Applications of random-matrix theory and nonparametric change-point analysis to three notable systemic crises

• Main Authors: David Melkuev, Danqiao Guo, Tony S. Wirjanto
• Format: Article
• Language: English
• Published: AIMS Press 2018-06-01
• Series: Quantitative Finance and Economics
• Subjects: global financial crisis| Eurozone sovereign debt crisis| Asian financial crisis| equities|bonds| CDS| contract| principal component analysis| random matrix theory| nonparametric changepoint analysis
• Online Access: http://www.aimspress.com/article/10.3934/QFE.2018.2.413/fulltext.html
• ISSN: 2573-0134

This paper studies association between changes in absorption ratio and aggregate market returns in three systemic crises across a broad class of assets. Time series of normalized eigenvalue estimates reveal that crises are characterized by a general breakdown of correlation structure. The structure of return correlations is nonlinear and nonstationary across dierent asset groups. So we introduce a nonparametric technique to monitor divergence in distributions underlying successive observations of normalized dominant eigenvalue of the returns. Periods of high divergence imply a change in the correlation structure of asset returns. They are found to either precede or coincide with systemic shocks. An additional parametric analysis is provided as an informal check on the results obtained in the paper.