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Minimum entropy density method for the time series analysis

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Author Info

  • Lee, Jeong Won
  • Park, Joongwoo Brian
  • Jo, Hang-Hyun
  • Yang, Jae-Suk
  • Moon, Hie-Tae
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    Abstract

    The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0378437108008339
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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 388 (2009)
    Issue (Month): 2 ()
    Pages: 137-144

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    Handle: RePEc:eee:phsmap:v:388:y:2009:i:2:p:137-144

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Econophysics; Entropy density; Time series analysis;

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    Cited by:
    1. Lavička, H. & Lin, L. & Novotný, J., 2010. "Employment, Production and Consumption model: Patterns of phase transitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1708-1720.
    2. Chapeau-Blondeau, François & Rousseau, David, 2009. "The minimum description length principle for probability density estimation by regular histograms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3969-3984.

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