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All Journal Operations Research: International Conference Series International Journal of Global Operations Research
Simanjuntak, Alberto
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Journal : Operations Research: International Conference Series

 1 
Use of ARIMA-GARCH Model to Estimating Value-at-Risk in Gudang Garam (GGRM) Stock Simanjuntak, Alberto
Operations Research: International Conference Series Vol. 1 No. 2 (2020): Operations Research International Conference Series (ORICS), June 2020
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i2.75

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.
Estimating Value-at-Risk in TLKM Shares using the ARIMA-GARCH Model Simanjuntak, Alberto
Operations Research: International Conference Series Vol. 1 No. 3 (2020): Operations Research International Conference Series (ORICS), September 2020
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i3.145

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 of Telekomunikasi Indonesia Persero Tbk.’s (TLKM) 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 TLKM shares. Based on the results of the study, it was found that the TLKM stock has a VaR of 0.022876. In other words, if an investment of IDR 1,000,000.00 is made for TLKM shares for 37 days (5% of 751 days), the investment period with a 95% confidence level, the maximum loss that may be borne by the investor is IDR 22.876.00.
Application of ARIMA-GARCH Model to Estimating Expected Shortfall in BMRI Stocks Simanjuntak, Alberto
Operations Research: International Conference Series Vol. 1 No. 4 (2020): Operations Research International Conference Series (ORICS), December 2020
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i4.149

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 possibility of profit. One way of calculating risk is to use the Expected Shortfall (ES). Because 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 ES calculations using time series analysis. The purpose of the study was to determine the expected shortfall value of BMRI shares using time series analysis. The data used for this research is the daily closing price of shares for three years. In 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 value and variance obtained from the model are then used in calculating the ES on BMRI stock. Based on the results of the study, it was obtained that BMRI's stock had an ES of 0.008116. This means if an investment is made for BMRI shares of IDR 1,000,000.00 for 37 days (5% of 751 days) for an investment period with a 95% confidence level, the expected loss to be borne by the investor is IDR 8,116.00.
Co-Authors Saputra, Jumadil