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.

Information and algorithmic support of a multi-level integrated system for the investment strategies formation

The article summarizes the accumulated practical experience of the authors in the development of algorithms for the formation of investment strategies. For this purpose, the optimization of the studied parameters, information support of investment activities, verification, monitoring and adjustment in the testing mode and the subsequent practical application of the described tools are considered. The system is based on the main provisions of the Markowitz portfolio theory. The analytical block of the Information System Portfolio Investor includes Profitability-Risk model; empirical models of optimal complexity; hybrid predictive model systems; the principle of combining (integrating) both models and forecasts, as well as decision rules; optimization of the training sample length (modified Markowitz model); optimization of the frequency of monitoring and adjusting the composition of the investment portfolio. The principles of design and development of the information block of the system, its replenishment and functioning are described in detail. All the above listed components of the algorithmic content of the investment decision making system are described sequentially. The system modules have been successfully tested on a wide class of financial instruments: ordinary shares, preferred shares, government and corporate bonds, exchange commodities, stock, commodity, industry and bond indices, exchange-traded investment funds and real estate funds. The implemented Markowitz model with a dynamic database of historical data can significantly increase the efficiency of investment decisions, which is facilitated by taking into account the characteristics of both the markets under study and the corresponding financial instruments.

Optimization of Stock Portfolio Using the Markowitz Model in the Era of the COVID-19 Pandemic

Stocks are one of the popular investment instruments traded in the capital market. The popularity of stock purchase has developed along with the massive financial literacy movement. However, the massiveness of this movement must be balanced with knowledge and expertise in managing stock instruments since they have a high return rate and high risk. One way to manage stocks is by developing an optimal stock portfolio based on the Markowitz model. The Markowitz model is a method that formulates the elements of return and risk in an investment, and specifically the elements of risk can be minimized through diversification and combination of various investment instruments into a portfolio. By using the Markowitz method, investors can take advantage of all available information as a basis for maximizing the portfolio. This study aimed to determine which stocks can form an optimal portfolio, especially in the era of the COVID 19 pandemic and the optimal proportion of the portfolio that is feasible to obtain from stocks listed in the LQ 45 Index. The study samples involved stocks listed in the LQ 45 Index. The data analysis technique applied in this study was portfolio optimization using the Markowitz model. The results of this study showed that the optimal portfolio consisted of BBCA with a weight of 78.09% and BRPT with a weight of 21.91% which produced an expected return of 2.35% and a standard deviation of 7.01%.

Simulation Of Optimal Portfolio Using Single Index Model and Markowitz Model On Lq-45 Index Shares For 2018

The essence of portfolio formation is to reduce risk by means of diversification, namely allocating a number of funds to various investment alternatives that are negatively correlated. To select returns in a portfolio, you can use the Single Index Model and the Markowitz Model. This study was conducted with the aim of comparing the calculation of which company portfolios can provide a good rate of return with a small risk using the Single Index and Markowitz Model based on the sector of the company. So that the results of this study can provide recommendations to investors in decision making on portfolio selection. The research was conducted on companies indexed by LQ 45 on the Indonesia Stock Exchange. The research period is to use companies indexed by LQ 45 in 2018 for two periods.

OPTIMASI PORTOFOLIO PADA SAHAM PEFINDO 25 DENGAN MENGGUNAKAN MODEL MARKOWITZ (STUDI KASUS DI BURSA EFEK INDONESIA)

Fund investment activities in the capital market required expertise to minimize the investment risk. One way was to form a portfolio. Markowitz model helped investors determined the stocks which was the member of the optimal portfolio. Minimization of risk and maximization of return became the urgent thing, and the value of the return expectation became the basis of calculation. This research used non probability sampling to select Pefindo 25 indeks stocks at BEI as a population and sample. Results showed from 25 sample that only 6 (six) stocks were included in the optimal portfolio, which was Adi Sara Armada Tbk (ASSA), Wilmar Cahaya Indonesia Tbk (CEKA), Elnusa Tbk (ELSA), Erajaya Swasembada Tbk (ERAA), Champion Pacific Indonesia Tbk (IGAR), dan Vale Indonesia Tbk (INCO). The optimal investment portfolio provided total expected return portfolio was 15.592 percent and a risk of deviation / variance portfolio was 0.108 percent.