Identifying Extreme Events: A Stock Market Case Study of North America and Europe

Explore a TDA-based analysis of the 2008 financial crisis, which uses L¹ and L² norms to identify extreme events in the stock markets of North America and Europe.


This content originally appeared on HackerNoon and was authored by Market Crash

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

A. Obtaining point cloud from stock price time-series

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:::info 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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:::info This paper is available on arxiv under CC BY 4.0 DEED license.

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This content originally appeared on HackerNoon and was authored by Market Crash


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