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中国管理科学 ›› 2024, Vol. 32 ›› Issue (4): 26-37.doi: 10.16381/j.cnki.issn1003-207x.2021.2541cstr: 32146.14.j.cnki.issn1003-207x.2021.2541

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比特币价格风险、宏观经济波动与股市风险传染

黄云洲,黄炯豪,夏晓华()   

  1. 中国人民大学应用经济学院,北京 100872
  • 收稿日期:2021-12-07 修回日期:2022-03-09 出版日期:2024-04-25 发布日期:2024-04-25
  • 通讯作者: 夏晓华 E-mail:xia.email@ruc.edu.cn
  • 基金资助:
    国家自然科学基金项目(71974192);中国人民大学应用经济学院研究生科学研究项目(2022YJBJCX10)

Bitcoin Price risk, Macroeconomic Environment and Risk Contagion in China's Stock Market:An Analysis Based on Quantile Coherency Network

Yunzhou Huang,Jionghao Huang,Xiaohua Xia()   

  1. School of Applied Economics,Renmin University of China,Beijing 100872,China
  • Received:2021-12-07 Revised:2022-03-09 Online:2024-04-25 Published:2024-04-25
  • Contact: Xiaohua Xia E-mail:xia.email@ruc.edu.cn

摘要:

本文以中国股市28个一级行业为研究样本,利用分位数关联方法量化各一级行业间的金融互联程度,进一步结合空间自回归模型,将比特币价格波动对中国股市造成的风险冲击分解为直接效应与间接效应,测度了比特币价格波动的风险传染效应,并从宏观经济层面分析了其影响因素。研究发现:比特币价格波动对股市行业收益率存在正向影响,且其可以通过行业间的分位数关联在不同行业之间扩散。此外,不同市场状态和不同频率的行业关联呈现出异质性的风险传染模式。具体而言,市场平稳状态、繁荣状态、低迷状态下的风险传染效应依次减弱;中期(周度)的比特币风险传染效应强于短期(日度)的风险传染效应;在市场平稳状态下,周度频率分位数关联网络下的风险传染效应更强。分组检验显示,较低的利率和价格水平能够显著减弱比特币价格冲击对中国股市的风险传染效应。本文的贡献有两点:第一,采用分位数关联方法构建了各一级行业收益率间的依赖结构,并描绘了不同频率和市场状态下的分位数关联网络;第二,使用空间自回归模型将风险冲击分解为直接效应和间接效应,这有助于了解分位数关联在风险传播中的作用,为制定防范比特币风险的相关政策提供了经验证据。

关键词: 分位数关联, 比特币价格, 风险传染

Abstract:

The cryptocurrency market represented by Bitcoin is becoming more and more mature, and it is of great significance to study the impact of Bitcoin price fluctuations on China's financial market. Whether and how Bitcoin price volatilities could propagate through the sectoral financial interconnectedness network and result in larger scale financial turmoil in China’s stock market is investigated in this paper. Using the quantile coherency method, the financial interconnectedness is quantified and the general dependence structure between returns of 28 industries in China’s stock market is evaluated. By constructing a spatial autoregressive framework based on the quantile coherency network, the overall impact of Bitcoin price shocks is further decomposed into direct effects and indirect effects propagating through the financial interconnectedness of industries. The main findings are as follows. Firstly, Bitcoin price volatility has a positive impact on the returns of industries, and it can propagate among different industries through financial interconnectedness. Secondly, the risk contagion effects under the steady state, prosperity and downturn of the market weaken in turn. Thirdly, the mid-term (weekly) Bitcoin risk contagion is stronger than the short-term (daily) risk contagion effect. Fourthly, in the steady state of the market, the risk contagion effect under the weekly frequency financial interconnectedness network is stronger. Finally, lower interest rates and price levels can significantly reduce the risk contagion effect of Bitcoin price shocks on the Chinese stock market. The contributions of this paper are as follows. Firstly, the general dependence structure of 28 industries’returns is constructed and the financial interconnectedness network is further depicted under different frequencies and market conditions. Secondly, spatial autoregressive framework is used to decompose risk shocks into direct effects and indirect effects, which helps to understand the role of financial interconnectedness in risk propagation and empirical evidence is provided for the formulation of policies and regulations to prevent Bitcoin-related risks.

Key words: quantile coherency, Bitcoin price, risk propagation

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