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Distinguishing Between Chaotic And Stochastic Systems In Financial Time Series

Author

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  • MASSIMILIANO MENNA

    (Department of Economics, Financial and Insurance Decisions, University of Rome "La Sapienza", via del Castro Laurenziano, 9 Rome, 00161, Italy)

  • GIULIA ROTUNDO

    (Department of Economics, Financial and Insurance Decisions, University of Rome "La Sapienza", via del Castro Laurenziano, 9 Rome, 00161, Italy)

  • BRUNELLO TIROZZI

    (Department of Physics, University of Rome "La Sapienza", piazzale A.Moro, 5, Rome, 00185, Italy)

Abstract

In last years several mathematical methods were successfully used for financial time series modeling. The main problem is to check whether irregularities of data are generated by a stochastic process or they are due to some deterministic chaos and to the presence of low-dimensional strange attractor. We focus on a test based on the correlation dimension. In particular we examine the time series of the daily closure prices of the Italian car industry "FIAT" shares.

Suggested Citation

  • Massimiliano Menna & Giulia Rotundo & Brunello Tirozzi, 2002. "Distinguishing Between Chaotic And Stochastic Systems In Financial Time Series," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 31-39.
    • Handle: RePEc:wsi:ijmpcx:v:13:y:2002:i:01:n:s0129183102002936
    DOI: 10.1142/S0129183102002936
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    Cited by:

    1. Roy Cerqueti & Giulia Rotundo, 2015. "A review of aggregation techniques for agent-based models: understanding the presence of long-term memory," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1693-1717, July.

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