Optimization of the Investment Portfolio in the Environment of Table Processor MS Excel

This topic's study is due to modern challenges to ensure sustainable development in a volatile market environment. It is especially so for those who want to invest money to generate additional income, taking into account financial risks. For this, it is necessary to increase the level of use of information computer technologies to minimize financial risks. The work's practical significance is based on the analysis of mathematical models used in the formation of investment portfolios. For the first time, a comparative study of investment portfolios containing various types of assets in the Ukrainian economy (particularly cryptocurrency) was carried out, and their residual risks were analyzed. Optimal investment portfolios for direct and inverse problems have been formed. For the optimal use of savings and consideration of factors affecting the adoption of final investment decisions, the necessity of applying modern mathematical models and the capabilities of information computer technologies has been substantiated. Applied solutions are associated with processing a large amount of information, including in tabular form. Also, a significant part of these tasks is associated with optimization, and therefore the use of information technology is essential. One of these programs is a universal MS Excel, which can handle the tabular data and optimize both linear and nonlinear problems with the «Solver» and analyzed by the «Sensitivity» tool. Table processor MS Excel allowed processing tabular data using mathematical and statistical functions for working with matrices. For ease of use of the table processor features, a program was created in the VBA environment to install and select the parameters of the optimization models. The investment portfolio's optimal structures were calculated from the considered assets, which provide the maximum possible profitability at a given risk level (direct problem) or the lowest potential risk at given profitability (inverse problem). As a result, the investment portfolio's direct and inverse optimization problems were solved using the quasi-Sharpe model. All this allows the spreadsheet processor to be widely used both by professionals.