Stock Returns Forecast: An Examination By Means of Artificial Neural Networks

  • Martín Iglesias Caride
  • Aurelio F. Bariviera
  • Laura Lanzarini
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 125)

Abstract

The validity of the Efficient Market Hypothesis has been under severe scrutiny since several decades. However, the evidence against it is not conclusive. Artificial Neural Networks provide a model-free means to analize the prediction power of past returns on current returns. This chapter analizes the predictability in the intraday Brazilian stock market using a backpropagation Artificial Neural Network. We selected 20 stocks from Bovespa index, according to different market capitalization, as a proxy for stock size. We find that predictability is related to capitalization. In particular, larger stocks are less predictable than smaller ones.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Martín Iglesias Caride
    • 1
  • Aurelio F. Bariviera
    • 2
  • Laura Lanzarini
    • 3
  1. 1.Master Program in Data MiningUniversidad de Buenos AiresBuenos AiresArgentina
  2. 2.Department of BusinessUniversitat Rovira i VirgiliTarragonaSpain
  3. 3.Instituto de Investigación en Informática LIDI, Facultad de InformáticaUniversidad Nacional de La PlataLa PlataArgentina

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