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The swiftly growing and overwhelming epidemic in India has intensified the question: What will the trend and magnitude of impact of the novel coronavirus disease 2019 (COVID-19) be in India in the near future? To answer the present question, the study requires ample historical data to make an accurate forecast of the blowout of expected confirmed cases. All at once, no prediction can be certain as the past seldom reiterates itself in the future likewise. Besides, forecasts are influenced by a number of factors like reliability of the data and psychological factors like perception and reaction of the people to the hazards arising from the epidemic. The present study presents a simple but powerful and objective, that is, autoregressive integrated moving average (ARIMA) approach, to analyse the temporal dynamics of the COVID-19 outbreak in India in the time window 30 January 2020 to 16 September 2020 and to predict the final size and trend of the epidemic over the period after 16 September 2020 with Indian epidemiological data at national and state levels. With the assumption that the data that have been used are reliable and that the future will continue to track the same outline as in the past, underlying forecasts based on ARIMA model suggest an unending increase in the number of confirmed COVID-19 cases in India in the near future. The present article suggests varying epidemic’s inflection point and final size for underlying states and for the mainland, India. The final size at national level is expected to reach 25,669,294 in the next 230 days, with infection point that can be expected to be projected only on 23 April 2021. The study has enormous potential to plan and make decisions to control the further spread of epidemic in India and provides objective forecasts for the confirmed cases of COVID-19 in the coming days corresponding to the respective COVID periods of the underlying regions.

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This paper aims to investigate the cointegration of the spot market and future indices (NIFTY, NIKKEI, S&P 500 AND Singapore FTSE) of selected developed and developing nations from January 2011 to December, 2021. The Johansen cointegration test, Granger Causality Test, and Vector Error Correction Model (VECM) are all used to gauge the degree of cointegration. The study's empirical findings support the hypothesis that there is cointegration between the spot market and future market indices of selected global markets. Comparative Granger tests for causality using the error correction model and results of error correction tests reveal interdependencies. The fact that the S&P 500 spot market index and future market index have a bi-directional causality shows that how interdependent these stock indices are.  But, in case of Singapore FTSE, there is uni-causality from SGX future to SGX Spot indices. And in rest of indices (NIFTY and NIKKEI), there is no causality between spot and future stock indices. The study's conclusions show that investors may create diverse portfolio strategies to manage risk.

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