IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1107.5420.html
   My bibliography  Save this paper

Recurrence Quantification Analysis of Financial Market Crashes and Crises

Author

Listed:
  • Oleksandr Piskun
  • Sergii Piskun

Abstract

Financial markets are systems with the complex behavior, that can be hardly analyzed by means of linear methods. Recurrence Quantification Analysis (RQA) is a nonlinear methodology, which is able to work with the nonstationary and short data series. Thus, we apply RQA for the studying of the critical events on financial markets. For the present research, stock crashes of DJI 1929; DJI, NYSE and S&P500 1987; NASDAQ 2000; HSI 1994, 1997 and Spanish 1992, Portuguese 1992, British 1992, German 1992, Italian 1992, Mexican 1994, Brazilian 1999, Indonesian 1997, Thai 1997, Malaysian 1997, Philippine 1997, Russian 1998, Turkish 2001, Argentine 2002 currency devaluations were taken. The recent world financial crisis of 2007-2010 was considered as well. The possibility of LAM measure to serve as a tool for the revealing, monitoring, analysing and precursoring of financial bubbles, crises and crashes was asserted.

Suggested Citation

  • Oleksandr Piskun & Sergii Piskun, 2011. "Recurrence Quantification Analysis of Financial Market Crashes and Crises," Papers 1107.5420, arXiv.org.
    • Handle: RePEc:arx:papers:1107.5420
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1107.5420
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Strozzi, Fernanda & Zaldívar, José-Manuel & Zbilut, Joseph P., 2007. "Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 487-499.
    2. Strozzi, Fernanda & Zaldı́var, José-Manuel & Zbilut, Joseph P, 2002. "Application of nonlinear time series analysis techniques to high-frequency currency exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 520-538.
    3. A. Fabretti & M. Ausloos, 2005. "Recurrence Plot And Recurrence Quantification Analysis Techniques For Detecting A Critical Regime. Examples From Financial Market Inidices," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 671-706.
    4. McKenzie, Michael D., 2001. "Chaotic behavior in national stock market indices: New evidence from the close returns test," Global Finance Journal, Elsevier, vol. 12(1), pages 35-53.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sergii Piskun & Oleksandr Piskun & Dmitry Chabanenko, 2011. "RQA Application for the Monitoring of Financial and Commodity markets state," Papers 1112.0297, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Teresa Aparicio & Dulce Saura, 2013. "Do Exchange Rate Series Present General Dependence? Some Results using Recurrence Quantification Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 5(10), pages 678-686.
    2. Bastos, João A. & Caiado, Jorge, 2011. "Recurrence quantification analysis of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1315-1325.
    3. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    4. Giuseppe Orlando & Giovanna Zimatore, 2021. "Recurrence Quantification Analysis of Business Cycles," Dynamic Modeling and Econometrics in Economics and Finance, in: Giuseppe Orlando & Alexander N. Pisarchik & Ruedi Stoop (ed.), Nonlinearities in Economics, chapter 0, pages 269-282, Springer.
    5. Sergii Piskun & Oleksandr Piskun & Dmitry Chabanenko, 2011. "RQA Application for the Monitoring of Financial and Commodity markets state," Papers 1112.0297, arXiv.org.
    6. Ioannis Andreadis & Athanasios D. Fragkou & Theodoros E. Karakasidis & Apostolos Serletis, 2023. "Nonlinear dynamics in Divisia monetary aggregates: an application of recurrence quantification analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-17, December.
    7. Zaldívar, José-Manuel & Strozzi, Fernanda & Dueri, Sibylle & Marinov, Dimitar & Zbilut, Joseph P., 2008. "Characterization of regime shifts in environmental time series with recurrence quantification analysis," Ecological Modelling, Elsevier, vol. 210(1), pages 58-70.
    8. Ayan Bhattacharya & Rudra Sensarma, 2013. "Non-linearities in Emerging Financial Markets: Evidence from India," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 165-175, July.
    9. Didier Sornette & Wei-Xing Zhou, 2005. "Non-parametric determination of real-time lag structure between two time series: the 'optimal thermal causal path' method," Quantitative Finance, Taylor & Francis Journals, vol. 5(6), pages 577-591.
    10. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    11. Heng-Li Yang & Han-Chou Lin, 2017. "Applying the Hybrid Model of EMD, PSR, and ELM to Exchange Rates Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 99-116, January.
    12. Strozzi, Fernanda & Zaldívar, José-Manuel & Zbilut, Joseph P., 2007. "Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 487-499.
    13. Oya, Shunsuke & Aihara, Kazuyuki & Hirata, Yoshito, 2014. "An absolute measure for a key currency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 15-23.
    14. Aparicio, Teresa & Pozo, Eduardo F. & Saura, Dulce, 2008. "Detecting determinism using recurrence quantification analysis: Three test procedures," Journal of Economic Behavior & Organization, Elsevier, vol. 65(3-4), pages 768-787, March.
    15. Girault, Jean-Marc, 2015. "Recurrence and symmetry of time series: Application to transition detection," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 11-28.
    16. Strozzi, F. & Zaldívar, J.M., 2005. "Non-linear forecasting in high-frequency financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 463-479.
    17. Madhavan, Vinodh, 2013. "Nonlinearity in investment grade Credit Default Swap (CDS) Indices of US and Europe: Evidence from BDS and close-returns tests," Global Finance Journal, Elsevier, vol. 24(3), pages 266-279.
    18. Charakopoulos, Avraam & Karakasidis, Theodoros & Sarris, loannis, 2019. "Pattern identification for wind power forecasting via complex network and recurrence plot time series analysis," Energy Policy, Elsevier, vol. 133(C).
    19. B. Goswami & G. Ambika & N. Marwan & J. Kurths, 2011. "On interrelations of recurrences and connectivity trends between stock indices," Papers 1103.5189, arXiv.org.
    20. BenSaïda, Ahmed & Litimi, Houda, 2013. "High level chaos in the exchange and index markets," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 90-95.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1107.5420. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.