The development of wavelet theory in recent years has motivated the emergence of applications such as in signal processing, image and function representation, finance, economics, numerical method etc. One of the dvantages wavelet as compared with Fourier is, it has fast algorithm to evaluate the series expansion. In the present study, we will discuss the applications of fast wavelet algorithm namely Discrete Wavelet Transform (DWT) in finance such as denoising the time series by using wavelet thresholding. Some numerical results by using real data will be presented. © 2011 Asian Network for Scientific Information.