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Distinguishing between Chaotic and Stochastic Systems in Financial Time Series.

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Title: Distinguishing between Chaotic and Stochastic Systems in Financial Time Series.
Authors: Menna, Massimiliano, Rotundo, Giulia, Tirozzi, Brunello
Source: International Journal of Modern Physics C: Computational Physics & Physical Computation. Jan2002, Vol. 13 Issue 1, p31. 9p.
Subjects: Chaos theory, Stochastic systems, Time series analysis
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. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 7228929
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Distinguishing between Chaotic and Stochastic Systems in Financial Time Series.
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  Data: <searchLink fieldCode="AR" term="%22Menna%2C+Massimiliano%22">Menna, Massimiliano</searchLink><br /><searchLink fieldCode="AR" term="%22Rotundo%2C+Giulia%22">Rotundo, Giulia</searchLink><br /><searchLink fieldCode="AR" term="%22Tirozzi%2C+Brunello%22">Tirozzi, Brunello</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Chaos+theory%22">Chaos theory</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+systems%22">Stochastic systems</searchLink><br /><searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink>
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  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1142/S0129183102002936
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Stochastic systems
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      – SubjectFull: Time series analysis
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      – TitleFull: Distinguishing between Chaotic and Stochastic Systems in Financial Time Series.
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            NameFull: Menna, Massimiliano
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              Text: Jan2002
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