Haar and Daubechies wavelet methods in modeling banking sector

Recently, Wavelet Transform (WT) has gained very high attention in many fields andapplications such as physics, engineering, signal processing, applied mathematics andstatistics. In this paper, we present the advantages of WT in analyzing and improvingthe forecasting accuracy financial time series data. Amman stock market (Jordan) wasselected as a tool to show the ability of WT in forecasting financial time series,experimentally. This article suggests a novel technique for forecasting the financialtime series data, based on WT and ARIMA model. Daily return data from 1993 until2009 is used for this study.