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Price Direction Prediction on High Frequency Data Using Deep Belief Networks

  • Jaime Humberto Niño-PeñaEmail author
  • Germán Jairo Hernández-Pérez
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 657)

Abstract

This paper presents the use of Deep Belief Networks (DBN) for direction forecasting on financial time series, particularly those associated to the High Frequency Domain. The paper introduces some of the key concepts of the DBN, presents the methodology, results and its discussion. DBNs achieves better performance for particular configurations and training times were acceptable, however if they want to be pursued in real applications, windows sizes should be evaluated.

Keywords

Deep Belief Networks Stocks forecasting High frequency data 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Jaime Humberto Niño-Peña
    • 1
    Email author
  • Germán Jairo Hernández-Pérez
    • 1
  1. 1.Universidad Nacional de ColombiaBogotáColombia

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