Anwer Zaheer, Khan Ashraf, Naeem Muhammad Abubakr, Tiwari Aviral Kumar
Department of Economics and Finance, Sunway University Business School, Sunway University, Bandar Sunway, Malaysia.
Institute of Business Administration, Karachi, Pakistan.
Ann Oper Res. 2022 Aug 9:1-35. doi: 10.1007/s10479-022-04879-x.
COVID-19 led restrictions make it imperative to study how pandemic affects the systemic risk profile of global commodities network. Therefore, we investigate the systemic risk profile of global commodities network as represented by energy and nonenergy commodity markets (precious metals, industrial metals, and agriculture) in pre- and post-crisis period. We use neural network quantile regression approach of Keilbar and Wang (Empir Econ 62:1-26, 2021) using daily data for the period 01 January 2018-27 October 2021. The findings suggest that at the onset of COVID-19, the two firm-specific risk measures namely value at risk and conditional value of risk explode pointing to increasing systemic risk in COVID-19 period. The risk spillover network analysis reveals moderate to high lower tail connectedness of commodities within each sector and low tail connectedness of energy commodities with the other sectors for both pre- and post-COVID-19 periods. The Systemic Network Risk Index reveals an abrupt increase in systemic risk at the start of pandemic, followed by gradual stabilization. We rank commodities in terms of systemic fragility index and observe that in post COVID-19 period, gold, silver, copper, and zinc are the most fragile commodities while wheat and sugar are the least fragile commodities. We use Systemic Hazard Index to rank commodities with respect to their risk contribution to global commodities network. During post COVID-19 period, the energy commodities (except natural gas) contribute most to the systemic risk. Our study has important implications for policymakers and the investment industry.
新冠疫情导致的限制措施使得研究这场大流行如何影响全球大宗商品网络的系统性风险状况变得势在必行。因此，我们调查了以能源和非能源商品市场（贵金属、工业金属和农业）为代表的全球大宗商品网络在危机前和危机后的系统性风险状况。我们使用了Keilbar和Wang（《实证经济学》62:1 - 26，2021）的神经网络分位数回归方法，采用了2018年1月1日至2021年10月27日期间的每日数据。研究结果表明，在新冠疫情爆发之初，两项特定公司风险指标，即风险价值和条件风险价值急剧上升，表明新冠疫情期间系统性风险在增加。风险溢出网络分析显示，在新冠疫情前后两个时期，每个部门内的商品之间存在中度到高度的下尾连通性，而能源商品与其他部门之间的尾端连通性较低。系统性网络风险指数显示，在大流行开始时系统性风险急剧上升，随后逐渐稳定。我们根据系统性脆弱性指数对商品进行排名，观察到在新冠疫情后时期，黄金、白银、铜和锌是最脆弱的商品，而小麦和糖是最不脆弱的商品。我们使用系统性风险指数对商品在全球大宗商品网络中的风险贡献进行排名。在新冠疫情后时期，能源商品（天然气除外）对系统性风险的贡献最大。我们的研究对政策制定者和投资行业具有重要意义。
