美国大宗商品行业的尾部风险依赖网络。COVID-19是否有所作为?

Dimitra Tzaferi
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摘要

本文的目的是研究2019冠状病毒病之前和期间美国大宗商品部门(农业、畜牧业、能源、工业和贵金属)的尾部风险依赖网络。在2012年3月1日至2022年5月31日的时间范围内,应用受惩罚的分位数回归模型扩展了COVID-19期间的每日商品回报和虚拟变量,提供了CoVaR估计。主要的实证结果是:(i)在极端利好事件的情况下,COVID影响了商品之间的尾部风险连通性(ii)能源部门仍然是商品风险网络中的风险接收者,独立于其条件(福利,爆发)以及(iii)商品部门之间的风险传导联系大多是正的。因此,所有商品市场的对应方(农民、投资者、政策制定者和政府)都不应忽视大流行的不确定性,也不应忽视其他商品部门的冲击可以控制能源部门的繁荣和萧条。最后,大宗商品市场似乎吸引了更多的投机者,而不是对冲者。据作者所知,这是第一篇正式研究美国5个商品行业尾部风险依赖模式在COVID存在方面的潜在差异的研究论文,并定义了用于检测美国商品行业网络尾部风险网络发送者和接收者的新连通性措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TAIL-RISK DEPENDENCE NETWORKS IN THE US COMMODITY SECTORS. HAS COVID-19 MADE A THING?
The objective of this paper is to examine the tail-risk dependence networks in the US commodity sectors: agriculture, livestock, energy, industrial and precious metals before and during COVID-19. Applying penalised quantile regression models extended with the dummy variable for the COVID-19 period in daily commodity returns and in the time horizon 3/1/2012 to 31/5/2022, CoVaR estimations are provided. The main empirical results are that (i) COVID has affected the tail-risk connectedness between commodities in the case of their extreme good events (ii) energy sector has remained a risk receiver in the risk-network of commodities independently of their conditions (welfare, burst) and (iii) the risk transmission linkages between commodity sectors are mostly positive. As a result, all commodity markets counterparts (farmers, investors, policymakers, governments) should not ignore pandemic uncertainties, as well that shocks in the other commodities sectors can control the booms and bursts of the energy sector. Finally, commodity markets seem to attract more speculators than hedgers. To the best of author(s) knowledge this is the first research paper that examines formally potential difference in the pattern of the tail risk dependence of the 5 US commodity sectors with respect to COVID’s existence and defines new connectedness measures for the detection of the tailrisk net transmitters and receivers of the US commodity sectors’ network.
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