Wavelet Based Method for Islamic Stock Prices in Malaysia and Indonesia: Pre-US Subprime Crisis

Wavelets have been widely used in sciences, finance, economy and engineering applications. One of the main streams of wavelet based method is the capability of its transform to localize both in scale (frequency) and space (time) respectively. Besides that, wavelet transform also will be able to preserves the variances of the original time series. This is crucial for statistical analyst. This paper is a preliminary study of the application of wavelets into Islamic stock price movement among the Asian country. We restrict the analysis to two countries only which is Malaysia and Indonesia particularly during pre-US subprime crisis. Symlet 8 (16 high pass and lowpass filters) have been utilized for our purpose. From the main results, there exists strong relationship between Malaysia and Indonesia before the US crisis. This can be seen clearly from wavelet decomposition and statistical analysis.