Predicting Malaysia business cycle using wavelet analysis

Samsul Arffin Abdul Karim, and Bakri Abdul Karim, and Andersson, Fredrik N. G. and Mohammad Khatim Hasan, and Jumat Sulaiman, and Radzuan Razal, (2011) Predicting Malaysia business cycle using wavelet analysis. In: 2011 IEEE Symposium on Business, Engineering and Industrial Applications, ISBEIA 2011, 25-28 September 2011, Langkawi, Kedah, Malaysia.

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Official URL: http://dx.doi.org/10.1109/ISBEIA.2011.6088841

Abstract

Wavelet transforms are capable to decompose time series at various level which corresponds to the resolution of the decomposition. We can find the trend, cycle, noise, structural break etc. This is where wavelets are so efficient in studying characteristics of the any time series. In this present article, we study the use of wavelet (symlet 16) to detect the business cycle in Malaysia. Firstly we decompose the time series then we study the long-run trend and we filtered the high frequency components and finally we find the business cycle in Malaysia. The results indicated the existence of business cycles for GDP data in Malaysia which is strongly counter-cyclical.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Business cycles, Counter-cyclical, High frequency components, Malaysia, Structural break, Industrial applications, Time series, Wavelet analysis, Wavelet decomposition
Subjects:?? QA299.6-433 ??
Divisions:SCHOOL > School of Science and Technology
ID Code:4051
Deposited By:IR Admin
Deposited On:30 Apr 2012 16:37
Last Modified:30 Dec 2014 09:39

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