The purpose of this paper is to propose an occurrence-based model to improve the forecasting of regime switches so as to assist decision making.
This paper proposes a novel model where occurrences of relationships are taken into account when forecasting. Taiwan Stock Exchange Capitalization Weighted Stock Index is taken as the forecasting target.
Due to the consideration of occurrences of relationships in forecasting, the out of sample forecasting is improved.
The proposed model can be applied to forecast other time series for regime switches. In addition, it can be integrated with other time series models to improve forecasting performance.
The empirical results show that the proposed model can improve the forecasting performance.
This work is partially supported by National Science Council, Taiwan, ROC, under grants NSC 99-2410-H-035-033-MY2, NSC 101-2410-H-035-004-, and NSC 102-2410-H-035 -038-MY2.
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