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

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  • Takala, Kari
  • Viren, Matti

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  • 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
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    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.
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    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.
    11. Foued Saâdaoui & Hana Rabbouch, 2024. "Structured multifractal scaling of the principal cryptocurrencies: Examination using a self‐explainable machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2917-2934, November.

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