Event Detection in Financial Time Series by Immune-Based Approach

  • Tomasz Pelech
  • Jan T. Duda
Part of the Advances in Soft Computing book series (AINSC, volume 35)


The paper presents a concept of immune paradigm application to monitoring of company environment. Short-time prediction of stock rates is used as a basic tool to vigil relevant events, viewed as switching between “healthy” and “ill” behavior of the monitored quotations. Two predictive formulas are applied alternatively to recognize the behavior kind. “Illness” detection rules are proposed, based on the prediction efficiency evaluated in moving windows. Parameters of the predictors are modified according to the immune paradigm.


Event Detection Financial Time Series Daily Increment Immune Memory Detection Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2006

Authors and Affiliations

  • Tomasz Pelech
    • 1
  • Jan T. Duda
    • 1
  1. 1.AGH-University of Science and TechnologyKrakówPoland

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