Forecasting Stock Price Index Using Artificial Neural Networks in the Indonesian Stock Exchange
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Institusion
Universitas Atma Jaya Yogyakarta
Author
TIPHIMMALA, SOUKKHY
Subject
Manajemen Keuangan
Datestamp
2015-01-23 09:23:23
Abstract :
Stock price index is the initial significant factor influencing on investors' financial decision making. That's why predicting the exact movements of stock price index is considerably regarded. This study aims at evaluating the effectiveness of using technical indicators, such as A/D Oscillator, Moving Average, RSI, CCI, MACD, etc. in predicting movements of Indonesian Stock Exchange Price Index (IDX). An artificial neural network is employed for stock price index forecasting. The existing data are achieved from Yahoo.Finance. To capture the relationship between the technical indicators and the levels of the index in the market for the period under investigation, a back propagation neural network is used. The statistical and financial performance of this technique is evaluated and empirical results revealed that artificial neural networks are fairly good tools for financial market predicting.
Stock price index is the initial significant factor influencing on investors' financial decision making. That's why predicting the exact movements of stock price index is considerably regarded. This study aims at evaluating the effectiveness of using technical indicators, such as A/D Oscillator, Moving Average, RSI, CCI, MACD, etc. in predicting movements of Indonesian Stock Exchange Price Index (IDX). An artificial neural network is employed for stock price index forecasting. The existing data are achieved from Yahoo.Finance. To capture the relationship between the technical indicators and the levels of the index in the market for the period under investigation, a back propagation neural network is used. The statistical and financial performance of this technique is evaluated and empirical results revealed that artificial neural networks are fairly good tools for financial market predicting.
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