ESTIMASI VALUE AT RISK DAN EXPECTED SHORTFALL MENGGUNAKAN ASYMMETRIC EXPONENTIAL POWER DISTRIBUTION PADA DATA SAHAM

VaR is a risk measurement method that statistically estimate the maximum loss that may occur on an asset at a certain time and at a certain confidence level. However, often times the value of the loss exceeds the estimated VaR. VaR can not inform the magnitude of losses at the tail loss, thus introduced a measure of risk that can explain the value of the losses is Expected shortfall (ES). ES is the average of the tail loss or a loss in excess of VaR at a certain confidence level. In practice, the data return is often not symmetric (asymmetric) to the extent of the left and right of the area, making it difficult to capture the properties of the fat tail and skewness in the return distribution. Therefore, it is necessary Asymmetric Exponential Power Distribution (AEPD) extension from exponetial distribution, where AEPD have characteristic heavy tailed and the left and right parameter is different, so this distribution can capture the properties of the data