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

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

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