financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …

forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent …, recurrent artificial neural network based ARMA model and feed-forward SVR based ARMA model) by using two forecasting accuracy … evaluation metrics (NSME and sign) and robust Diebold–Mariano test. The results reveal that for one-step-ahead forecasting, the …

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms …

Wavelet SVM modelling. The findings show that SWSVM and MSR present the best forecasting performance, in the outof sample …

Wavelet SVM modelling. The findings show that SW-SVM and MSR present the best forecasting performance, in the out-of sample …

Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns … to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the … focus on fit in-sample, but SVR considers both fit and forecast out-of-sample which endows SVR with an excellent forecasting …

blood glucose levels and diabetes, few have focused on the risk forecasting of postprandial blood glucose levels in patients …