High-Order Networks and Stock Market Crashes

Andrii Bielinskyi, Andrii Bielinskyi, Vladimir Soloviev, Vladimir Soloviev, Serhii Hushko, Arnold Kiv, Arnold Kiv, Andriy V. Matviychuk, Andriy V. Matviychuk

2022

Abstract

Network analysis has proven to be a powerful method to characterize complexity in socio-economic systems, and to understand their underlying dynamical features. Here, we propose to characterize the temporal evolution of higher-order dependencies within the framework of high-order networks. We test the possibility of financial crashes identification on the example of the Dow Jones Industrial Average (DJIA) index. Regarding topological measures of complexity, we see drastic changes in the complexity of the system during crisis events. Using high-order network analysis and topology, we show that, unlike traditional tools, the presented method is the most perspective, comparing to traditional methods of financial time series analysis.

Paper Citation

in Harvard Style

Bielinskyi A., Soloviev V., Hushko S., Kiv A. and V. Matviychuk A. (2022). High-Order Networks and Stock Market Crashes. In Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy - Volume 1: M3E2; ISBN 978-989-758-640-8, SciTePress, pages 134-144. DOI: 10.5220/0011931900003432

in Bibtex Style

@conference{m3e222,
author={Andrii Bielinskyi and Vladimir Soloviev and Serhii Hushko and Arnold Kiv and Andriy V. Matviychuk},
title={High-Order Networks and Stock Market Crashes},
booktitle={Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy - Volume 1: M3E2},
year={2022},
pages={134-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011931900003432},
isbn={978-989-758-640-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy - Volume 1: M3E2
TI - High-Order Networks and Stock Market Crashes
SN - 978-989-758-640-8
AU - Bielinskyi A.
AU - Soloviev V.
AU - Hushko S.
AU - Kiv A.
AU - V. Matviychuk A.
PY - 2022
SP - 134
EP - 144
DO - 10.5220/0011931900003432
PB - SciTePress