Abstract
This study analyzes the application of Value at Risk (VaR) in estimating the risk of investment in banking stocks and the formation of an optimal portfolio using the Mean-VaR method based on the Markowitz approach. Many studies show that market data are often abnormal and make the assumption of normality considered irrelevant. This is the background of research on VaR using the historical simulation method, which is a method that moves away from the concept of normality. In addition, the crisis due to the Covid-19 pandemic makes the market difficult to predict. The period used in this study is during a normal market and a crisis (covid-19 pandemic). VaR is calculated with a holding period (t) of one week and a confidence level of 95%. Based on the backtesting test, the historical simulation method is accepted as an accurate method in estimating the VaR value in both normal and crisis periods. The optimal portfolios formed based on the mean-VaR are Portfolio-1 (normal period) and Portfolio-2 (crisis period). The composition of Portfolio-1 is BBRI, BBCA, BNLI, BTPN, and BNBA with the optimal proportion of each share sequentially of (18.35%), (23.90%), (11.39%), (18.63 %), and (27.73%). The VaR value of Portfolio-1 is -0.0107. The composition of Portfolio-2 is BNII and BNBA with optimal proportions of each share (22.71%) and (77.29%). The VaR value of Portfolio-2 is -0.0354. The results of this study can be used by investors as a reference in making investment decisions that focus on downside risk.
Highlights
Since the introduction of RiskMetricsTM in 1994 by J.P
The results proved that the historical simulation method accurately measured an enormous potential loss on mutual fund investments
The development of the mean-VaR model can assist in making decisions to form an optimal portfolio of bank stocks with risk measured using Value at Risk
Summary
Since the introduction of RiskMetricsTM in 1994 by J.P. Morgan, Value at Risk (VaR). Modern Portfolio Theory by Harry Markowitz in 1952 explained that portfolio weighting uses a calculation It considers the risk of each investment called the meanvariance model, where the expected return is calculated using the average method (mean) and variance as a risk measure used ( Hartono, 2014). The development of the mean-VaR model can assist in making decisions to form an optimal portfolio of bank stocks with risk measured using Value at Risk. Jorion (1996) explained the concept of Value at Risk (VaR), which is defined as a risk measurement method that statistically estimates the maximum possible loss on an investment over a specific time horizon target at a certain confidence level in the normal market conditions. Mean-VaR Portfolio Ismanto (2016) explained that forming an optimal portfolio with the mean-VaR approach is developing a model from Markowitz, namely, changing the risk measure from standard. The efficient frontier VaR is similar to the meanvariance frontier except for the definition of risk, where risk is reflected by the VaR and not the standard deviation
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