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Purpose

– 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.

Design/methodology/approach

– 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.

Findings

– Due to the consideration of occurrences of relationships in forecasting, the out of sample forecasting is improved.

Practical implications

– 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.

Originality/value

– The empirical results show that the proposed model can improve the forecasting performance.

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