Özet:

The modeling of the series in the time series analysis, as well as the examination of the relations between them, is the main purpose of the future forecasting. One of the most widely used methods in the literature is exponential smoothing methods. Due to many reasons such as financial crises, natural disasters in the data production processes of the series, permanent structural changes can occur. These changes affect model parameters as well as analysis results. The main purpose of this study is to compare the predictive performances of the newly developed Modified Exponential Smoothing (MSES)(2016) methods with the simple exponential smoothing (SES) when there are structural breaks in the series with different break magnitude and different break location. Mean Absolute Error values of methods are affected by the sample size, break magnitude and location. The breaks in the data set would affect the model estimation negatively. Possible breaks’ magnitude and locations should be taken into consideration in the use of the MSES method.

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