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Phase Distribution and Phase Correlation of Financial Time Series

Author

Listed:
  • Ming-Chya Wu

    (Academic Sinica, Taiwan)

  • Ming-Chang Huang

    (Chung Yuan University, Taiwan)

  • Hai-Chin Yu

    (Chung Yuan University, Taiwan)

  • Thomas Chiang

    (Drexel University, USA)

Abstract

Scaling, phase distribution and phase correlation of financial time series are investigated based on the Dow Jones Industry Average (DJIA) and NASDAQ 10-minute intraday data for a period from Aug. 1 1997 to Dec. 31 2003. The returns of the two indices are shown to have nice scaling behaviors and belong to stable distributions according to the criterion of Levy's alpha stable distribution condition. A novel approach catching characteristic features of financial time series based on the concept of instantaneous phase is further proposed to study phase distribution and correlation. The analysis of phase distribution concludes return time series fall into a class which is different from other non-stationary time series. The correlation between returns of the two indices probed by the distribution of phase difference indicates there was a remarkable change of trading activities after the event of 911 attack, and this change persisted in later trading activities.

Suggested Citation

  • Ming-Chya Wu & Ming-Chang Huang & Hai-Chin Yu & Thomas Chiang, 2005. "Phase Distribution and Phase Correlation of Financial Time Series," Finance 0512013, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0512013
    Note: Type of Document - pdf; pages: 20
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/fin/papers/0512/0512013.pdf
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    More about this item

    Keywords

    Phase Distribution; High Frequency Data; Scaling Analysis; Levy Distribution; Stock Market; Frequency Variant;

    JEL classification:

    • G - Financial Economics

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