EconPapers    
Economics at your fingertips  
 

Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

Tetsuya Takaishi

Papers from arXiv.org

Abstract: We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, cross-correlation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile.

New Economics Papers: this item is included in nep-rmg
Date: 2017-04
References: Add references at CitEc
Citations Track citations by RSS feed

Published in Journal of Physics: Conference Series 738 (2016) 012077

Downloads: (external link)
http://arxiv.org/pdf/1704.08612 Latest version (application/pdf)

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:arx:papers:1704.08612

Access Statistics for this paper

More papers in Papers from arXiv.org
Series data maintained by arXiv administrators ().

 
Page updated 2017-12-19
Handle: RePEc:arx:papers:1704.08612