Madheswaran Madhavan, Lingaraja Kasilingam, Duraisamy Pandiaraja
Department of Mathematics, Thiagarajar College, Madurai Kamaraj University, Madurai, Tamil Nadu 625009 India.
Department of Business Administration, Thiagarajar College, Madurai, Tamil Nadu 625009 India.
Environ Dev Sustain. 2023 Feb 22:1-16. doi: 10.1007/s10668-023-03022-5.
Unexpected and sudden spread of the novel Coronavirus disease (COVID-19) has opened up many scopes for researchers in the fields of biotechnology, health care, educational sectors, agriculture, manufacturing, service sectors, marketing, finance, etc. Hence, the researchers are concerned to study, analyze and predict the impact of infection of COVID-19. The COVID-19 pandemic has affected many fields, particularly the stock markets in the financial sector. In this paper, we have proposed an econometric approach and stochastic approach to analyze the stochastic nature of stock price before and during a COVID-19-specific pandemic period. For our study, we considered the BSE SENSEX INDEX closing pricing data from the Bombay Stock Exchange for the period before and during COVID-19. We have applied the statistical tools, namely descriptive statistics for testing the normal distribution of data, unit root test for testing the stationarity, and GARCH and stochastic model for measuring the risk, also investigated drift and volatility (or diffusion) coefficients of the stock price SDE by using R Environment software and formulated the 95% confidence level bound with the help of 500 times simulations. Finally, the results have been obtained from these methods and simulations are discussed.
新型冠状病毒病（COVID-19）的意外突然传播为生物技术、医疗保健、教育部门、农业、制造业、服务业、营销、金融等领域的研究人员开辟了许多研究范围。因此，研究人员关注研究、分析和预测COVID-19感染的影响。COVID-19大流行影响了许多领域，特别是金融部门的股票市场。在本文中，我们提出了一种计量经济学方法和随机方法，以分析COVID-19特定大流行时期之前和期间股票价格的随机性质。为了我们的研究，我们考虑了孟买证券交易所（BSE）在COVID-19之前和期间的SENSEX指数收盘价数据。我们应用了统计工具，即用于检验数据正态分布的描述性统计、用于检验平稳性的单位根检验以及用于测量风险的GARCH和随机模型，还使用R环境软件研究了股票价格随机微分方程的漂移和波动率（或扩散）系数，并通过500次模拟制定了95%置信水平界限。最后，讨论了从这些方法和模拟中获得的结果。
