IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v93y1996i1p155-172.html
   My bibliography  Save this article

Chaos and nonlinear dynamics in financial and nonfinancial time series: Evidence from Finland

Author

Listed:
  • Takala, Kari
  • Viren, Matti

Abstract

No abstract is available for this item.

Suggested Citation

  • Takala, Kari & Viren, Matti, 1996. "Chaos and nonlinear dynamics in financial and nonfinancial time series: Evidence from Finland," European Journal of Operational Research, Elsevier, vol. 93(1), pages 155-172, August.
  • Handle: RePEc:eee:ejores:v:93:y:1996:i:1:p:155-172
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0377-2217(95)00150-6
    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. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    2. Brock, W. A., 1986. "Distinguishing random and deterministic systems: Abridged version," Journal of Economic Theory, Elsevier, vol. 40(1), pages 168-195, October.
    3. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
    4. repec:zbw:bofrdp:1995_009 is not listed on IDEAS
    5. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    6. Frank, Murray Z & Stengos, Thanasis, 1988. "Chaotic Dynamics in Economic Time-Series," Journal of Economic Surveys, Wiley Blackwell, vol. 2(2), pages 103-133.
    7. Mullineux, Andy & Peng, WenSheng, 1993. "Nonlinear Business Cycle Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 7(1), pages 41-83.
    8. Ramsey, James B. & Rothman, Philip, 1988. "Characterization Of The Time Irreversibility Of Economic Time Series: Estimators And Test Statistics," Working Papers 88-39, C.V. Starr Center for Applied Economics, New York University.
    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. Caraiani, Petre, 2012. "Is the Romanian Business Cycle Characterized by Chaos?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 142-151, September.
    2. Alonso-Rivera, Angélica & Cruz-Aké, Salvador & Venegas-Martínez, Francisco, 2017. "Variables monetarias y formación de burbujas especulativas: un análisis de sincronización de frecuencias (1992-2013)," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 12(24), pages 7-24, Primer se.
    3. Caraiani, Petre, 2012. "Nonlinear dynamics in CEE stock markets indices," Economics Letters, Elsevier, vol. 114(3), pages 329-331.
    4. Bonache, Adrien & Moris, Karen, 2009. "Nonlinear and chaotic patterns in Japanese video game console sales and consequences for management control," MPRA Paper 18196, University Library of Munich, Germany.
    5. Foued Sa^adaoui, 2023. "Structured Multifractal Scaling of the Principal Cryptocurrencies: Examination using a Self-Explainable Machine Learning," Papers 2304.08440, arXiv.org.
    6. Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    7. Saâdaoui, Foued, 2023. "Skewed multifractal scaling of stock markets during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    8. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2021. "Nonlinearities and Chaos: A New Analysis of CEE Stock Markets," Mathematics, MDPI, vol. 9(7), pages 1-13, March.
    9. BenSaïda, Ahmed & Litimi, Houda, 2013. "High level chaos in the exchange and index markets," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 90-95.
    10. Matti Vir, 2000. "Analysing long memory and asymmetries," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 240-258.

    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. Takala, Kari & Virén, Matti, 1995. "Testing nonlinear dynamics, long memory and chaotic behaviour with macroeconomic data," Research Discussion Papers 9/1995, Bank of Finland.
    2. repec:zbw:bofrdp:1995_009 is not listed on IDEAS
    3. Takala, Kari & Virén, Matti, 1995. "Testing nonlinear dynamics, long memory and chaotic behaviour with macroeconomic data," Bank of Finland Research Discussion Papers 9/1995, Bank of Finland.
    4. repec:zbw:bofrdp:1994_011 is not listed on IDEAS
    5. Takala, Kari & Virén, Matti, 1994. "Chaos and nonlinear dynamics : evidence from Finland," Research Discussion Papers 11/1994, Bank of Finland.
    6. Takala, Kari & Virén, Matti, 1994. "Chaos and nonlinear dynamics: evidence from Finland," Bank of Finland Research Discussion Papers 11/1994, Bank of Finland.
    7. Mills, Terence C., 1995. "Business cycle asymmetries and non-linearities in U.K. macroeconomic time series," Ricerche Economiche, Elsevier, vol. 49(2), pages 97-124, June.
    8. Takala, Kari & Virén, Matti, 1993. "Testing nonlinearities with Finnish historical time series," Bank of Finland Research Discussion Papers 15/1993, Bank of Finland.
    9. Matilla-Garcia, Mariano, 2007. "A non-parametric test for independence based on symbolic dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 31(12), pages 3889-3903, December.
    10. repec:zbw:bofrdp:1993_015 is not listed on IDEAS
    11. Takala, Kari & Virén, Matti, 1993. "Testing nonlinearities with Finnish historical time series," Research Discussion Papers 15/1993, Bank of Finland.
    12. 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.
    13. A. Corcos & J-P Eckmann & A. Malaspinas & Y. Malevergne & D. Sornette, 2002. "Imitation and contrarian behaviour: hyperbolic bubbles, crashes and chaos," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 264-281.
    14. Scott C. Linn & Nicholas S. P. Tay, 2007. "Complexity and the Character of Stock Returns: Empirical Evidence and a Model of Asset Prices Based on Complex Investor Learning," Management Science, INFORMS, vol. 53(7), pages 1165-1180, July.
    15. Zacharias Psaradakis & Marián Vávra, 2019. "Portmanteau tests for linearity of stationary time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 248-262, February.
    16. 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.
    17. Panas, E., 2001. "Long memory and chaotic models of prices on the London Metal Exchange," Resources Policy, Elsevier, vol. 27(4), pages 235-246, December.
    18. 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.
    19. Ntebogang Dinah Moroke, 2015. "An Optimal Generalized Autoregressive Conditional Heteroscedasticity Model for Forecasting the South African Inflation Volatility," Journal of Economics and Behavioral Studies, AMH International, vol. 7(4), pages 134-149.
    20. Kevin J. Dooley & Andrew H. Van de Ven, 1999. "Explaining Complex Organizational Dynamics," Organization Science, INFORMS, vol. 10(3), pages 358-372, June.
    21. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    22. repec:dau:papers:123456789/3188 is not listed on IDEAS
    23. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    24. Serkan Erkam & Tarkan Cavusoglu, 2008. "Modelling Inflation Uncertainty In Transition Economies:The Case Of Russia And The Former Soviet Republics," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 53(178-179), pages 44-71, July - De.

    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:ejores:v:93:y:1996:i:1:p:155-172. 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/eor .

    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.