Jump point detection using empirical mode decomposition

• Published in: Land use policy Vol. 58; pp. 1 - 8
• Main Authors: Lam, Benson S.Y., Yu, Carisa K.W., Choy, Siu-Kai, Leung, Jacky K.T.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15.12.2016
• Subjects: Empirical mode decomposition; Jump points; Real estate; Time series; Jump points; Empirical mode decomposition; Real estate; Time series
• ISSN: 0264-8377; 1873-5754
• DOI: 10.1016/j.landusepol.2016.07.006

•A robust signal decomposition method, EMD for removing noise from the real world time series is present.•A third-order derivative based detector is proposed to capture the jump points of the time series.•The housing price indices and stock price index are evaluated.•The proposed method can detect more jump points that correspond to the announcement of some international/regional regulation and policies.•The proposed method does not have any sensitive parameter. Real estate is an important form of investment in Hong Kong. Recent researches on the analysis of real estate market have revealed that jump points in the housing price time series play an essential role in the Hong Kong economy. Detecting such jump points thus becomes important as they represent vital findings that enable policy-makers and investors to look forward. In this paper, we propose a jump point detection methodology, which makes use of the empirical mode decomposition algorithm and a derivative-based detector, to detect jump points in the time series of some housing price indices in Hong Kong. Experimental results reveal that our proposed method has a superior performance and outperforms the current state-of-the-art wavelet approach.