Abstract
The main objective in developing a statistical model is to improve accuracy in forecasting. In this paper, we propose a hybrid non-stationary model for forecasting financial time series. The proposed model is non-stationary in trend with a regressor and a GARCH (1, 1) error. We derive the expression for h-step ahead forecast along with forecast variance. A simulation study is carried out to examine the performance of the proposed model with other existing model. Estimation based on the proposed model performs better than existing models in terms of mean squared error criterion. Real data sets of stock prices were used to examine the forecasting accuracy of the proposed model and it is found that the proposed approach has the best forecasting accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of the Indian Society for Probability and Statistics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
