股票市场
经济
库存(枪支)
金融经济学
货币经济学
业务
地理
考古
背景(考古学)
作者
Min Ouyang,Huiling Xiao
标识
DOI:10.1016/j.frl.2024.105233
摘要
This study employs a combination of the CAViaR model and the TVP-VAR-based connectedness approach to investigate tail risk spillovers among Chinese stock sectors. Using daily data on ten sector indices from January 5, 2006, to September 28, 2023, the empirical findings reveal significant time-varying tail risk spillovers among sectors, with heightened spillovers observed during extreme events. Moreover, the industrials, materials, and consumer discretionary sectors are found to be the senders of tail risk spillovers, while the energy, estate, and finance sectors are receivers during the sample period. The findings carry substantial implications for policy shaping and investment decision-making.
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