Formation Of Optimal Portfolio Research Articles

MENENTUKAN PORTOFOLIO OPTIMAL PADA PASAR SAHAM YANG BERGERAK DENGAN MODEL GERAK BROWN GEOMETRI MULTIDIMENSI

Model of stock price movements that follow stochastic process can be formulated in Stochastic Diferential Equation (SDE). The exact solution of SDE model is called Geometric Brownian Motion (GBM) model. Determination the optimal portfolio of three asset that follows Multidimensional GBM model is to be carried out in this research.Multidimensional GBM model represents stock price in the future is affected by three parameter, there are expectation of stock return, risk stock, and correlation between stock return. Therefore, theory of portfolio Markowitz is used on formation of optimal portfolio. Portfolio Markowitz formulates three of same parameter that is calculated on Multidimensional GBM model. The result of this research are optimal portfolio reaches with the proportion of fund are 39,38% for stock BBCA, 59,82% for stock ICBP, and 0,80% for stock INTP. This proportion of fund represents value of parameters that is calculated on modelling stock price.

ANALISIS PERBEDAAN RETURN DAN RISIKO SAHAM PORTOFOLIO OPTIMAL DENGAN BUKAN PORTOFOLIO OPTIMAL

The aim of this study is to find out if there are any differences of return and risk between optimal portfolio candidate and non-optimal portfolio candidate. This is a quantitative study with purposive sampling technique. Population of this study is all data of IDX 30 index which is 42 whereas the sample is 15. Analysis model that is used in this study is Markowitz method. The results of calculations using the Markowitz methods that includes the optimal portfolio with the proportion of funds that of UNVR stock as 31.19%, BBCA stock as 16.69%, ADRO stock as 14.14%, UNTR stock as 13.43%, PGAS stock as 9.33%, INDF stock as 7.73% and GGRM stock as 7.50%. The conclusion of this study is that there are no significant differences of return and risk on the formation of optimal portfolio. This shows that the preferences of investors do not consider the calculation methods Markowitz and indifference curve in selecting the optimal portfolio. Suggestion related to this study is that investor and investment manager may execute the investment fund to form an optimal portfolio Markowitz method as a benefit from stock diversification

The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm

Investments in financial assets have become a trend in the globalization era, especially the investment in mutual fund shares. Investors who want to invest in stock mutual funds can set up an investment portfolio in order to generate a minimal risk and maximum return. In this study the authors used the Multi-Objective Genetic Algorithm Non-dominated Sorting II (MOGA NSGA-II) technique with the Markowitz portfolio principle to find the best portfolio from several mutual funds. The data used are 10 company stock mutual funds with a period of 12 months, 24 months and 36 months. The genetic algorithm parameters used are crossover probability of 0.65, mutation probability of 0.05, Generation 400 and a population numbering 20 individuals. The study produced a combination of the best portfolios for the period of 24 months with a computing time of 63,289 seconds.

DEVELOPMENT OF PROJECTS PORTFOLIO OF HIGH-TECH ENTERPRISE

The rational use of expensive high-tech enterprise resources (financial, staff, technology) required formation of the appropriated project portfolio. In this article the mathematical model of the prior formation of a project portfolio of a high-tech enterprise with the available nomenclature of products and potential customers is proposed. The mathematical model of the optimal portfolio formation of high-tech enterprise Zorya-Mashproekt within available products (gas turbines), customers, and the cost of supplies in NEOS Server is calculated. NEOS Server provides the interaction between users and systems to solve many different types of optimization problems. Users download model file and data file in the language AMPL to the server which are then processed in different systems (KNITRO, MINTO, BARON, ASA, etc.). In the article the mathematical model and the input data are described in the language AMPL. The problem using MINTO NEOS-interface is solved.

Application of Markowitz model in analysing risk and return a case study of BSE stock

In this paper the optimal portfolio formation using real life data subject to two different constraint sets is attempted. It is a theoretical framework for the analysis of risk return choices. Decisions are based on the concept of efficient portfolios. Markowitz portfolio analysis gives as output an efficient frontier on which each portfolio is the highest return earning portfolio for a specified level of risk. The investors can reduce their risks and can maximize their return from the investment, The Markowitz portfolio selections were obtained by solving the portfolio optimization problems to get maximum total returns, constrained by minimum allowable risk level. Investors can get lot of information knowledge about how to invest when to invest and why to invest in the particular portfolio. It basically calculates the standard deviation and returns for each of the feasible portfolios and identifies the efficient frontier, the boundary of the feasible portfolios of increasing returns.

Finansinio sverto naudojimas aktyviai valdant investicijų portfelį

The analysis of the portfolio theories was carried out in the article. H. Markowitz theory of an optimal portfolio formation was briefly described, the process of the portfolio selection was discussed, the basic corrections, improvements, development and application of the theory suggested by the scientists were named. With reference to the literature analysis the most suitable portfolio theory was chosen for further development, aiming at the application of the theory to active portfolio management using the financial leverage. The basic limitations of the chosen theory were evaluated in order to apply it to the subject of research, specific development solutions were suggested and, on the grounds of them, the adjusted efficient set was proposed. An empirical research was carried out, validating the expedience of the financial leverage usage when actively managing the investment portfolio, and evaluating the intensity of the financial leverage usage. Built on the results of the research,the efficient set which was suggested in the theoretical-hypothetical part of the study was adjusted.