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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Vydáno v:The North American journal of economics and finance Ročník 65; s. 101882
Hlavní autoři: Li, Boyan, Diao, Xundi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.03.2023
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ISSN:1062-9408, 1879-0860
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Abstract 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.
AbstractList 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.
ArticleNumber 101882
Author Diao, Xundi
Li, Boyan
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  organization: Antai College of Economics & Management, Shanghai Jiao Tong University, Shanghai, China
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10.1080/01621459.2012.737745
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10.1214/aos/1176343001
10.1080/00401706.2018.1438926
10.1016/j.iref.2014.12.011
10.1080/03610920801919692
10.18637/jss.v058.i03
10.2307/2529204
10.1016/j.jeconom.2004.02.008
10.1016/j.iref.2021.10.019
10.1080/07362994.2014.917359
10.1016/j.najef.2019.101126
10.1080/17442508.2013.802791
10.1016/j.jedc.2004.01.005
10.1162/003465397557132
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References Killick, Eckley (b9) 2014; 58
Horváth, Liu (b7) 2021
Sen, Srivastava (b15) 1975; 3
Bai (b2) 1997; 79
Killick, Fearnhead, Eckley (b10) 2012; 107
Gregorio, Iacus (b6) 2008; 37
Iacus, Yoshida (b8) 2012; 122
Scott, Knott (b14) 1974; 30
Kirman, Teyssiere (b11) 2005; 29
Aminikhanghahi, Cook (b1) 2017; 51
Chen, Choi, Zhou (b4) 2005; 126
Bardwell, Fearnhead, Eckley, Smith, Spott (b3) 2019; 61
Mishra, Rao (b12) 2014; 86
Mishra, Rao (b13) 2014; 32
Zhu, Xie, Li, Wu (b17) 2015; 38
Zhao, Wen (b16) 2022; 77
Esteve, Navarro-Ibáñez, Prats (b5) 2020; 52
Gregorio (10.1016/j.najef.2023.101882_b6) 2008; 37
Horváth (10.1016/j.najef.2023.101882_b7) 2021
Iacus (10.1016/j.najef.2023.101882_b8) 2012; 122
Mishra (10.1016/j.najef.2023.101882_b13) 2014; 32
Chen (10.1016/j.najef.2023.101882_b4) 2005; 126
Sen (10.1016/j.najef.2023.101882_b15) 1975; 3
Esteve (10.1016/j.najef.2023.101882_b5) 2020; 52
Aminikhanghahi (10.1016/j.najef.2023.101882_b1) 2017; 51
Zhu (10.1016/j.najef.2023.101882_b17) 2015; 38
Killick (10.1016/j.najef.2023.101882_b9) 2014; 58
Killick (10.1016/j.najef.2023.101882_b10) 2012; 107
Bai (10.1016/j.najef.2023.101882_b2) 1997; 79
Bardwell (10.1016/j.najef.2023.101882_b3) 2019; 61
Kirman (10.1016/j.najef.2023.101882_b11) 2005; 29
Scott (10.1016/j.najef.2023.101882_b14) 1974; 30
Zhao (10.1016/j.najef.2023.101882_b16) 2022; 77
Mishra (10.1016/j.najef.2023.101882_b12) 2014; 86
References_xml – volume: 107
  start-page: 1590
  year: 2012
  end-page: 1598
  ident: b10
  article-title: Optimal detection of changepoints with a linear computational cost
  publication-title: Journal of the American Statistical Association
– volume: 32
  start-page: 664
  year: 2014
  end-page: 686
  ident: b13
  article-title: Estimation of drift parameter and change point for switching fractional diffusion processes
  publication-title: Stochastic Analysis and Applications
– volume: 38
  start-page: 18
  year: 2015
  end-page: 28
  ident: b17
  article-title: Change point detection for subprime crisis in American banking: From the perspective of risk dependence
  publication-title: International Review of Economics & Finance
– volume: 29
  start-page: 765
  year: 2005
  end-page: 799
  ident: b11
  article-title: Testing for bubbles and change-points
  publication-title: Journal of Economic Dynamics & Control
– volume: 122
  start-page: 1068
  year: 2012
  end-page: 1092
  ident: b8
  article-title: Estimation for the change point of volatility in a stochastic differential equation
  publication-title: Stochastic Processes and their Applications
– volume: 79
  start-page: 551
  year: 1997
  end-page: 563
  ident: b2
  article-title: Estimation of a change point in multiple regression models
  publication-title: The Review of Economics and Statistics
– volume: 30
  start-page: 507
  year: 1974
  end-page: 512
  ident: b14
  article-title: A cluster analysis method for grouping means in the analysis of variance
  publication-title: Biometrics
– volume: 37
  start-page: 2342
  year: 2008
  end-page: 2357
  ident: b6
  article-title: Least squares volatility change point estimation for partially observed diffusion processes
  publication-title: Communications in Statistics. Theory and Methods
– volume: 61
  start-page: 88
  year: 2019
  end-page: 98
  ident: b3
  article-title: Most recent changepoint detection in panel data
  publication-title: Technometrics
– volume: 52
  year: 2020
  ident: b5
  article-title: Stock prices, dividends, and structural changes in the long-term: The case of U.S.
  publication-title: The North American Journal of Economics and Finance
– volume: 3
  start-page: 98
  year: 1975
  end-page: 108
  ident: b15
  article-title: On tests for detecting change in mean
  publication-title: The Annals of Statistics
– volume: 58
  start-page: 1
  year: 2014
  end-page: 19
  ident: b9
  article-title: Changepoint: An R package for changepoint analysis
  publication-title: Journal of Statistical Software
– volume: 126
  start-page: 79
  year: 2005
  end-page: 114
  ident: b4
  article-title: Nonparametric estimation of structural change points in volatility models for time series
  publication-title: Journal of Econometrics
– volume: 77
  start-page: 481
  year: 2022
  end-page: 492
  ident: b16
  article-title: Risk-return relationship and structural breaks: Evidence from China carbon market
  publication-title: International Review of Economics & Finance
– year: 2021
  ident: b7
  article-title: How to identify the different phases of stock market bubbles statistically?
