Explanation of binarized time series by a behavioral economic approach

  • Takashi Yamada
  • Kazuhiro Ueda
Conference paper
Part of the Springer Series on Agent Based Social Systems book series (ABSS, volume 3)


The aim of this paper is to reveal the relations between time scales and time series properties by concentrating on information requisite for speculators using a genetic learning model of investor sentiment. For this purpose, first we identify the conditions to describe investor sentiment using a variety of parameters of genetic algorithm. Then we calculate auto-correlations and conditional probabilities using the estimated models in the first step. Our results show that both the amount and quality of information for the agents determine the time series properties. This implies that the preciseness of information which speculators permit depends on their time scales.


Conditional Probability Sample Path Price Movement Foreign Exchange Market Investor Sentiment 
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 2007

Authors and Affiliations

  • Takashi Yamada
    • 1
    • 2
  • Kazuhiro Ueda
    • 1
  1. 1.Department of General Systems Studies, Graduate School of Arts and SciencesUniversity of TokyoTokyoJapan
  2. 2.Department of Computational Intelligence and System Sciences, Interdisci-plinary Graduate School of Science and EngineeringTokyo Institute of TechnologyJapan

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