Application of Empirical Mode Decomposition with Local Linear Quantile Regression in Financial Time Series Forecasting

M. Jaber, Abobaker and Ismail, Mohd Tahir and M. Altaher, Alsaidi Application of Empirical Mode Decomposition with Local Linear Quantile Regression in Financial Time Series Forecasting. Scientific World Journal, 2014 (708918). pp. 1-5. ISSN 2356-6140

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Abstract

This paper mainly forecasts the daily closing price of stockmarkets.We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ).We use the proposed technique, EMDLLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposedmethod, in which EMD-LPQ, EMD, andHolt-Winter methods are compared.The proposed EMD-LPQ model is determined to be superior to the EMDandHolt- Winter methods in predicting the stock closing prices.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics
Divisions:	Pusat Pengajian Sains Matematik (School of Mathematical Sciences) > Article
Depositing User:	Mr Noorazilan Noordin
Date Deposited:	11 Jan 2018 07:57
Last Modified:	11 Jan 2018 07:57
URI:	http://eprints.usm.my/id/eprint/38348

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