TY  - JOUR
SP  - 226
TI  - Application of Stationary Wavelet Support Vector Machines for the Prediction of Economic Recessions
AV  - public
KW  - Discrete choice models
KW  -  Stationary Wavelets Transform
KW  -  Economic crisis
KW  -  Markov Switching Regime
KW  -  Support Vector Machines
VL  - 7
Y1  - 2013///
UR  - http://www.naun.org/wseas/cms.action?id=5358
A1  - Giovanis, Eleftherios
N2  - 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.
EP  - 237
ID  - eprints1645
SN  - 1998-0140
IS  - 3
PB  - North Alantic University  Union
JF  - International Journal of Mathematical Models and Methods in Applied Sciences
ER  -