The study analyzes the family of regime switching GARCH neural network models, which allow the generalization of MS type RS-GARCH models to MS-GARCH-NN models by incorparating with neural network architectures with different dynamics and forecasting capabilities both in addition to the family of...

The Turkish version of this paper can be found at: "http://ssrn.com/abstract=2222071" http://ssrn.com/abstract=2222071The study aims to investigate linear GARCH, fractionally integrated FI-GARCH and Asymmetric Power APGARCH models and their nonlinear counterparts based on Support Vector...

The English version of this paper can be found at: "http://ssrn.com/abstract=2227747" http://ssrn.com/abstract=2227747Çalışma, temel GARCH modelinin Destek Vektör Makinesi ve Yapay Sinir Ağları ile iyileştirilmiş modellerin incelenerek GARCH modelinin tahmin performansının...

The study proposes and a family of regime switching GARCH neural network models to model volatility. The proposed MS-ARMA-GARCH-NN models allow MS type regime switching in both the conditional mean and conditional variance for time series and further augmented with artificial neural networks to...