Global Financial Analysis: A TDA-Based Approach to Market Crashes

Written by marketcrash | Published 2025/08/29
Tech Story Tags: stock-market | stock-market-crashes | extreme-events-(ees) | persistent-homology | wasserstein-distance | financial-crises-analysis | covid-19-pandemic-impact | financial-crisis

TLDRThis article reveals how TDA successfully identified EEs across different continents during the 2008 and COVID-19 crises and provides a sectoral analysis of the pandemic's impact in the Indian stock market.via the TL;DR App

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

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.


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


Written by marketcrash | Market Crash
Published by HackerNoon on 2025/08/29