Quantum Majorization in Market Crash Prediction

J Rhet Montana, Luis A. Souto Arias, Pasquale Cirillo () and Cornelis W. Oosterlee
Additional contact information
J Rhet Montana: CWI Amsterdam, 1098 XG Amsterdam, The Netherlands
Luis A. Souto Arias: Mathematical Institute, Utrecht University, 3584 CS Utrecht, The Netherlands
Pasquale Cirillo: Institute of Business Information Technology, ZHAW School of Management and Law, 8400 Winterthur, Switzerland
Cornelis W. Oosterlee: CWI Amsterdam, 1098 XG Amsterdam, The Netherlands

Risks, 2024, vol. 12, issue 12, 1-18

Abstract: We introduce the Quantum Alarm System, a novel framework that combines the informational advantages of quantum majorization applied to tail pseudo-correlation matrices with the learning capabilities of a reinforced urn process, to predict financial turmoil and market crashes. This integration allows for a more nuanced analysis of the dependence structure in financial markets, particularly focusing on extreme events reflected in the tails of the distribution. Our model is tested using the daily log-returns of the 30 constituents of the Dow Jones Industrial Average, spanning from 2 January 1992 to 30 August 2024. The results are encouraging: in the validation set, the 12-month ahead probability of correct alarm is between 73 % and 80 % , while maintaining a low false alarm rate. Thanks to the application of quantum majorization, the alarm system effectively captures non-traditional and emerging risk sources, such as the financial impact of the COVID-19 pandemic—an area where traditional models often fall short.

Keywords: quantum majorization; pseudo-correlation matrix; forecasting; market crash; alarm system; urn model; risk (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/12/12/204/pdf (application/pdf)
https://www.mdpi.com/2227-9091/12/12/204/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:12:y:2024:i:12:p:204-:d:1545469

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().