HYBRID SYSTEM OF SIMPLE EXPONENTIAL SMOOTHING AND NEURAL NETWORK FOR KSE100 INDEX
Abstract
This study deals with application of Hybrid forecasting systems to formulate simple exponential smoothing model for KSE 100 index daily share price data. We used 7 days ahead forecasts for daily share price of KSE100 index data. This study is divided into two phases. In the first phase of the study we compared ANN model with SES and found that ANN model gives better forecasting performance then SES model. In the second phase of the study we developed a hybrid system of Artificial Neural Networks (ANN) and Simple Exponential Smoothing (SES) models represented as ANN SES for KSE100 index daily share price data. Empirical results support our proposed hybrid system (ANN SES).References
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