PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
Investing in the stock market requires a lot of information that affects stock prices. Stock values having higher volatility reflect high level of risk as well. Technical analysis is a tool used to predict stock price movements and an influencing indicator based on historical data. If the historical...
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Main Authors: | , |
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Format: | Theses and Dissertations NonPeerReviewed |
Published: |
[Yogyakarta] : Universitas Gadjah Mada
2012
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Subjects: | |
Online Access: | https://repository.ugm.ac.id/98836/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=54928 |
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Institution: | Universitas Gadjah Mada |
Summary: | Investing in the stock market requires a lot of information that affects
stock prices. Stock values having higher volatility reflect high level of risk as
well. Technical analysis is a tool used to predict stock price movements and an
influencing indicator based on historical data. If the historical data and stocks
predictive value are already known then it can be taken into consideration while
investing. This study focuses on forecasting the daily Composite Stock Price
Index starting from January 3, 1991 until June 30, 2011 by ARIMA and GARCH
methods which will further be tested their accuracy of predictions.
The results of this study indicate that daily stock index data over the
period 1991 to 2011 are classified as not stationary. Having made difference 1 and
log transformation then the data became stationary. The correlogram test results
obtained a significant partial autocorrelation of nine lags, namely lag1, lag 10,
lag11, lag 13, lag 16, lag 17, lag 25, lag 33, and lag 36. The best suited model of
ARIMA(1,1,0) was obtained. On the residual value of ARIMA(1,1,0) there�s an
ARCH effect forecasting is then performed by GARCH method and obtained the
best prediction model GARCH(2,2). ARIMA(1,1,0) has better accuracy as
compared to GARCH(2,2) because the forecast error value of one period ahead
and the MAE and MAPE values were smaller, which means that the forecast of
ARIMA (1,1,0) almost reached the factual value. |
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