Structural break in different stock index markets in China

This paper first presents a two-stage change point estimation approach in the framework of online analysis to detect the Chinese stock market abrupt variations during the period from 4 January 2005 to 10 December 2021. As a check, the pruned exact linear time (PELT) algorithm method is applied to de...

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Bibliographic Details
Published in:The North American journal of economics and finance Vol. 65; p. 101882
Main Authors: Li, Boyan, Diao, Xundi
Format: Journal Article
Language:English
Published: Elsevier Inc 01.03.2023
Subjects:
Change point
Pruned exact linear time algorithm
Significant events
Two-stage estimation method
Pruned exact linear time algorithm
C52
C22
Two-stage estimation method
C13
G15
Change point
Significant events
ISSN:1062-9408, 1879-0860
Online Access:Get full text
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Summary:This paper first presents a two-stage change point estimation approach in the framework of online analysis to detect the Chinese stock market abrupt variations during the period from 4 January 2005 to 10 December 2021. As a check, the pruned exact linear time (PELT) algorithm method is applied to detect structural changes in the framework of offline analysis in terms of all data. We select four representative indices in Chinese markets to find some important time-stamp tags. The results show that all indices can detect some common events, while the small-cap and small-mid-cap indices can identify local risks such as China’s market freezing. Besides, we find some events such as the global financial crisis and China’s market freezing can incur the inverse anomaly with higher volatility in lower reward. •Adopt two-stage change point estimation method to trace the structural change online.•Use pruned exact linear time algorithm to detect multiple change points offline.•Four representative indices in Chinese markets are utilized for empirical analysis.•The small-cap and small-mid-cap indices can identify China’s market freezing.•Some financial events incur higher volatility with lower reward.
ISSN:1062-9408
1879-0860
DOI:10.1016/j.najef.2023.101882