IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1112.0297.html
   My bibliography  Save this paper

RQA Application for the Monitoring of Financial and Commodity markets state

Author

Listed:
  • Sergii Piskun
  • Oleksandr Piskun
  • Dmitry Chabanenko

Abstract

Nowadays, when crashes and crises are rather frequent events, an effective monitoring system for the international financial market is needed. Modern nonlinear methods, such as Recurrence Quantification Analysis (RQA), demonstrate the ability to reveal the regularities of the system behavior. Thus, they can be useful for the analysis of the market state in real time. In present paper we did an effort to apply the RQA for the purpose of economic time series monitoring. 12 stock indexes, 6 currency pairs and 4 commodities were taken for the study.

Suggested Citation

  • Sergii Piskun & Oleksandr Piskun & Dmitry Chabanenko, 2011. "RQA Application for the Monitoring of Financial and Commodity markets state," Papers 1112.0297, arXiv.org.
    • Handle: RePEc:arx:papers:1112.0297
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1112.0297
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Claude Diebolt & Catherine Kyrtsou, 2005. "New Trends in Macroeconomics," Post-Print hal-00279607, HAL.
    3. 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.
    4. Gilmore, Claire G., 2001. "An examination of nonlinear dependence in exchange rates, using recent methods from chaos theory," Global Finance Journal, Elsevier, vol. 12(1), pages 139-151.
    5. 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.
    6. 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.
    7. Facchini, Angelo & Mocenni, Chiara & Marwan, Norbert & Vicino, Antonio & Tiezzi, Enzo, 2007. "Nonlinear time series analysis of dissolved oxygen in the Orbetello Lagoon (Italy)," Ecological Modelling, Elsevier, vol. 203(3), pages 339-348.
    8. Claire G. Gilmore, 1996. "Detecting Linear and Nonlinear Dependence in Stock Returns: New Methods Derived from Chaos Theory," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 23(9-10), pages 1357-1377, December.
    9. 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.
    10. 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.
    11. Oleksandr Piskun & Sergii Piskun, 2011. "Recurrence Quantification Analysis of Financial Market Crashes and Crises," Papers 1107.5420, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    5. 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.
    6. 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.
    7. Krishnadas M. & K. P. Harikrishnan & G. Ambika, 2022. "Recurrence measures and transitions in stock market dynamics," Papers 2208.03456, arXiv.org.
    8. Ashe, Sinéad & Egan, Paul, 2023. "Examining financial and business cycle interaction using cross recurrence plot analysis," Finance Research Letters, Elsevier, vol. 51(C).
    9. 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.
    10. 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.
    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. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2013. "Nonlinear dynamics and recurrence plots for detecting financial crisis," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 416-435.
    13. Peter Martey Addo & Monica Billio & Dominique Guegan, 2013. "Turning point chronology for the Euro-Zone: A Distance Plot Approach," Documents de travail du Centre d'Economie de la Sorbonne 13025r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Oct 2013.
    14. Oleksandr Piskun & Sergii Piskun, 2011. "Recurrence Quantification Analysis of Financial Market Crashes and Crises," Papers 1107.5420, arXiv.org.
    15. 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.
    16. 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.
    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. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.
    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. Mostafa Shabani & Martin Magris & George Tzagkarakis & Juho Kanniainen & Alexandros Iosifidis, 2022. "Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots," Papers 2210.14605, arXiv.org, revised Nov 2022.

    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:arx:papers:1112.0297. 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.