Stock returns forecast : an examination by means of artificial neural networks
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| Otros autores o Colaboradores: | , |
| Formato: | Capítulo de libro |
| Lengua: | inglés |
| Temas: | |
| Acceso en línea: | https://doi.org/10.1007/978-3-319-69989-9_23 Consultar en el Cátalogo |
| 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. |
| Notas: | Formato de archivo PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca) |
| Descripción Física: | 1 archivo (401,0 kB) |
| DOI: | 10.1007/978-3-319-69989-9_23 |