The purpose of this article is to analyze the effect that halving has on the fair market value of bitcoins. The main hypothesis of the study is that the decline in the cost of miners’ remuneration for mining is a significant factor that affects the price of cryptocurrencies. The article examines the factors that regulate the issuing process. The significance of a limited supply of bitcoin is detailed in the article, as well as the mechanism for the implementation of the issue of new bitcoins. The study compares the historical inflation data of the US dollar and the projected data on the inflation of bitcoin. The article analyzes the main technical element of cryptocurrency – halving – when the miner’s reward is halved. This analysis includes the mathematical methods of statistical data processing. Research results show that reducing remuneration by half every four years leads to an increased market value of the cryptocurrency. This relationship is clearly illustrated by the Kendall rank correlation method. The results of the study can have a significant impact on the fundamental assessment of bitcoin and can also enable investors to assess any of the existing and operating cryptocurrencies according to this method.

Energy Efficient Development Model for Regions of the Russian Federation: Evidence of Crypto Mining

Priorities of Russian Energy Policy in Russian-Chinese Relations

Digital trading apps are evidence of developing open innovations in the financial sector. The investment industry (including banks and brokers) can greatly benefit from the utilization of digital trading applications and corresponding tools, such as smart contracts. The goal of this research paper is to examine the possibility that brokers’ existing mobile apps outperform banks without mobile apps in the Russian financial sector. The efficiency of brokers is compared to banks in Russia. The results of these institutions’ activities are related to the number of profitable banks, which declines as a sign of high efficiency. The paper uses methods of t-test, linear and polynomial regression analysis between assets (dependent variable) and the profit to assets (independent variable) in Russia. The article finds the different directions of the utilization of the discussed technology, and they all share the consequential growth after the technology’s introduction. The paper also discusses the various areas of digital trading apps implementation and the future contributions for the Russian banking system and economy.

This study proposes the concept of Analytic Hierarchy Processing (AHP) on the market of active substances used in treatment of HIV and checks the control factors and criteria interconnection and implements Random Forest forecasting model. The new method must help to improve the management decision-making process in the fields of healthcare government budget planning. It has become a prime concern for understanding and comparing of publicly available information with internal market data and the consequences of companies' and government s actions in choosing the best approach for correct construction of to reduce HIV incidence in Russia. The paper develops the forecasting model of one of the parameters, which has a substantial role in decision-making process. The medication market data in this study represents the cumulative daily concluded contracts, used in treatment of HIV in Russia, the level of HIV incidence (yearly) and federal budget on healthcare (yearly). The proposed approach have more than 82% average accuracy at predicting the sum of medication contract prices at the 3-year time period. The received figures are effective in predicting the factors' behavior in future. It can be used for improved modulation of AHP and consequently, the overall accuracy of the model structure.