Pengukuran Risiko Harga Minyak Menggunakan Pendekatan Value At Risk Dengan Metode Variance Covariance(Studi Kasus PT. Medco Energy Internasional Tbk.) - , RA. Ratna Dewi Kusumawati, Dr. Mamduh Mahmadah Hanafi, MBA. ([Yogyakarta] : Universitas Gadjah Mada, 2012)
Crude oil industries are very complex industries with huge funding requirements and involve high technology. Because of the nature of such industries, the risks faced by the industry are also very diverse and high. MedcoEnergy as a one of crude oil industries in Indonesia also not independent of those risks. Further research had used Value At Risk (VaR) method to assess the losses from the sale of MedcoEnergi crude oil. VaR approach with variance-covariance method begins by establishing the oil price returns data of Indonesian Crude Price (ICP) from 2008-2010. Continued with stationarity test and in which the stationary test are met if the value of the ADF Test Statistic is smaller than the MacKinnon critical value for Î± = 5% and Î± = 1%. Once stationary conditions are met then the heteroscedasticity test can be done. The terms of heteroscedasticity test fulfilled if the probability of is greater than the critical value of 5% and 1%. Further test is normality test and these tests are met if the probability of Jarque Bera normality test is greater than the critical value of 5% and 1%. If the normality condition is not met the alpha (Î±) used is Cornish Fisher Expansion alpha. The last stage is to determine the VaR by multiplying of Ï, Î±, the value of assets and the holding period and equipped with a model validation test using Kupiec test and backtesting. The results were showed that the return data has not been stationary since the ADF Test Statistic (-2.249479) greater than the MacKinnon critical value for Î± = 5% (-2.9527) and Î± = 1% (-3.6422). Using differentiation process with level 1 and the result of stationary conditions are met because the value of ADF Test Statistic (-3.801863) is smaller than the MacKinnon critical value for Î± = 5% (-2.9558) and Î± = 1% (-3.6496). Next step is the heteroscedasticity test and these tests are fulfilled because the probability of (0.618949) is greater than the critical value of 5% and 1% with Ï of 0.111044. Continued with the normality test which is the Jarque Bera test probability (0.000276) is smaller than the critical value of 5% and 1%, which is concluded the normal conditions are not met. The Cornish Fisher Expansion alpha (Î± ') can be used with alpha 5% is (2.056657) and 1% is (3.390183). Value of Ï and Î± can be used to obtain the VaR and fulfilled with the validity test for the VaR model. The VaR model is valid because the LR value is smaller than the critical value of Chi-square 5% (3.84) and 1% (6.63).