Foreign exchange rate (forex) forecasting has been the subject of several rigorous investigations due to its importance in evaluating the benefits and risks of the international business environments. Many methods have been researched with the ultimate goal being to increase the reliability and efficiency of the forecasting method. However as the data are inherently dynamic and complex, the development of accurate forecasting method remains a challenging task if not a formidable one. This paper proposes a new weight of the fuzzy time series model for a daily forecast of the exchange rate market. Through this method, the weights are assigned to the fuzzy relationships based on a probability approach. This can be implemented to carry out the frequently recurring fuzzy logical relationship (FLR) in the fuzzy logical group (FLG). The US dollar to the Malaysian Ringgit (MYR) exchange rates are used as an example and the efficiency of the proposed method is compared with the methods proposed by Yu and Cheng et al. The result shows that the proposed method has enhanced the accuracy and efficiency of the daily exchange rate forecasting opportunities.
Problem statement: It is common in time series data with extreme change in its mean caused by an intervention which comes from external and/or internal factors. This extreme change in mean is known as regime change or structural change. Problems of external factor intervention such as the effect of the Arab oil embargo to consumption level of electricity in United States. The issue of interest here is on the impact of terrorist Bali's bomb to tourism industry in Indonesia. Approach: A theoretical and empirical studies on the intervention model, particularly pulse function of intervention is carried out focusing on the differential statistics that can be used to determine the order of intervention model. A case study of the first Bali bomb that occurred on October 12th, 2002 is an intervention of external factor that has affected the occupancy level of five star hotels in Bali. Results: The results of this theoretical study were applied to construct a model procedure of intervention model. The empirical study showed that intervention model is used to describe and explain the quantity and the length of the first Bali bomb effect towards the occupancy level of five star hotels in Bali. It shows a decreasing trend in tourist arrival in Bali, Indonesia. Conclusion: This study was focused on the derivation of some effect shapes, i.e., temporary, gradually or permanent on the arrival of tourist into Bali. A new model building procedure with three main iterative steps for determining an intervention model was used for data with extreme change in mean. The results from this theoretical study will give an opportunity for further research related to time series model that contains regime change, caused by intervention of pulse function and/or step function.
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