Abstract

Purpose. Investigate the methods of decision-making in the project portfolio management, as well as perform their software implementation as part of the system of the portfolio management optimization of energy saving projects at energy-intensive enterprises. Methodology. To achieve this goal, Markovitz's portfolio theory was chosen - the theory of financial investment, in which the methods of optimization are the most profitable distribution of the risk of the securities portfolio and income valuation. In combination with portfolio theory, methods were used to find the maximum Sharpe coefficient and minimum volatility according to randomly generated portfolios. Findings. Methods of portfolio management of energy saving projects are considered through their generalization to the methods of optimization of investment portfolios, but taking into account the specifics of the subject area. A software application has been developed and tested that automatically downloads data for certain stocks for a certain period from an electronic resource, generates random portfolios and optimizes them by maximizing the Sharpe ratio and minimizing portfolio volatility. Composing a portfolio of investments from four stocks traded on the stock exchange, the return and risk of the portfolio with different types of optimization were calculated. The application implements graphical display of portfolio optimization results in the form of tables and graphs. The first graph shows the changes in each stock over a given period of time. The following is a graph of daily profitability instead of actual prices, where you can see the volatility of shares. The simulated portfolio optimization based on the effective limit is graphically presented - the line along which the points will give the least risk to the target return and the calculated optimization of the portfolio based on the effective limit. The graphs and tables built by the program allow the user to better assess the created portfolio of the energy saving project. Originality. The approach proposed in this paper is a combination of methods for optimizing the investment portfolio according to Markovitz's portfolio theory and methods for finding the maximum Sharpe coefficient and minimum volatility in one software application to solve a wide range of problems. Practical value. The completed development has significant practical value, as it allows you to optimize quickly the financial portfolio for any assets, which allows, among other things, to use the system to optimize the management of portfolios of energy saving projects in energy-intensive enterprises. In addition, it can be the basis or model for a similar development.

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