This is an introductory text to a collection of selected papers from the M3E2 2019: The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy, which was held in Odessa, Ukraine, on the May 22-24, 2019. It consists of short introducation and some observations about the event and its future.
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.
The article considers the possibility of analyzing the dynamics of changes in the characteristics of time series obtained on the basis of recurrence plots. The possibility of using the studied indicators to determine the presence of critical phenomena in economic systems is considered. Based on the analysis of economic time series of different nature, the suitability of the studied characteristics for the identification of critical phenomena is assessed. The description of recurrence diagrams and characteristics of time series that can be obtained on their basis is given. An analysis of seven characteristics of time series, including the coefficient of self-similarity, the coefficient of predictability, entropy, laminarity, is carried out. For the entropy characteristic, several options for its calculation are considered, each of which allows the one to get its own information about the state of the economic system. The possibility of using the studied characteristics as precursors of critical phenomena in economic systems is analyzed. We have demonstrated that the entropy analysis of financial time series in phase space reveals the characteristic recurrent properties of complex systems. The recurrence entropy methodology has several advantages compared to the traditional recurrence entropy defined in the literature, namely, the correct evaluation of the chaoticity level of the signal, the weak dependence on parameters. The characteristics were studied on the basis of daily values of the Dow Jones index for the period from 1990 to 2019 and daily values of oil prices for the period from 1987 to 2019. The behavior of recurrence entropy during critical phenomena in the stock markets of the USA, Germany and France was studied separately. As a result of the study, it was determined that delay time measure, determinism and laminarity can be used as indicators of critical phenomena. It turned out that recurrence entropy, unlike other entropy indicators of complexity, is an indicator and an early precursor of crisis phenomena. The ways of further research are outlined.
The article emphasizes the importance of information and digital technologies in pre-service training of primary school teachers, substantiates the content and components of information and digital competence of prospective primary school teachers. It points out that the main purpose of information and digital training in the pedagogical higher educational institutions (HEI) is to ensure the formation of digital competence of future primary school teachers, to prepare them for developing primary students’ digital literacy in classes on various academic subjects, for active use of ICT in primary school teachers’ professional activities. An integrated approach to the modernization of information and digital training of pre-service primary school teachers, which covers the main forms of the educational process – training sessions, independent work, practical training, and control activities is justified. The article presents the results the pedagogical experiment aimed at testing the effectiveness of the integrated approach to the modernization of information and digital training of prospective primary school teachers. The results are determined by the level of digital literacy and the ability of students in the control and experimental groups to use information and digital technology in the educational process of primary school.
This is an introductory text to a collection of selected papers from the M3E2 2020 Summer: The Special Edition of International Conference on Monitoring, Modeling & Management of Emergent Economy, which was held in Odessa, Ukraine, on the July 13-18, 2020. It consists of short introduction and some observations about the event and its future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.