Table of Links
I. Introduction
II. Methodology
III. TDA Approach to analyzing multiple time series
IV. Data Analyzed
V. Results and Discussion
A. Obtaining point cloud from stock price time-series
B. EE due to the 2008 Financial crisis
C. EE due to COVID-19 pandemic
D. Impact of COVID-19 on different Indian sectors
VI. Conclusion
VII. Acknowledgments and References
IV. DATA ANALYZED
We have carried out continent-wise analysis during the 2008 financial crisis and the COVID-19 pandemic. We selected four major indices from each continent—North-South America, Europe, Asia, and Oceania—to identify EEs, focusing on these highly developed regions. We have also analyzed the impact of COVID-19 on different sectors in India. The sectors include pharmaceuticals, banking, metals, automobiles, and fast-moving consumer goods (FMCG). We have taken the companies based on their respective Nifty sector indices. We have taken the daily closing price from January 1, 2006 to December 31, 2010 to analyze the 2008 financial crisis and to analyze the crash due to COVID-19 we have taken the data from January 1, 2019 to December 31, 2022. The time duration has been chosen as it captures the whole crash period. The data have been obtained from Yahoo Finance Website[46]. The subsequent sections present the results of our analysis.
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Authors:
(1) Anish Rai, Department of Physics, National Institute of Technology Sikkim, Sikkim, India-737139;
(2) Buddha Nath Sharma, Department of Physics, National Institute of Technology Sikkim, Sikkim, India-737139;
(3) Salam Rabindrajit Luwang, Department of Physics, National Institute of Technology Sikkim, Sikkim, India-737139;
(4) Md.Nurujjaman, Department of Physics, National Institute of Technology Sikkim, Sikkim, India-737139;
(5) Sushovan Majhi, Data Science Program, George Washington University, USA, 20052.
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This paper is available on arxiv under CC BY 4.0 DEED license.
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