You sneeze, and the markets are paranoid: the fear, uncertainty and distress sentiments impact of the COVID-19 pandemic on the stock-bond correlation

被引:22
作者
Banerjee, Ameet Kumar [1 ]
机构
[1] XLRI Xavier Sch Management, Jamshedpur, Bihar, India
关键词
COVID-19; Stock-bond correlation; DCC-GARCH; Markov regime-switching regression; AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY; INVESTOR SENTIMENT; DETERMINANTS; MODEL; FLIGHT;
D O I
10.1108/JRF-04-2022-0095
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Purpose This paper investigates the influence of three different sentiment indicators on the time-varying stock-bond correlation of 15 countries during the global crisis period of the coronavirus disease 2019 (COVID-19) pandemic. Design/methodology/approach The author uses the time-varying correlation estimated using the autoregressive moving average -dynamic conditional correlation - generalised autoregressive conditional heteroskedasticity (ARMA-DCC-GARCH) model to achieve this aim. The impact of investor sentiment on the stock-bond correlation was analysed using the Markov regime-switching regression. Findings The study results show that the sentiment indicators of fear, uncertainty and distress have a pronounced negative impact on the stock-bond correlation. They further provide evidence of a strong regime effect on the stock-bond correlation with sentiment indicators. Practical implications The paper has a relevant impact on policymakers and fund managers. First, the policymakers now have more insightful evidence of how the stock and bond markets react during crises. Second, the fund managers need to focus on behavioural variables as they may be driving factors in crisis periods that may impair portfolio management. Originality/value To the best of my knowledge, the paper is the first to throw light on the behaviour of the stock-bond correlation for 15 countries during the COVID-19 period.
引用
收藏
页码:652 / 668
页数:17
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