%0 Conference Paper
%A Abdul Karim, S.A.
%A Abdul Karim, B.
%A Andersson, F.N.G.
%A Hasan, M.K.
%A Sulaiman, J.
%A Razali, R.
%D 2011
%F scholars:1420
%K Business cycles; Counter-cyclical; High frequency components; Malaysia; Structural break, Industrial applications; Time series; Wavelet analysis; Wavelet decomposition, Time series analysis
%P 379-383
%R 10.1109/ISBEIA.2011.6088841
%T Predicting Malaysia business cycle using wavelet analysis
%U https://khub.utp.edu.my/scholars/1420/
%X 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. © 2011 IEEE.
%Z cited By 0; Conference of 2011 IEEE Symposium on Business, Engineering and Industrial Applications, ISBEIA 2011 ; Conference Date: 25 September 2011 Through 28 September 2011; Conference Code:87820