METODE SIMULASI HISTORIS UNTUK PERHITUNGAN NILAI VALUE AT RISK PADA PORTOFOLIO DENGAN MODEL MARKOWITZ

A portfolio concerns the formation of the composition of multiple assets to obtain optimum results. At the same time, Value at Risk is a technique in risk management to measure and assess parametrically (variant and co-variant), Monte-Carlo, and historical simulation. This research employed historic simulation because normal distribution is not required from returns and is a Value at Risk calculation model that is determined by the past value on produced return asset, in which this research aimed to determine the Markowitz model positive shares and Value at Risk in the portfolio by using historical simulation. The Markowitz model found eight shares with positive expected returns, which are as follows: BBCA, BBRI, BRPT, EXCL, ICBP, INDF, MNCN, and TPIA. The BBCA has the most significant exposure of all the shares with the amount of Rp 2.287.200.440.000, while the TPIA has the smallest exposure of all the shares with the amount of Rp 58.899.375.000. Further, the EXCL has the largest VaR with the amount of Rp 236.189.538.497, while the TPIA and ICBP had no VaR losses because the VaR of TPIA and ICBP is Rp 0 and Rp -1.407.719.893, respectively, along with the INDF as the share with the smallest VaR of Rp 18.513.213.620. The most significant exposure average is Rp 719.246.318.375, while the largest VaR average is Rp 76.827.608.341,3. As long as the VaR did not exceed the exposure value, the investors will be safe and have no loss.

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Boom and Bust Driven by Value-at-Risk

Risk and Liquidity ◽

10.1093/oso/9780198847069.003.0003 ◽

2019 ◽

pp. 28-55

Author(s):

Hyun Song Shin

Keyword(s):

At Risk ◽

Value At Risk ◽

Hedge Fund ◽

Balance Sheet ◽

Asset Returns ◽

Expected Returns ◽

Capital Management ◽

A Value ◽

Boom And Bust

An example of a hedge fund illustrates a long-short strategy that maximises expected returns subject to a Value-at-Risk strategy. Balance sheet capacity depends on the measured volatility of asset returns and the book equity of the long-short hedge fund. The principles are illustrated by the case of Long Term Capital Management (LTCM).

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Analysis of Risk using Value at Risk (VaR) After Crisis in 2008 Study in Stocks of Bank Mandiri, Bank BRI and Bank BNI in 2009-2011

Information Management and Business Review ◽

10.22610/imbr.v5i8.1067 ◽

2013 ◽

Vol 5 (8) ◽

pp. 394-400 ◽

Cited By ~ 1

Author(s):

Hasna Fadhila ◽

Nora Amelda Rizal

Keyword(s):

At Risk ◽

Maximum Likelihood ◽

Value At Risk ◽

Maximum Likelihood Method ◽

Historical Data ◽

Likelihood Function ◽

Likelihood Method ◽

Normal Curve ◽

Historical Simulation ◽

Time Value

Value at Risk (VaR) is a tool to predict the greater loss less than the certain confidence level over a period of time. Value at Risk Historical Simulation produce reliable value of VaR because of the historical data and measure the skewness of the observe data. So, Value at Risk well used by investors to determine the risk to be faced on their investment. To calculate VAR it is better to use maximum likelihood, which has been considered for estimating from historical data and also available for estimating nonlinear model. It is also a mathematic function that can approximate return. From the maximum likelihood function with normal distribution, we can draw the normal curve at one tail test. This research conducted to calculate Value at Risk using maximum likelihood. The normal curve will be compared with data return at each bank (Bank Mandiri, Bank BRI and Bank BNI). Empirical results demonstrated that Bank BNI in 2009, Bank BRI in 2010 and Bank BNI in 2011, had less value of VaR by historical simulation in each year. It is concluded that by using maximum likelihood method in the estimation of VaR, has certain appropriates compared with the normal curve.

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