The paper focuses on monitoring and modelling of the cryptocurrency market. The application of the chosen research methods is based on the analysis of existing methods and tools of economic and mathematical modelling of time series research on the example of the cryptocurrency market. It is proved that the use of individual methods is not relevant, as they do not give an adequate assessment of the specified market, so a comprehensive approach is the most acceptable. Therefore, monitoring and modelling of some cryptocurrency pairs with different capitalization degree were implemented by fractal and recurrent methods of the financial markets. The daily values of currency pairs for the period from September 2015 to November 2019 were chosen as information basis for monitoring and modelling. The use of R/S modelling method make it possible to conclude the persistence of time series of the selected cryptocurrencies indicating that the market trends are clearly defined, the currency pair of XRP/USD has the highest level of trend resistance. To compare the obtained results, the comprehensive approach is offered using recurrent diagrams that help to determine the cryptocurrency stability. The results of modelling by the recurrent method show that the most stable cryptocurrencies are the ones with the highest capitalization, namely Bitcoin and Ripple.

In this article, we present the results of simulation for cryptocurrency market based on fractal and entropy analysis using six cryptocurrencies in the first 20 of the capitalization rating. The application of the selected research methods is based on an analysis of existing methodologies and tools of economic and mathematical modeling of financial markets. It has been shown that individual methods are not relevant because they do not provide an adequate assessment of the given market, so an integrated approach is the most appropriate. Daily values of cryptocurrency pairs from August 2016 to August 2020 selected by the monitoring and modelling database. The application of fractal analysis led to the conclusion that the time series of selected cryptocurrencies were persistent. And the use of the window procedure for calculating the local Hurst coefficient allowed to detail and isolate the persistant and antipersistant gaps. Interdisciplinary methods, namely Tsallis entropy and wavelet entropy, are proposed to complement the results. The results of the research show that Tsallis entropy reveals special (crisis) conditions in the cryptocurrency market, despite the nature of the crises’ origin. Wavelet entropy is a warning indicator of crisis phenomena. It provides additional information on a small scale.

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The purpose of this study is to assess the structural changes in the national economy of Ukraine, the countries of the European Union, the USA and the Republic of Bilorus, which is supposed to be implemented through the use of an integrated indicator of the assessment of structural changes in the sectoral structure of The choice of components of the integral indicator for structural changes is due to the sectoral division of GDP into industry, agriculture and services. The proposed integral indicator reflects the harmonious (ideal) GDP structure peculiar to the post-industrial economy, while deviations in the real structure indicate structural changes in the national economy of Ukraine, the European Union, the USA and the Republic of Bilorus. The article presents the results of the calculation of the integral indicator of structural changes in the sectoral structure of GDP and its structural elements. Besides, the article provides analysis of the reasons for the deviations of real indicators from the harmonious ones. The calculations show the crisis phenomena both in the Ukrainian economy and in the EU, the USA and the Republic of Belarus.The domestic economy demonstrates significant deviations in virtually all sectors, indicating a low level of economy, a mismatch between supply and demand in the labor market, a low level of innovation, and the inertia of transformational processes within the transition to the post-industrial stage of production. The ISSN 2707-5036 . 2019 4 102application of the proposed methodology will allow us to identify strategic directions for the development of national economy sectors and develop forecast scenarios.

The article deals with various distance learning management system for pedagogical higher education institution. The most prominent distance learning management systems are mostly focused on: Moodle, WebCT, BlackBoard, eFront, Claroline, Metacoon, SharePoint LMS and Virtual University. Having analyzed the best platforms for creating of distance learning system in pedagogical higher education institution, it is stated that Moodle is leading according to the number of users. Moodle platform is a software suite for creating distance learning courses and websites that works with open source IMS and SCORM. As a result of the analysis and comparisons of the abovementioned platforms, based on pedagogical, didactic, organizational, technical, financial distance learning features, the distance learning management system in State Higher Educational Institution «Pereiaslav-Khmelnytskyi Hryhorii Skovoroda State Pedagogical University» on the basis of Moodle platform is developed. The platform works in different web browsers. There are no special requirements for hardware and operating system. Moodle platform can be installed on any server with any operating system using arbitrary databases. The platform is free for users. Moodle distance learning management system consists of 35 modules: Chat module, Task module, Forum module, Log module, Test module, Resource module, Research module, Seminar module and so on. Moodle distance learning management system enables distance learning in higher education at an affordable innovation level, creates a calendar of learning process events, creates formal algorithms for the teacher's activity in the educational process, thereby achieving a high level of interactivity and achievement of the required level of quality, skills.