Üssel düzleştirme ve ATA metodu ile finansal veri analizi

Time series occurs by collecting the data in a particular category in a given time period. Accurate analysis of financial data, which is a sort of time series, has a great importance for financial institutions to make predictions for the future. Exponential smoothing method is one of the most used method in time series analysis. Exponential smoothing methods have been used widely for many years due to their simplicity and success in prediction results. The success of the method has proved many times in the famous M-competitions. However, the selection of initial value and smoothing constant according to subjective choices for exponential smoothing method adversely affect the accuracy of this method. The ATA method, which is a new method developed as an alternative to the exponential smoothing method, eliminates these disadvantages of the exponential smoothing method. In this study, the M4 results of exponential smoothing method and ATA method will be compared, especially their performance in financial data will be evaluated.