Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting



Jaber AM, Ismail MT, Altaher AM.


ScientificWorldJournal. 2014;2014:708918. doi: 10.1155/2014/708918. Epub 2014 Jul 22.


This paper mainly forecasts the daily closing price of stock markets. 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, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

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Link/DOI: 10.1155/2014/708918