Predicting Turning Points in Financial Markets with Fuzzy-Evolutionary and Neuro-Evolutionary Modeling

  • Authors:
  • Antonia Azzini;Célia Costa Pereira;Andrea G. Tettamanzi

  • Affiliations:
  • Dipartimento di Tecnologie dell'Informazione, Università degli Studi di Milano, Crema, Italy I-26013;Dipartimento di Tecnologie dell'Informazione, Università degli Studi di Milano, Crema, Italy I-26013;Dipartimento di Tecnologie dell'Informazione, Università degli Studi di Milano, Crema, Italy I-26013

  • Venue:
  • EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
  • Year:
  • 2009

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Abstract

Two independent evolutionary modeling methods, based on fuzzy logic and neural networks respectively, are applied to predicting trend reversals in financial time series, and their performances are compared. Both methods are found to give essentially the same results, indicating that trend reversals are partially predictable.