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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Stock Returns Forecast: An Examination By Means of Artificial Neural Networks
verfasst von : Martín Iglesias Caride, Aurelio F. Bariviera, Laura Lanzarini
Erschienen in: Complex Systems: Solutions and Challenges in Economics, Management and Engineering
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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.