IDEAS home Printed from https://ideas.repec.org/a/eee/jeborg/v65y2008i3-4p768-787.html
   My bibliography  Save this article

Detecting determinism using recurrence quantification analysis: Three test procedures

Author

Listed:
  • Aparicio, Teresa
  • Pozo, Eduardo F.
  • Saura, Dulce

Abstract

In this paper we use the "Recurrence Quantification Analysis" proposed by Zbilut and Webber [Zbilut, J.P., Webber Jr., C.L., 1992. Embeddings and delays as derived from quantification of recurrence plots. Physics Letters A 171, 199-203] to develop three test procedures that allow us to detect general dependence and, from that, possible deterministic behavior underlying series. Based on the concept of "Percent of Determinism" we obtain three statistics that allow us to test for the null hypothesis of randomness. The results of the application of these procedures to a set of simulated and real series reveal good behavior in a wide variety of situations, including different sample sizes and series affected by noise.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:jeborg:v:65:y:2008:i:3-4:p:768-787
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-2681(06)00225-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jorge Belaire-Franch, & Dulce Contreras & Lorena Tordera-Lledo, 2002. "Assessing Non-Linear Structures in Real Exchange Rates Using Recurrence Plot Strategies," Computing in Economics and Finance 2002 239, Society for Computational Economics.
    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. Teresa Aparicio & Eduardo Pozo & Dulce Saura, 2002. "The nearest neighbour method as a test for detecting complex dynamics in financial series. An empirical application," Applied Financial Economics, Taylor & Francis Journals, vol. 12(7), pages 517-525.
    4. Mayfield, E Scott & Mizrach, Bruce, 1992. "On Determining the Dimension of Real-Time Stock-Price Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 367-374, July.
    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. Aparicio Teresa & Pozo Eduardo F. & Saura Dulce, 2010. "Detecting Determinism Using Recurrence Quantification Analysis: A Solution to the Problem of Embedding," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-12, December.
    2. Zhang, Yali & Wang, Jun, 2019. "Linkage influence of energy market on financial market by multiscale complexity synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 254-266.
    3. Saul Hazledine & Jongho Sun & Derin Wysham & J Allan Downie & Giles E D Oldroyd & Richard J Morris, 2009. "Nonlinear Time Series Analysis of Nodulation Factor Induced Calcium Oscillations: Evidence for Deterministic Chaos?," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-10, August.
    4. 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.
    5. 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.
    6. Aparicio Teresa & Saura Dulce & Pozo Eduardo F., 2021. "A Strategy for the Use of the Cross Recurrence Quantification Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-14, April.

    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. 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.
    2. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    3. 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.
    4. Sergii Piskun & Oleksandr Piskun & Dmitry Chabanenko, 2011. "RQA Application for the Monitoring of Financial and Commodity markets state," Papers 1112.0297, arXiv.org.
    5. Belaire-Franch, Jorge, 2004. "Testing for non-linearity in an artificial financial market: a recurrence quantification approach," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 483-494, August.
    6. 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.
    7. Tzagkarakis George & Dionysopoulos Thomas & Achim Alin, 2016. "Recurrence quantification analysis of denoised index returns via alpha-stable modeling of wavelet coefficients: detecting switching volatility regimes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 75-96, February.
    8. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    9. Karagianni Stella & Kyrtsou Catherine, 2011. "Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    10. 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.
    11. Elena Olmedo, 2014. "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 183-197, February.
    12. Petre Caraiani & Emmanuel Haven, 2013. "The Role of Recurrence Plots in Characterizing the Output-Unemployment Relationship: An Analysis," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    13. Marcos álvarez Díaz & Josep Mateu-Sbert, 2011. "Forecasting Daily Air Arrivals in Mallorca Island Using Nearest Neighbour Methods," Tourism Economics, , vol. 17(1), pages 191-208, February.
    14. 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.
    15. Álvarez-Díaz, Marcos & Hammoudeh, Shawkat & Gupta, Rangan, 2014. "Detecting predictable non-linear dynamics in Dow Jones Islamic Market and Dow Jones Industrial Average indices using nonparametric regressions," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 22-35.
    16. Eduardo Pozo & Lucia Amboj, 2001. "Noise reduction methods and the Grassberger-Procaccia algorithm. A simulation study," Applied Economics Letters, Taylor & Francis Journals, vol. 8(2), pages 71-75.
    17. Oleksandr Piskun & Sergii Piskun, 2011. "Recurrence Quantification Analysis of Financial Market Crashes and Crises," Papers 1107.5420, arXiv.org.
    18. Nie, Chun-Xiao, 2017. "Correlation dimension of financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 632-639.
    19. 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.
    20. Nie, Chun-Xiao, 2019. "Applying correlation dimension to the analysis of the evolution of network structure," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 294-303.

    More about this item

    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:eee:jeborg:v:65:y:2008:i:3-4:p:768-787. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jebo .

    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.