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Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis

Author

Listed:
  • DAVID E. ALLEN

    (Department of Finance, Asia University, Taiwan2School of Mathematics and Statistics, The University of Sydney, Australia3School of Business and Law, Edith Cowan University, Australia)

  • MICHAEL McALEER

    (Department of Finance, Asia University, Taiwan4Discipline of Business Analytics, University of Sydney Business School, Australia5Institute of Advanced Studies, Yokohama National University, Japan6Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands7Department of Economic Analysis and ICAE, Complutense University of Madrid, Spain)

  • ROBERT J. POWELL

    (School of Business and Law, Edith Cowan University, Australia)

  • ABHAY K. SINGH

    (Department of Applied Finance, Faculty of Business and Economics, Macquarie University, Australia)

Abstract

This paper presents an application of a recently developed approach by Matteson and James (2014) for the analysis of change points in a dataset, namely major financial market indices converted to financial return series. The general problem concerns the inference of a change in the distribution of a set of time-ordered variables. The approach involves the non-parametric estimation of both the number of change points and the positions at which they occur. The approach is general and does not involve assumptions about the nature of the distributions involved or the type of change beyond the assumption of the existence of the α absolute moment, for some α∈(0,2). The estimation procedure is based on hierarchical clustering and the application of both divisive and agglomerative algorithms. The method is used to evaluate the impact of the Global Financial Crisis (GFC) on the US, French, German, UK, Japanese and Chinese markets, as represented by the S&P500, CAC, DAX, FTSE All Share, Nikkei 225 and Shanghai A share Indices, respectively, from 2003 to 2013. The approach is used to explore the timing and the number of change points in the datasets corresponding to the GFC and subsequent European Debt Crisis.

Suggested Citation

  • DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    • Handle: RePEc:wsi:afexxx:v:13:y:2018:i:02:n:s2010495218500082
    DOI: 10.1142/S2010495218500082
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    Cited by:

    1. Massoud Moslehpour & Shin Hung Pan & Aviral Kumar Tiwari & Wing Keung Wong, 2021. "Editorial in Honour of Professor Michael McAleer," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(4), pages 1-14, December.
    2. Allen, David E. & McAleer, Michael & Powell, Robert J. & Singh, Abhay K., 2017. "Volatility Spillovers from Australia's major trading partners across the GFC," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 159-175.
    3. Tareq Almazyad & Norhayati Zakuan & Laith Alrubaiee & Shamaila Butt & Azmirul Ashaari & Raghed IBRAHIM ESMAEEL, 2024. "Bibliometric Insights into Crisis Management: A Review of Key Literature," Advances in Decision Sciences, Asia University, Taiwan, vol. 28(2), pages 1-34, June.

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    More about this item

    Keywords

    Non-parametric analysis; multiple change points; cluster analysis; global financial crisis;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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