scholarly journals Price Index Modeling and Risk Prediction of Sharia Stocks in Indonesia

Economies ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 17
Author(s):  
Hersugondo Hersugondo ◽  
Imam Ghozali ◽  
Eka Handriani ◽  
Trimono Trimono ◽  
Imang Dapit Pamungkas
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Prediction ◽  
Stock Prices ◽  
Value At Risk ◽  
Stock Price ◽  
Price Index ◽  
Simulation Approach ◽  
Trading Period ◽  
Short Time

This study aimed to predict the JKII (Jakarta Islamic Index) price as a price index of sharia stocks and predict the loss risk. This study uses geometric Brownian motion (GBM) and Value at Risk (VaR; with the Monte Carlo Simulation approach) on the daily closing price of JKII from 1 August 2020–13 August 2021 to predict the price and loss risk of JKII at 16 August 2021–23 August 2021. The findings of this study were very accurate for predicting the JKII price with a MAPE value of 2.03%. Then, using VaR with a Monte Carlo Simulation approach, the loss risk prediction for 16 August 2021 (one-day trading period after 13 August 2021) at the 90%, 95%, and 99% confidence levels was 2.40%, 3.07%, and 4.27%, respectively. Most Indonesian Muslims have financial assets in the form of Islamic investments as they offer higher returns within a relatively short time. The movement of all Islamic stock prices traded on the Indonesian stock market can be seen through the Islamic stock price index, namely the JKII (Jakarta Islamic Index). Therefore, the focus of this study was predicting the price and loss risk of JKII as an index of Islamic stock prices in Indonesia. This study extends the previous literature to determine the prediction of JKII price and the loss risk through GBM and VaR using a Monte Carlo simulation approach.

Price Limits, the VaR calculation, and a Monte Carlo Simulation

2002 ◽  
Vol 10 (1) ◽  
pp. 81-111
Author(s):  
Jin Yoo
Keyword(s):  
At Risk ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Confidence Level ◽  
Value At Risk ◽  
Stock Price ◽  
Price Limits ◽  
Holding Period ◽  
A Value ◽  
Practical Implications

This paper raises an issue of calculating a value at risk (VaR) of a stock price in the presence of daily price limits, suggests an appropriate methodology for it, and discusses its practical implications. One finding is that the VaR with price limits is never bigger than without. It turns out that the discrepancy between the two VaRs increases as the confidence level rises, the holding period lengthens, the volatility goes up, or the price limits get tighter.

scholarly journals Applying three VaR (value at risk) approaches in measuring market risk of stock portfolio: The case study of VN-30 stocks basket in HOSE

2017 ◽  
Vol 24 (02) ◽  
pp. 90-113
Author(s):  
Thinh Nguyen Quang ◽  
Quy Vo Thi
Keyword(s):  
At Risk ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Value At Risk ◽  
Stock Price ◽  
Stock Exchange ◽  
Market Risk ◽  
Risk Models ◽  
Historical Simulation ◽  
Back Testing

This study examines and applies the three statistical value at risk models including variance-covariance, historical simulation, and Monte Carlo simulation in measuring market risk of VN-30 portfolio of Ho Chi Minh stock exchange (HOSE) in Vietnam stock market and some back-testing techniques in assessing the validity of the VaR performance in the timeframe of January 30, 2012–February 26, 2016. The models are constructed from two volatility methods of stock price: SMA and EWMA throughout the five chosen confi-dence level: 90%, 93%, 95%, 97.5%, and 99%. The findings of the study show that the differences among the results of three models are not significant. Additionally, three VaR (Value at Risk) models have generally the similar accepted range assessed in both types of back-tests at all confidence levels considered and at the 97.5% con-fidence level. They can work best to achieve the highest validity level of results in satisfying both conditional and unconditional back-tests. The Monte Carlo Simulation (MCS) has been considered the most appropriate method to apply in the context of VN-30 port-folio due to its flexibility in distribution simulation. Recommenda-tions for further research and investigations are provided according-ly.

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