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.
Notas
Parte de Berger-Vachon, C.; Gil Lafuente, A. M.; Kacprzyk, J.; Kondratenko, Y.; Merigó, J. M.; Morabito, F. C. (eds.) (2018). Complex Systems: Solutions and Challenges in Economics, Management and Engineering. Cham: Springer.
Información general
Fecha de publicación:2017
Idioma del documento:Inglés
Institución de origen:Instituto de Investigación en Informática