Table of Links I. Introduction I. Introduction II. Methodology II. Methodology III. TDA Approach to analyzing multiple time series III. TDA Approach to analyzing multiple time series IV. Data Analyzed IV. Data Analyzed V. Results and Discussion V. Results and Discussion A. Obtaining point cloud from stock price time-series A. Obtaining point cloud from stock price time-series B. EE due to the 2008 Financial crisis B. EE due to the 2008 Financial crisis C. EE due to COVID-19 pandemic C. EE due to COVID-19 pandemic D. Impact of COVID-19 on different Indian sectors D. Impact of COVID-19 on different Indian sectors VI. Conclusion VI. Conclusion VII. Acknowledgments and References VII. Acknowledgments and References V. RESULTS AND DISCUSSION This section shows the result of the identification of continent-wise extreme events (EEs) during the 2008 financial crisis and the COVID-19 pandemic using TDA. It allows the identification of EEs from multiple stock time series at once. Also, a sector-wise impact of the COVID-19 pandemic is analyzed in the Indian stock market. 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. Authors: 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. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv
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