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: , Budi Nugroho, , Prof. Dr. Sukmawati Sukamulja, M.M.
格式: Theses and Dissertations NonPeerReviewed
出版: [Yogyakarta] : Universitas Gadjah Mada 2012
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spelling id-ugm-repo.988362016-03-04T08:45:56Z https://repository.ugm.ac.id/98836/ PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011 , Budi Nugroho , Prof. Dr. Sukmawati Sukamulja, M.M. ETD 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. [Yogyakarta] : Universitas Gadjah Mada 2012 Thesis NonPeerReviewed , Budi Nugroho and , Prof. Dr. Sukmawati Sukamulja, M.M. (2012) PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=54928
institution Universitas Gadjah Mada
building UGM Library
country Indonesia
collection Repository Civitas UGM
topic ETD
spellingShingle ETD
, Budi Nugroho
, Prof. Dr. Sukmawati Sukamulja, M.M.
PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
description 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.
format Theses and Dissertations
NonPeerReviewed
author , Budi Nugroho
, Prof. Dr. Sukmawati Sukamulja, M.M.
author_facet , Budi Nugroho
, Prof. Dr. Sukmawati Sukamulja, M.M.
author_sort , Budi Nugroho
title PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
title_short PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
title_full PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
title_fullStr PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
title_full_unstemmed PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011
title_sort perbandingan akurasi peramalan metodearima dan garch untuk memprediksi ihsgperiode 1991 - 2011
publisher [Yogyakarta] : Universitas Gadjah Mada
publishDate 2012
url 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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