Neural network-based fuzzy auto-regressive models of different orders to forecast Taiwan stock index

This article proposes the use of a fuzzy time series model based on neural networks that are intended to calculate the complicated fuzzy relationships among observations. The Taiwan stock exchange capitalisation weighted stock index is used as the forecasting target. Various parameters such as the order of the time series the threshold for defuzzification, and the in-sample estimation results are used to determine the proper models for out-of-sample forecasting.

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Year of publication:	2009
Authors:	Yu, Tiffany Hui-Kuang ; Huarng, Kun-Huang ; Rianto, Rapon
Published in:	International Journal of Economics and Business Research. - Inderscience Enterprises Ltd, ISSN 1756-9850. - Vol. 1.2009, 3, p. 347-358
Publisher:	Inderscience Enterprises Ltd
Subject:	forecasting \| fuzzy sets \| neural networks \| orders \| thresholds \| autoregressive modelling \| Taiwan stock exchange \| fuzzy logic

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

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