks play an important role in the spillover of Chinese energy stocks. The robustness of our results is proved by additional tests with different forecast horizons. Our paper contributes to the literature by examining the multiscale spillover effect in the Chinese energy stock market, which provides references for market participants on investment horizons choosing, stocks selection and risk aversion.

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  • Sun, Qingru & Gao, Xiangyun & An, Haizhong & Guo, Sui & Liu, Xueyong & Wang, Ze, 2021. "Which time-frequency domain dominates spillover in the Chinese energy stock market?," International Review of Financial Analysis, Elsevier, vol. 73(C).
  • Handle: RePEc:eee:finana:v:73:y:2021:i:c:s1057521920302842
    DOI: 10.1016/j.irfa.2020.101641
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    More about this item

    Keywords

    Energy stocks; Spillover effect; Multiscale; Generalized variance decomposition; Wavelet method;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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