eprintid: 2224
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/22/24
datestamp: 2023-11-09 15:50:25
lastmod: 2023-11-09 15:50:25
status_changed: 2023-11-09 15:42:17
type: article
metadata_visibility: show
creators_name: Al Wadi, S.
creators_name: Ismail, M.T.
creators_name: Alkhahazaleh, M.H.
creators_name: Addul Karim, S.A.
title: Selecting wavelet transforms model in forecasting financial time series data based on ARIMA model
ispublished: pub
note: cited By 54
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.
date: 2011
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952173522&partnerID=40&md5=6326b637265d0802973fdaeae72572ea
full_text_status: none
publication: Applied Mathematical Sciences
volume: 5
number: 5-8
pagerange: 315-326
refereed: TRUE
issn: 1312885X
citation:   Al Wadi, S. and Ismail, M.T. and Alkhahazaleh, M.H. and Addul Karim, S.A.  (2011) Selecting wavelet transforms model in forecasting financial time series data based on ARIMA model.  Applied Mathematical Sciences, 5 (5-8).  pp. 315-326.  ISSN 1312885X