PERBANDINGAN TAKSIRAN VALUE AT RISK DENGAN PROGRAM R DAN MATLAB ANALISIS INVESTASI SAHAM MENGGUNAKAN METODE GARCH - Sari, Fenny Tunjung; Mariani, Scolastika (Unnes Journal of Mathematics, 2016)
Value at Risk (VaR) became a popular statistical method used to measure the risk investing. When estimating it require forecasting volatility. One of methods for modeling the heteroscedastic volatility called Generalized Autoregressive Conditional Heteroscedasticity (GARCH). The goal of this research are compare the result estimated it, by R program and MATLAB program, and then comparing accuracy of them. This research used data index March 4, 2013 to October 1, 2014. The result show that the forecasting it with probability 95% and 15-days horizon on R program is -0,2224606 then MATLAB program is -0,215263. While the result of calculation Mean Square Error (MSE) respectively R and MATLAB programs are 0,0003623 and 0,0003609. MATLAB program is the best level of accuracy in forecasting variansi. They have been modeling the volatility of LQ45 stock index to estimate it, using GARCH(1,1) model