eprintid: 1645
rev_number: 8
eprint_status: archive
userid: 6
dir: disk0/00/00/16/45
datestamp: 2013-07-10 13:03:12
lastmod: 2013-07-10 13:03:12
status_changed: 2013-07-10 13:03:12
type: article
metadata_visibility: show
creators_name: Giovanis, Eleftherios
creators_id: eleftherios.giovanis@imtlucca.it
title: Application of Stationary Wavelet Support Vector Machines for the Prediction of Economic Recessions
ispublished: pub
subjects: DA
subjects: HB
divisions: EIC
full_text_status: public
keywords: Discrete choice models, Stationary Wavelets Transform, Economic crisis, Markov Switching Regime, Support Vector Machines
abstract: This paper examines the efficiency of various approaches on the classification and prediction of economic expansion and recession periods in United Kingdom. Four approaches are applied. The first is discrete choice models using Logit and Probit regressions, while the second approach is a Markov Switching Regime (MSR) Model with Time-Varying Transition Probabilities. The third approach refers on Support Vector Machines (SVM), while the fourth approach proposed in this study is a Stationary Wavelet SVM modelling. The findings show that SW-SVM and MSR present the best forecasting performance, in the out-of sample period. In addition, the forecasts for period 2012-2015 are provided using all approaches.
date: 2013
date_type: published
publication: International Journal of Mathematical Models and Methods in Applied Sciences
volume: 7
number: 3
publisher: North Alantic University  Union
pagerange: 226-237
refereed: TRUE
issn: 1998-0140
official_url: http://www.naun.org/wseas/cms.action?id=5358
citation:   Giovanis, Eleftherios  Application of Stationary Wavelet Support Vector Machines for the Prediction of Economic Recessions.  International Journal of Mathematical Models and Methods in Applied Sciences, 7 (3).  pp. 226-237.  ISSN 1998-0140      (2013)  
document_url: http://eprints.imtlucca.it/1645/1/Naun_Giovanis_2013.pdf