FORECASTING ANALYSIS FOR CLOSING STOCK PRICE OF SECTORAL INDEX USING WAVELET NEURAL NETWORK

• Main Author: ANISA (NIM : 10214065), RIZKY
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/30609
• Institution: Institut Teknologi Bandung

There are five dominant sectoral stocks after global financial crisis, mining sector, financial sector, infrastructure sector, basic industries and chemical sector, and consumer goods sector. To know which sector experienced the most significant in the future, it is necessary a forecasting. The purpose of this study is to determine the results of the closing stock price predictions and determine the investment strategy based on predicted results. The method used in this research is a combination of wavelet and artificial neural network so called wavelet neural network (WNN). The data used will be divided into two namely the data train and test data. Furthermore, from the data will be generated training performance, regression results, and WNN output results with the target. If the test results, WNN output with the target is the same or close then it can be continued to make predictions in the future. As well as from these predictions, can be analyzed investment strategies that can be used.