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Dynamic Local Trend Associations in Analysis of Comovements of Financial Time Series

  • Francisco Javier García-López
  • Ildar Batyrshin
  • Alexander Gelbukh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 648)

Abstract

We show that the correlation coefficient, often used for analysis of co-movements of financial time series, can be misleading because it does not take into account the time ordering of time series values. We propose the new method of analysis of time series comovements based on dynamic local trend association measure. This measure can capture the dynamic change of the sign of association between time series. The advantage of the new method is demonstrated on examples of financial time series. The associations between time series dynamics and related events are also considered.

Keywords

Time series Comovement Association measure Stock market Event Correlation 

Notes

Acknowledgment

The work was supported by the projects IPN SIP 20171344 and SEP - CONACYT 283778, Mexico.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Francisco Javier García-López
    • 1
  • Ildar Batyrshin
    • 1
  • Alexander Gelbukh
    • 1
  1. 1.Centro de Investigación en ComputaciónInstituto Politécnico NacionalMexico CityMexico

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