{"title":"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?","authors":"Dimitra Tzaferi","doi":"10.47509/ijaeb.2023.v05i01.03","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":344009,"journal":{"name":"INDIAN JOURNAL OF APPLIED ECONOMICS AND BUSINESS","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"TAIL-RISK DEPENDENCE NETWORKS IN THE US COMMODITY SECTORS. HAS COVID-19 MADE A THING?\",\"authors\":\"Dimitra Tzaferi\",\"doi\":\"10.47509/ijaeb.2023.v05i01.03\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":344009,\"journal\":{\"name\":\"INDIAN JOURNAL OF APPLIED ECONOMICS AND BUSINESS\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INDIAN JOURNAL OF APPLIED ECONOMICS AND BUSINESS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47509/ijaeb.2023.v05i01.03\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"INDIAN JOURNAL OF APPLIED ECONOMICS AND BUSINESS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47509/ijaeb.2023.v05i01.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.