Smoothing Techniques for Time Series Forecasting

There are many forecasting techniques available, and selecting the appropriate technique is very important issue to achieve a good forecasting performance. This thesis intends to present the smoothing techniques for time series forecasting. The forecasting process using simple moving average and weighted moving average methods is investigated. The exponential smoothing forecasting method is analyzed. The simple exponential smoothing method is described. Some error measures - Mean Absolute Deviation, Mean Absolute Percentage Error, and Mean Square Error are calculated for above forecasting techniques to define the forecast accuracy of these methods. The double exponential smoothing method is discussed.