Abstract
Covid Pandemic had devastating effects on the human population, resulting in fatalities and social and economic losses. The exponential behaviour of the spread of the virus in recent times has led to assertive impacts on the financial markets all over the world; India is no exception. With the agglomeration of more cases throughout the country; on 23rd March, the stock markets dipped by a record of 13.15% with a huge impact on the countrys GDP. This fall by far, is the largest ever, in Indian history. The returns of the stock market are studied extensively in literature where most of the models assume that the returns are normally distributed ignoring the actuality of contribution of the market crashes and volatility to the fat-tailed structure of the distribution. In this research paper we exploit and understand the statistical distribution of the crash (market returns) which is found out to be strongly fat-tailed; labelling it to be a Black swan event. We have used the NIFTY 50 daily return as the primary dataset for the analysis and observations using Extreme Value statistics. The role of socio-economics in market fluctuation is predominantly explored in this article. The correlation between the Indian market and GDP growth is analysed statistically. Concluding that the distribution of the return generated is fat-tailed and a positive correlation exists between the market and GDP. Hypothesis testing is performed to guarantee the proper distribution and analysis of the results and Power Law distribution is applied.
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Bhuyan, B.P., Prasad, A. (2022). Statistical Distribution and Socio-Economics in Accordance with the Indian Stock Market in the COVID19 Scenario. In: Sharma, H., Vyas, V.K., Pandey, R.K., Prasad, M. (eds) Proceedings of the International Conference on Intelligent Vision and Computing (ICIVC 2021). ICIVC 2021. Proceedings in Adaptation, Learning and Optimization, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-97196-0_16
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