A COMPARATIVE STUDY OF STOCK PRICE FORECASTING USING NONLINEAR MODELS

Diteboho Xaba, Ntebogang Dinah Moroke, Johnson Johnson, Charlemagne Pooe
2017 Risk Governance and Control: Financial Markets & Institutions  
How to cite this paper: This study compared the in-sample forecasting accuracy of three forecasting nonlinear models namely: the Smooth Transition Regression (STR) model, the Threshold Autoregressive (TAR) model and the Markov-switching Autoregressive (MS-AR) model. Nonlinearity tests were used to confirm the validity of the assumptions of the study. The study used model selection criteria, SBC to select the optimal lag order and for the selection of appropriate models. The Mean Square Error
more » ... E), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) served as the error measures in evaluating the forecasting ability of the models. The MS-AR models proved to perform well with lower error measures as compared to LSTR and TAR models in most cases.
doi:10.22495/rgcv7i2art1 fatcat:xdosw2b67nbodluai4hkumjaki