publication . Article . 2007

FORECASTING KUALA LUMPUR COMPOSITE INDEX: EVIDENCE OF THE ARTIFICIAL NEURAL NETWORK AND ARIMA

Sukmana, Raditya; Solihin, Mahmud Iwan;
Open Access English
  • Published: 01 Aug 2007 Journal: Jurnal Ekonomi dan Bisnis Airlangga (J E B A) (issn: 2597-4564, eissn: 2338-2686, Copyright policy)
  • Publisher: Fakultas Ekonomi dan Bisnis, Universitas Airlangga
Abstract
The aim of this paper is to use, compare, and analyze two forecasting technique: namelyAuto Regressive Integrated Moving Average(ARIMA) and Artificial NeuralNetwork(ANN) using Kuala Lumpur Composite Index(KLCI) in Malaysia. ArtificialNeural Network is used because of its popularity of capturing the volatility patterns innonlinear time series while ARIMA used since it is a standard method in the forecastingtool. Daily data of Kuala Lumpur Composite Index from 4 January 1999 to 26 September2005 is used. ANN training with “early stopping” technique is investigated. We foundthat the deviation or error showed in the ANN technique is much less than that inARIMA. Hence...
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