  publication-title: Finance Research Letters
– volume: 51
  start-page: 339
  year: 2017
  end-page: 367
  ident: b1
  article-title: A survey of methods for time series change point detection
  publication-title: Knowledge and Information Systems
– volume: 86
  start-page: 429
  year: 2014
  end-page: 449
  ident: b12
  article-title: Estimation of change point for switching fractional diffusion processes
  publication-title: Stochastics. An International Journal of Probability and Stochastic Processes
– volume: 122
  start-page: 1068
  issue: 3
  year: 2012
  ident: 10.1016/j.najef.2023.101882_b8
  article-title: Estimation for the change point of volatility in a stochastic differential equation
  publication-title: Stochastic Processes and their Applications
  doi: 10.1016/j.spa.2011.11.005
– volume: 107
  start-page: 1590
  issue: 500
  year: 2012
  ident: 10.1016/j.najef.2023.101882_b10
  article-title: Optimal detection of changepoints with a linear computational cost
  publication-title: Journal of the American Statistical Association
  doi: 10.1080/01621459.2012.737745
– volume: 51
  start-page: 339
  issue: 2
  year: 2017
  ident: 10.1016/j.najef.2023.101882_b1
  article-title: A survey of methods for time series change point detection
  publication-title: Knowledge and Information Systems
  doi: 10.1007/s10115-016-0987-z
– volume: 3
  start-page: 98
  issue: 1
  year: 1975
  ident: 10.1016/j.najef.2023.101882_b15
  article-title: On tests for detecting change in mean
  publication-title: The Annals of Statistics
  doi: 10.1214/aos/1176343001
– volume: 61
  start-page: 88
  issue: 1
  year: 2019
  ident: 10.1016/j.najef.2023.101882_b3
  article-title: Most recent changepoint detection in panel data
  publication-title: Technometrics
  doi: 10.1080/00401706.2018.1438926
– volume: 38
  start-page: 18
  year: 2015
  ident: 10.1016/j.najef.2023.101882_b17
  article-title: Change point detection for subprime crisis in American banking: From the perspective of risk dependence
  publication-title: International Review of Economics & Finance
  doi: 10.1016/j.iref.2014.12.011
– volume: 37
  start-page: 2342
  issue: 15
  year: 2008
  ident: 10.1016/j.najef.2023.101882_b6
  article-title: Least squares volatility change point estimation for partially observed diffusion processes
  publication-title: Communications in Statistics. Theory and Methods
  doi: 10.1080/03610920801919692
– volume: 58
  start-page: 1
  issue: 3
  year: 2014
  ident: 10.1016/j.najef.2023.101882_b9
  article-title: Changepoint: An R package for changepoint analysis
  publication-title: Journal of Statistical Software
  doi: 10.18637/jss.v058.i03
– volume: 30
  start-page: 507
  issue: 3
  year: 1974
  ident: 10.1016/j.najef.2023.101882_b14
  article-title: A cluster analysis method for grouping means in the analysis of variance
  publication-title: Biometrics
  doi: 10.2307/2529204
– volume: 126
  start-page: 79
  issue: 1
  year: 2005
  ident: 10.1016/j.najef.2023.101882_b4
  article-title: Nonparametric estimation of structural change points in volatility models for time series
  publication-title: Journal of Econometrics
  doi: 10.1016/j.jeconom.2004.02.008
– volume: 77
  start-page: 481
  year: 2022
  ident: 10.1016/j.najef.2023.101882_b16
  article-title: Risk-return relationship and structural breaks: Evidence from China carbon market
  publication-title: International Review of Economics & Finance
  doi: 10.1016/j.iref.2021.10.019
– volume: 32
  start-page: 664
  year: 2014
  ident: 10.1016/j.najef.2023.101882_b13
  article-title: Estimation of drift parameter and change point for switching fractional diffusion processes
  publication-title: Stochastic Analysis and Applications
  doi: 10.1080/07362994.2014.917359
– volume: 52
  year: 2020
  ident: 10.1016/j.najef.2023.101882_b5
  article-title: Stock prices, dividends, and structural changes in the long-term: The case of U.S.
  publication-title: The North American Journal of Economics and Finance
  doi: 10.1016/j.najef.2019.101126
– volume: 86
  start-page: 429
  issue: 3
  year: 2014
  ident: 10.1016/j.najef.2023.101882_b12
  article-title: Estimation of change point for switching fractional diffusion processes
  publication-title: Stochastics. An International Journal of Probability and Stochastic Processes
  doi: 10.1080/17442508.2013.802791
– volume: 29
  start-page: 765
  issue: 4
  year: 2005
  ident: 10.1016/j.najef.2023.101882_b11
  article-title: Testing for bubbles and change-points
  publication-title: Journal of Economic Dynamics & Control
  doi: 10.1016/j.jedc.2004.01.005
– year: 2021
  ident: 10.1016/j.najef.2023.101882_b7
  article-title: How to identify the different phases of stock market bubbles statistically?
  publication-title: Finance Research Letters
– volume: 79
  start-page: 551
  issue: 4
  year: 1997
  ident: 10.1016/j.najef.2023.101882_b2
  article-title: Estimation of a change point in multiple regression models
  publication-title: The Review of Economics and Statistics
  doi: 10.1162/003465397557132
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Pruned exact linear time algorithm
Significant events
Two-stage estimation method
Title Structural break in different stock index markets in China
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