Widiarti, Widiarti and Usman, Mustofa and Anwar, Rohimatul and Russel, Edwin and Elfaki, Faiz A. M. (2017) APPLICATION OF GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GARCH) MODEL TO DETERMINE THE VALUE AT RISK ON THE ANALYSIS OF RISK INVESTMENT. Science International Lahore, 29 (5). pp. 11471153. ISSN 10135316

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Abstract
The aims of this study were to find the best Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, to predict volatility, and to determine the Value at Risk on the Data Composite Stock Price Index (IHSG) over the period from January 2011 to February 2016. In time series data, sometimes we faced a problem that the variance is not a constant or heteroscedasticity. One of a model that can be used to deal with this condition is GARCH model. The GARCH model can be used to forecast volatility. Based on the results of calculation of Value at Risk, GARCH model can be used to estimate the risk of investment. Based on the analysis results, it was found that the best model is the ARMA (2,2)GARCH (1,1) and the value of the Value at Risk on the level of confidence 95% for one period ahead. By square root of the forecast of the variance, we found that the forecast of the volatility is as big as 0.011943077. This means that if an investor allocates fund Rp.100,000,000.00 to invest, there is a 5% chance of occurrence of losses in excess of Rp1.966.458,00 during the next 24 hours.
Item Type:  Article 

Subjects:  Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science 
Divisions:  Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika 
Depositing User:  WIDIARTI 
Date Deposited:  23 Oct 2017 06:40 
Last Modified:  23 Oct 2017 06:40 
URI:  http://repository.lppm.unila.ac.id/id/eprint/4037 
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