Abstract
The study is designed to demonstrate how the forecasting models with corrected error term can be effectively used to high performance forecasts for stock price applications. Another purpose of this study is to compare the forecasts generated by the error correction model (ECM), the autoregressive conditional heteroscedastic (ARCH) model, the regression with ARMA error model (Reg-ARMA) and the autoregressive error model (Autoreg). The accuracy of these forecasting models is measured by using the forecasting errors in a post-sample period. The results show that the forecasting performance of the ECM is the best, and the next best in Autoreg model while the worst is Reg-ARMA model.
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