Open AccessValue-at-Risk Estimation Method Based on Normal Distribution, Logistics Distribution and Historical Simulation
Author(s) -
Dwi Susanti,
Sukono Sukono,
Maria Jatu Verrany
Publication year - 2020
Publication title -
operations research international conference series/operations research.international conference series
Language(s) - English
Resource type - Journals
eISSN - 2723-1739
pISSN - 2722-0974
DOI - 10.47194/orics.v1i1.19
Subject(s) - value at risk , portfolio , econometrics , stock (firearms) , normal distribution , distribution (mathematics) , economics , mathematics , computer science , statistics , financial economics , risk management , engineering , finance , mechanical engineering , mathematical analysis
This paper discusses the risk analysis of single stock and portfolio returns. The stock data analyzed are BNI, BRI shares and portfolio. After obtaining a stock return, value at risk (VaR) will be estimated using the normal distribution approach, logistic distribution, and historical simulation. From the VaR results, a backtest is then conducted to test the validity of the model and the backtest results for BNI and the portfolio produce a smaller QPS on the historical simulation method compared to the normal distribution and logistics distribution approaches. This shows that BNI VaR and VaR portfolios with the historical simulation method are more consistent than other methods. While the backtest results for BRI produced the smallest QPS on the normal distribution approach compared to the logistical distribution and historical simulation approaches. This shows that the VaR BRI using the normal distribution approach is more consistent than the other methods.