Financial Journal

27-42

Authors: O.K. Yastrebova, O.I. Karasev

The key actual task of improving the tools of scientific and technological policy is the focus of R&D on obtaining socially significant results, including the creation of in-demand innovative products and technologies. Its solution requires appropriate improvement of the system of financial support for science. The authors of the article consider the existence of a clearly structured relationship between the national goals set for the scientific field as a whole and specific tools for their achievement as a necessary condition for effective management of this sphere. The paper analyzes the key instruments of R&D financing from the point of view of approaches to ensuring their effectiveness. The necessity of linking the volume of funding with the achieved results is shown, and specific proposals to solving this problem are made, including those based on the assessment of the technology readiness level (TRL).

63-81

Authors: A.I. Denisova, D.A. Sozaeva, K.V. Gonchar, G.A. Aleksandrov

The study raises the issue of evaluating the effectiveness of public procurement, especially procurement of medicines. This topic is relevant, since a significant part of state funding is directed specifically to the healthcare system. In addition, the quality of organization of procurement activities affects the work of hospitals and polyclinics. In this regard, the improvement of the methodology for assessing the economic efficiency of public procurement, particularly procurement of medicines, is critically important. The paper presents the results of statistical analysis showing the need to develop a more comprehensive methodology that takes into account the volume of failed purchases in the context of efficiency assessment. The issue of "repeated" purchases was studied separately, since information about them would allow drawing conclusions about the existing patterns in tenders and the reasons for recognizing a purchase as failed. The methodological novelty is associated with the description of the approach to the formation of a sample for research and the algorithm for identifying "repeated" procurement procedures. All calculations are based on real data on procurement under the Federal Law No. 44-FZ for 2021–2022. The data was aggregated from the Unified Information System for Procurement. A statistical analysis of the scale of failed and repeated purchases in the context of regions, medicines and pharmacotherapeutic groups has been conducted. Based on the analysis, approximate estimates of hidden costs of the state budget related to re-organizing and re-conducting of trade procedures are given. The results of the work can be used for further scientific research in the field of public procurement efficiency, as well as to improve public policy in the field of procurement and provision of medicines.

98-111

Authors: Zh.A. Mingaleva, I.A. Nikitina, I.A. Kruglova

Introduction: Investment decisions by many private and institutional investors are made taking into account the information (current estimates, forecasts, trends) contained in various country ratings regularly published by leading international financial and regulatory organizations (IMF, IBRD, UN), which allows investors to assess the level of risk and return on investment in various projects in these countries. The article evaluates the Environmental Performance Index (EPI), the most common in international studies, from the point of view of its use as a comprehensive tool for comparative analysis and an indicator for assessing the success of achieving the goals of sustainable social and environmental development of Russian regions. Purpose: Analysis of the feasibility of using EPI and its individual elements as part of an integrated approach to assessing the effectiveness of social and environmental development of Russia and its regions. Results: The authors reviewed the transformation of the methodology for calculating EPI over the entire period of its compilation; analyzed the dynamics of indicators, directions and blocks that make up the Index; assessed their adequacy to the geographical and sectoral features of social and environmental development. Conclusions: An extremely high level of politicization of the Index and inconsistency of its calculation methodology with the real conditions of Russia’s economic development were revealed. The inexpediency of its use in the present conditions to assess the social and environmental development of Russian regions, to build a rating of their sustainable development, to develop criteria for evaluating the effectiveness of environmental programs and projects, including in the field of green and environmental investments, was proved.

123-137

Authors: A.Yu. Mikhaylov, V. Khare, S. E. Uhunamure, Ts. Chang, D.I. Stepanova

The goal of the article is to develop an innovative forecasting approach based on the Random Forest and fuzzy logic models for predicting crypto-asset prices (IFSs, PFSs, q-ROFSs). The baseline forecast horizon is 90 days (additional horizons are 30, 60, 120 and 150 days), which allows to estimate the significance of the chosen features and the impact of time on the forecast accuracy. The paper proposes an optimal data selection approach for the Random Forest and fuzzy logic models to improve the prediction of the daily closing price of Bitcoin, using online social network activity, trading parameters, technical indicators, and data on other cryptocurrencies. This paper utilizes a tree-based machine learning prediction and a fuzzy logic model for Bitcoin. The article attempts to prove that automated Bitcoin forecasting using machine learning algorithms is very effective for the cryptocurrency market. Nevertheless, the latter is characterized by high volatility, significant rate hikes of the most liquid cryptocurrencies (mainly Bitcoin). Therefore, investments in cryptocurrencies, especially long-term ones, involve significant risks. This defines the paper’s significance for investors and regulators. As shown by simulation studies of data selection approaches generalizing the accuracy performance of the Random Forest and fuzzy logic models to real preferences of forecasting, even under significant noise measurements, the proposed selection approach leads to fast convergence of estimates. The accuracy of the model’s results exceed 85.21 on a 90-day time horizon.