ARIMA-GARCH model for estimation of value-at-risk and expected shortfall of some stocks in Indonesian capital market

Puspa Liza, Ghazali and Sukono, . and Soeryana, E and Simanjuntak, A and Santoso, A and Bon, A.T. (2019) ARIMA-GARCH model for estimation of value-at-risk and expected shortfall of some stocks in Indonesian capital market. In: 1st GCC International Conference on Industrial Engineering and Operations Management, IEOM 2019;, 26-28 November 2019, riyadh; Saudi Arabia.

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Abstract

In stock investments, keep in mind the movements and risk of losses that may occur from investments made. One way to calculate risk is to use Value-at-Risk and Expected Shortfall. The purpose of this research is to determine the amount Value-at-Risk and Expected Shortfall of selected stocks using the time series model approach. The data used in this study is the daily closing price of some stocks for three years. In the time series modeling process, the models used for predicting stock movements are Autoregressive Integrated Moving Average (ARIMA) for the mean model, and Generalized Autoregressive Conditional Heteroscedasticty (GARCH) for the volatility model. The values of mean and variance obtained from the model are then used to calculate the Value-at-Risk and Expected Shortfall of each preferred stock. Based on the analysis, it was found that from the selected stocks, Bank Mandiri stocks had the lowest risk level and Mustika Ratu stocks had the highest risk level with the Value-at-Risk value of stocks generally smaller than the Expected Shortfall value

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