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Stock returns forecast : an examination by means of artificial neural networks

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Iglesias Caride, Martín

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Summary: 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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Item type	Home library	Collection	Call number	URL	Status	Date due	Barcode
Capítulo de libro	Biblioteca de la Facultad de Informática	Biblioteca digital	A0935 (Browse shelf(Opens below))	Link to resource	Recurso en Línea

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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.

Complex Systems: Solutions and Challenges in Economics, Management and Engineering, 125, pp. 399-410.