Stock returns forecast

Título:

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

Autor:

Iglesias Caride, Martín

Colaboradores:

; Bariviera, Aurelio F.; Lanzarini, Laura Cristina

Temas:

REDES NEURONALES

En:

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

Resumen:

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.

URL/DOI:

https://doi.org/10.1007/978-3-319-69989-9_23

Palabras clave:

índice Bovespa

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (401,0 kB)

Idioma:

Inglés

Publicación:

, 2018

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