Please use this identifier to cite or link to this item:
Title: Are Spanish Ibex35 stock future index returns forecasted with non-linear models?
Authors: Pérez Rodríguez, Jorge Vicente 
Torra, Salvador
Andrada Félix, Julián 
UNESCO Clasification: 530202 Modelos econométricos
Keywords: Análisis de series temporales
Teoría del caos
Issue Date: 2005
Publisher: 0960-3107
Journal: Applied Financial Economics 
Abstract: This study employs different nonlinear models (smooth transition autoregressive models (STAR), artificial neural networks (ANN) and nearest neighbours (NN)) to study the predictability of one-step-ahead forecast returns for the Ibex35 stock future index at a one year forecast horizon. It is found that the STAR, ANN and NN models beat the random walk (RW) and linear autoregressive (AR) models in out-of-sample forecast statistical accuracy, and also when economic criteria were used in a simple trading strategy including the impact of transaction costs on trading strategy profits. Finally, the overall results suggest that the nonlinear models (particularly ANN and NN) considered for the Ibex35 stock future index appear to provide a reasonable description of asset price movements in improving returns forecasts for the chosen horizon.
ISSN: 0960-3107
DOI: 10.1080/09603100500108220
Source: Applied Financial Economics[ISSN 0960-3107],v. 15, p. 963-975
Appears in Collections:Artículos
Show full item record


checked on Aug 7, 2022

Page view(s)

checked on Jul 23, 2022

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.