{"title":"行业指数对新冠肺炎封锁的反应不同吗?创造财富的经验教训","authors":"S. Agarwal, Megha Agarwal, Renu Ghosh","doi":"10.18311/jbt/2022/30158","DOIUrl":null,"url":null,"abstract":"This research paper is an attempt to study the impact of Covid-19 on the sectoral indices using Event Study Methodology (EVM) and regression models. It tries to analyze the differences in mean returns of one composite and ten sectoral indices on India’s premier National Stock Exchange during four periods-before lockdowns, during the lockdown, during unlocking and post unlock. The analysis is based on 15346 daily observations. Imposition of Lockdown is found to have a positive impact on the daily mean return of the eleven Nifty indices under study. The mean returns of sectoral indices are compared using non-parametric tests. The mean returns across four periods are compared using Friedman’s ANOVA and are found to be significantly different over the four periods. Post Hoc Analysis using Wilcoxon signed-rank test revealed that the daily mean returns during the lockdown were more than the daily mean returns during the period before lockdown, during unlock period or post unlock period. Kruskal Wallis test was used to investigate the equality of means of eleven indices found, mean returns of indices to be equal to each other during all the four alternate periods studied separately. GARCH (1,1) model is then used to estimate returns and variance of sectoral indices A significant portion of variances in sectoral index returns was explained by the variances in market proxy Nifty 50. The study highlights the emerging relevance of the Energy, FMCG, Healthcare, IT and Pharma sector during the lockdown as the abnormal positive returns have increased in these sectors. Infrastructure, Media and realty sectors have been severely affected due to the lockdown. The robustness of estimated parameters is checked by using a dummy variable regression model and it is found that stock markets were strengthening during the period of lockdown. The results of the dummy variable regression model are in line with the results of the Event Study Methodology (EVM) and GARCH (1,1). Overall, the imposition of lockdown as a policy initiative by the Government of India helped in mitigating the effect of Covid-19 on the stock market.","PeriodicalId":431578,"journal":{"name":"Journal of Business Thought","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Do Sectoral Indices React Differently to Lockdowns Imposed Due to Covid-19? Lessons for Wealth Generation\",\"authors\":\"S. Agarwal, Megha Agarwal, Renu Ghosh\",\"doi\":\"10.18311/jbt/2022/30158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research paper is an attempt to study the impact of Covid-19 on the sectoral indices using Event Study Methodology (EVM) and regression models. It tries to analyze the differences in mean returns of one composite and ten sectoral indices on India’s premier National Stock Exchange during four periods-before lockdowns, during the lockdown, during unlocking and post unlock. The analysis is based on 15346 daily observations. Imposition of Lockdown is found to have a positive impact on the daily mean return of the eleven Nifty indices under study. The mean returns of sectoral indices are compared using non-parametric tests. The mean returns across four periods are compared using Friedman’s ANOVA and are found to be significantly different over the four periods. Post Hoc Analysis using Wilcoxon signed-rank test revealed that the daily mean returns during the lockdown were more than the daily mean returns during the period before lockdown, during unlock period or post unlock period. Kruskal Wallis test was used to investigate the equality of means of eleven indices found, mean returns of indices to be equal to each other during all the four alternate periods studied separately. GARCH (1,1) model is then used to estimate returns and variance of sectoral indices A significant portion of variances in sectoral index returns was explained by the variances in market proxy Nifty 50. The study highlights the emerging relevance of the Energy, FMCG, Healthcare, IT and Pharma sector during the lockdown as the abnormal positive returns have increased in these sectors. Infrastructure, Media and realty sectors have been severely affected due to the lockdown. The robustness of estimated parameters is checked by using a dummy variable regression model and it is found that stock markets were strengthening during the period of lockdown. The results of the dummy variable regression model are in line with the results of the Event Study Methodology (EVM) and GARCH (1,1). Overall, the imposition of lockdown as a policy initiative by the Government of India helped in mitigating the effect of Covid-19 on the stock market.\",\"PeriodicalId\":431578,\"journal\":{\"name\":\"Journal of Business Thought\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Business Thought\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18311/jbt/2022/30158\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Thought","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18311/jbt/2022/30158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Do Sectoral Indices React Differently to Lockdowns Imposed Due to Covid-19? Lessons for Wealth Generation
This research paper is an attempt to study the impact of Covid-19 on the sectoral indices using Event Study Methodology (EVM) and regression models. It tries to analyze the differences in mean returns of one composite and ten sectoral indices on India’s premier National Stock Exchange during four periods-before lockdowns, during the lockdown, during unlocking and post unlock. The analysis is based on 15346 daily observations. Imposition of Lockdown is found to have a positive impact on the daily mean return of the eleven Nifty indices under study. The mean returns of sectoral indices are compared using non-parametric tests. The mean returns across four periods are compared using Friedman’s ANOVA and are found to be significantly different over the four periods. Post Hoc Analysis using Wilcoxon signed-rank test revealed that the daily mean returns during the lockdown were more than the daily mean returns during the period before lockdown, during unlock period or post unlock period. Kruskal Wallis test was used to investigate the equality of means of eleven indices found, mean returns of indices to be equal to each other during all the four alternate periods studied separately. GARCH (1,1) model is then used to estimate returns and variance of sectoral indices A significant portion of variances in sectoral index returns was explained by the variances in market proxy Nifty 50. The study highlights the emerging relevance of the Energy, FMCG, Healthcare, IT and Pharma sector during the lockdown as the abnormal positive returns have increased in these sectors. Infrastructure, Media and realty sectors have been severely affected due to the lockdown. The robustness of estimated parameters is checked by using a dummy variable regression model and it is found that stock markets were strengthening during the period of lockdown. The results of the dummy variable regression model are in line with the results of the Event Study Methodology (EVM) and GARCH (1,1). Overall, the imposition of lockdown as a policy initiative by the Government of India helped in mitigating the effect of Covid-19 on the stock market.