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Non-linear forecasts of stock returns

Kanas, Angelos (2003) Non-linear forecasts of stock returns. Journal of Forecasting, 22 (4). pp. 299-315. ISSN 0277-6693. (doi:10.1002/for.858) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:41151)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1002/for.858

Abstract

Following recent non-linear extensions of the present-value model, this paper examines the out-of-sample forecast performance of two parametric and two non-parametric nonlinear models of stock returns. The parametric models include the standard regime switching and the Markov regime switching, whereas the non-parametric are the nearest-neighbour and the artificial neural network models. We focused on the US stock market using annual observations spanning the period 1872-1999. Evaluation of forecasts was based on two criteria, namely forecast accuracy and forecast encompassing. In terms of accuracy, the Markov and the artificial neural network models produce at least as accurate forecasts as the other models. In terms of encompassing, the Markov model outperforms all the others. Overall, both criteria suggest that the Markov regime switching model is the most preferable non-linear empirical extension of the present-value model for out-of-sample stock return forecasting. Copyright © 2003 John Wiley & Sons, Ltd.

Item Type: Article
DOI/Identification number: 10.1002/for.858
Uncontrolled keywords: Artificial neural networks, Forecast accuracy, Forecast encompassing, Forecasting, Markov regime switching, Nearest-neighbour, Non-linearity, Standard regime switching, Control nonlinearities, Economic and social effects, Markov processes, Mathematical models, Neural networks, Economic forecastings, Stock markets, Industrial economics
Subjects: H Social Sciences > HG Finance
Divisions: Divisions > Kent Business School - Division > Kent Business School (do not use)
Depositing User: Tracey Pemble
Date Deposited: 22 May 2014 14:08 UTC
Last Modified: 16 Nov 2021 10:16 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/41151 (The current URI for this page, for reference purposes)

University of Kent Author Information

Kanas, Angelos.

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