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

被引:3
|
作者
Lou, Yu [1 ]
Xiao, Chao [1 ,2 ]
Lian, Yi [2 ]
机构
[1] Southwestern Univ Finance & Econ, Sch Finance, Chengdu, Sichuan, Peoples R China
[2] Anyang Univ, Sch Econ & Management, Xinxiang, Henan, Peoples R China
来源
PLOS ONE | 2024年 / 19卷 / 01期
关键词
IMPULSE-RESPONSE ANALYSIS; OIL PRICE SHOCKS; VOLATILITY SPILLOVERS; CRUDE-OIL; EFFICIENT TESTS; FINANCIALIZATION; RETURNS; FUTURES; RISK; MODEL;
D O I
10.1371/journal.pone.0296501
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:39
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