Do Sectoral Indices React Differently to Lockdowns Imposed Due to Covid-19? Lessons for Wealth Generation

S. Agarwal, Megha Agarwal, Renu Ghosh
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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.
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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
本文试图利用事件研究方法(EVM)和回归模型来研究Covid-19对行业指数的影响。它试图分析印度主要的国家证券交易所在四个时期——封锁前、封锁期间、解锁期间和解锁后——一个综合指数和十个行业指数的平均回报差异。该分析基于15346个日常观察。研究发现,实施封锁对研究中的11个Nifty指数的日平均回报率产生了积极影响。使用非参数检验比较了部门指数的平均回报率。四个时期的平均收益使用弗里德曼方差分析进行比较,发现四个时期之间存在显着差异。使用Wilcoxon sign -rank检验的事后分析显示,封锁期间的日平均收益大于封锁前、解锁期间或解锁后期间的日平均收益。采用Kruskal Wallis检验对11个指标进行均值相等性检验,发现各指标的均值收益率在4个交替期均相等。然后使用GARCH(1,1)模型来估计行业指数的收益和方差。行业指数收益的很大一部分方差可以用市场代理Nifty 50的方差来解释。该研究强调了能源、快速消费品、医疗保健、IT和制药行业在封锁期间的新兴相关性,因为这些行业的异常正回报有所增加。由于封锁,基础设施、媒体和房地产行业受到严重影响。利用虚拟变量回归模型检验了估计参数的稳健性,发现股市在封锁期间走强。虚拟变量回归模型的结果与事件研究方法学(EVM)和GARCH(1,1)的结果一致。总体而言,作为印度政府的一项政策举措,实施封锁有助于减轻新冠肺炎对股市的影响。
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