{"title":"新冠肺炎疫情将对七国集团股市产生什么影响?交叉量子图方法的新证据","authors":"N. Hung","doi":"10.15196/RS130203","DOIUrl":null,"url":null,"abstract":"With several commodity and financial markets allegedly performing poorly during the coronavirus disease (Covid-19) pandemic, the objective of this study is to examine how the pandemic has affected stock markets in the G7 economies. The study applies the recently developed cross-quantilogram model introduced by Han et al. (2016) to investigate quantile dependence between the conditional stock return distributions of G7 countries and the total daily global confirmed Covid-19 cases across investment horizons. The results reveal that the cross-quantile dependence between the confirmed Covid-19 cases and G7 stock returns is most significant in the short and medium term. The interlinkage weakens as the lag period lengthens. These findings imply that, in the short and medium term, stock markets in the G7 countries reacted negatively and disproportionately to the increase in the number of daily verified Covid-19 cases. Besides, cross-quantile correlations calculated from recursive subsamples indicate that they change over time, especially in low and medium quantiles, suggesting that they are prone to jumps and discontinuities in the dependence structures. The findings can aid investors and policymakers in better understanding stock market dynamics, particularly during times of great stress and unknown events.","PeriodicalId":44388,"journal":{"name":"Regional Statistics","volume":"1 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"What effects will Covid-19 have on the G7 stock markets? New evidence from a cross-quantilogram approach\",\"authors\":\"N. Hung\",\"doi\":\"10.15196/RS130203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With several commodity and financial markets allegedly performing poorly during the coronavirus disease (Covid-19) pandemic, the objective of this study is to examine how the pandemic has affected stock markets in the G7 economies. The study applies the recently developed cross-quantilogram model introduced by Han et al. (2016) to investigate quantile dependence between the conditional stock return distributions of G7 countries and the total daily global confirmed Covid-19 cases across investment horizons. The results reveal that the cross-quantile dependence between the confirmed Covid-19 cases and G7 stock returns is most significant in the short and medium term. The interlinkage weakens as the lag period lengthens. These findings imply that, in the short and medium term, stock markets in the G7 countries reacted negatively and disproportionately to the increase in the number of daily verified Covid-19 cases. Besides, cross-quantile correlations calculated from recursive subsamples indicate that they change over time, especially in low and medium quantiles, suggesting that they are prone to jumps and discontinuities in the dependence structures. The findings can aid investors and policymakers in better understanding stock market dynamics, particularly during times of great stress and unknown events.\",\"PeriodicalId\":44388,\"journal\":{\"name\":\"Regional Statistics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Regional Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15196/RS130203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regional Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15196/RS130203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"GEOGRAPHY","Score":null,"Total":0}
What effects will Covid-19 have on the G7 stock markets? New evidence from a cross-quantilogram approach
With several commodity and financial markets allegedly performing poorly during the coronavirus disease (Covid-19) pandemic, the objective of this study is to examine how the pandemic has affected stock markets in the G7 economies. The study applies the recently developed cross-quantilogram model introduced by Han et al. (2016) to investigate quantile dependence between the conditional stock return distributions of G7 countries and the total daily global confirmed Covid-19 cases across investment horizons. The results reveal that the cross-quantile dependence between the confirmed Covid-19 cases and G7 stock returns is most significant in the short and medium term. The interlinkage weakens as the lag period lengthens. These findings imply that, in the short and medium term, stock markets in the G7 countries reacted negatively and disproportionately to the increase in the number of daily verified Covid-19 cases. Besides, cross-quantile correlations calculated from recursive subsamples indicate that they change over time, especially in low and medium quantiles, suggesting that they are prone to jumps and discontinuities in the dependence structures. The findings can aid investors and policymakers in better understanding stock market dynamics, particularly during times of great stress and unknown events.
期刊介绍:
The periodical welcomes studies, research and conference reports, book reviews, discussion articles reflecting on our former articles. The periodical welcomes articles from the following areas: regional statistics, regional science, social geography, regional planning, sociology, geographical information science Goals of the journal: high-level studies in the field of regional analyses, to encourage the exchange of views and discussion among researchers in the area of regional researches.