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Selecting Wavelet Transforms Model in Forecasting Financial Time Series Data Based on ARIMA Model

Sadam , Al Wadi and Ismail , Mohd Tahir and Karim Abdul, Samsul Ariffin (2011) Selecting Wavelet Transforms Model in Forecasting Financial Time Series Data Based on ARIMA Model. Applied Mathematical Sciences, , Vol. 5 (7). 315 -326. ISSN ISSN 1312-885X

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Abstract

Recently, wavelet transforms have gained very high attention in many fields and applications such as physics, engineering, signal processing, applied mathematics and statistics. In this paper, we present the advantage of wavelet transforms in forecasting financial time series data. Amman stock market (Jordan) was selected as a tool to show the ability of wavelet transform in forecasting financial time series, experimentally. This article suggests a novel technique for forecasting the financial time series data, based on Wavelet transforms and ARIMA model. Daily return data from 1993 until 2009 is used for this study.

Item Type:Article
Subjects:Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Departments > Fundamental & Applied Sciences
ID Code:3873
Deposited By: Samsul Ariffin Abdul Karim
Deposited On:07 Jan 2011 08:52
Last Modified:19 Jan 2017 08:23

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