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中国行业商品与工业股票市场之间的动态非对称溢出和关联性。

Dynamic asymmetric spillovers and connectedness between Chinese sectoral commodities and industry stock markets.

机构信息

School of Finance, Southwestern University of Finance and Economics, Chengdu, Sichuan, China.

School of Economics and Management, Anyang University, Xinxiang, Henan, China.

出版信息

PLoS One. 2024 Jan 2;19(1):e0296501. doi: 10.1371/journal.pone.0296501. eCollection 2024.

Abstract

This study investigates the dynamic and asymmetric propagation of return spillovers between sectoral commodities and industry stock markets in China. Using a daily dataset from February 2007 to July 2022, we employ a time-varying vector autoregressive (TVP-VAR) model to examine the asymmetric return spillovers and dynamic connectedness across sectors. The results reveal significant time-varying spillovers among these sectors, with the industry stocks acting as the primary transmitter of information to the commodity market. Materials, energy, and industrials stock sectors contribute significantly to these spillovers due to their close ties to commodity production and processing. The study also identifies significant asymmetric spillovers with bad returns dominating, influenced by major economic and political events such as the 2008 global financial crisis, the 2015 Chinese stock market crisis, the COVID-19 pandemic, and the Russia-Ukraine war. Furthermore, our study highlights the unique dynamics within the Chinese market, where net information spillovers from the stock market to commodities drive the financialization process, which differs from the bidirectional commodity financialization observed in other markets. Finally, portfolio analysis reveals that the minimum connectedness portfolio outperforms other approaches and effectively reflects asymmetries. Understanding these dynamics and sectoral heterogeneities has important implications for risk management, policy development, and trading practices.

摘要

本研究考察了中国行业商品和产业股票市场之间收益溢出的动态和非对称传播。利用 2007 年 2 月至 2022 年 7 月的日度数据,我们采用时变向量自回归(TVP-VAR)模型来检验行业之间的非对称收益溢出和动态关联。结果表明,这些行业之间存在显著的时变溢出,产业股票是向商品市场传递信息的主要渠道。由于与商品生产和加工密切相关,材料、能源和工业股票板块对这些溢出贡献显著。该研究还发现了显著的非对称溢出,由于重大经济和政治事件的影响,如 2008 年全球金融危机、2015 年中国股市危机、COVID-19 大流行和俄乌战争,坏的回报占主导地位。此外,我们的研究强调了中国市场的独特动态,其中来自股票市场的净信息溢出推动了金融化进程,这与其他市场观察到的双向商品金融化不同。最后,投资组合分析表明,最小关联投资组合的表现优于其他方法,并有效地反映了不对称性。了解这些动态和行业异质性对风险管理、政策制定和交易实践具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d664/10760744/ed175eb83cfa/pone.0296501.g001.jpg

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