A fuzzy engine model for efficient stock market prediction

Shereen M. Ahmad, Neamat El Gayar, Hazem Y. Abd Elazim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The prediction of stock market is considered a non-trivial problem in the financial arena. In the last few years many sophisticated models were developed to predict the stocks in order to achieve a maximum profit. Fuzzy models are one of the powerful methods that are used in this field. This paper proposes a fuzzy engine model that acts as an expert indicator that can generate buy and sell signals. The fuzzy engine model combines the most popular technical indicators with their firing strengths to provide a new fuzzy indicator that achieves good results compared to the other traditional indicators. Experiments were conducted to evaluate the performance of the model and the results prove that the fuzzy engine model gives more reliable buy and sell positions in different time horizons compared to other technical indicators.

Original languageEnglish
Title of host publicationCIMMACS'06: Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics
EditorsAntonella Cecchi, Nikos Mastorakis
PublisherWorld Scientific and Engineering Academy and Society
Pages217-222
Number of pages6
ISBN (Print)9608457564
Publication statusPublished - 20 Nov 2006
Event5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics 2006 - Venice, Italy
Duration: 20 Nov 200622 Nov 2006

Conference

Conference5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics 2006
Abbreviated titleCIMMACS '06
Country/TerritoryItaly
CityVenice
Period20/11/0622/11/06

Keywords

  • Fuzzy Inference
  • Fuzzy Logic
  • Fuzzy Rules
  • Technical Analysis
  • Technical indicators

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Software

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