Use of ARIMA-GARCH Model to Estimating Value-at-Risk in Gudang Garam (GGRM) Stock

Abstract

Stocks are one of the best-known forms of investment and are still used today. In stock investment, it is necessary to know the movement and risk of loss that may be obtained from the stock investment, so that investors can consider the possible losses. One way to calculate risk is to use Value-at-Risk (VaR). Since the stock movement is in the form of a time series, a model can be formed to predict the movement of the stock, which can then be used for VaR calculations using time series analysis. The purpose of the study was to determine the Value-at-Risk value of Gudang Garam Tbk.’s (GGRM) shares using time series analysis. The data used for this research is the daily closing price of shares for three years. At the time series analysis stage, the models used in predicting stock movements are Autoregressive Integrated Moving Average (ARIMA) for the mean model and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) for the volatility model. The average and variance values obtained from the model are then used in calculating the VaR of GGRM shares. Based on the results of the study, it was found that the GGRM stock has a VaR of 0.069598. In other words, if an investment of IDR 1,000,000.00 is made for GGRM shares for 37 days (5% of 747 days), the investment period with a 95% confidence level, the maximum loss that may be borne by the investor is IDR 69,598.00.