Browsing by Author "Viktoriia Radko"

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    Alchemy of innovations as a way to achieve economic development of Ukraine
    (Scientific and practical journal "Economics and technical engineering", 2023-10-25) Kateryna Holikova; Viktoriia Radko; Svitlana Matsyura
    The alchemy of innovation refers to the process of transforming or transforming elements, ideas or processes into something new, valuable and useful in order to achieve progress and development in various fields such as economics, science, technology and business. The term can cover a wide range of activities, including the introduction of innovations, the development of new products, processes or strategies, and the improvement of existing systems in order to achieve more effective results. Given the rapid development of digital technologies and the transformation of business processes, the alchemy of innovation becomes relevant in the context of the search for new strategies and approaches to stimulate the development of the economy and business, of any country. Of course, Ukraine is no exception. The article is aimed at analyzing the modern directions of innovations on the basis of the study of key trends and basic platforms for implementation in the field of development of digital technologies, which will allow to identify and describe the most effective tools, taking into account the domestic specifics and difficulties of implementation in conditions of uncertainty. The study showed that Ukraine's position in the ranking of digital competitiveness in terms of the main components in 2021 is increasing in the categories of "Knowledge," "Technology" and "Future readiness" due to such sub-factors as an increase in total state spending on education, the number of women researchers, increased investment in telecommunications and increased use of big data and analytics. Some digital technologies are not effective for Ukraine because of their complexity of implementation and cost of implementation in conditions of full-scale war. The digital economy sector in Ukraine has the potential to ensure the stability and growth of necessary financial revenues, especially for post-war reconstruction. Digital solutions are of interest not only from a financial point of view, but also strategic, as they can improve the efficiency of the industries in which they are integrated, including government and military sectors. Given the existence of such trends, we consider it promising to further expand, improve the practice of using digital technologies in Ukraine to achieve its economic development.
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    Forecasting Energy Market Dynamics with ARIMA approaches and Complex Network Indicators
    (Scientific and practical journal "Economics and technical engineering", 2025-12-30) Andrii Bielinkyi; Victoria Solovieva; Viktoriia Radko; Maksym Seleznov; Tetiana Pavlysh
    This study develops and evaluates a hybrid forecasting framework for energy market dynamics that combines classical econometrics with complex network science. Using daily West Texas Intermediate (WTI) spot prices from May 23, 1990 to October 30, 2025, we target short-horizon risk by forecasting 7-day forward returns, standardized via a rolling 50-day mean and volatility to mitigate heteroskedasticity. The univariate price series is mapped into Natural Visibility Graphs (NVGs) on rolling windows ( = 25, 50, 75, 100 days), and a vector of topological descriptors is extracted at each step, including spectral measures (e.g., algebraic connectivity, spectral gap, natural connectivity, graph energy) and centrality/efficiency and clustering indicators (e.g., global efficiency, harmonic centrality, betweenness, maximum degree, clustering, assortativity). These metrics serve as exogenous regressors in an ARIMAX model, enabling the forecasting engine to incorporate structural information embedded in the geometry of price history. Empirical results show that NVG topology exhibits regime-dependent signatures: crisis episodes are associated with sharp shifts in centralization and connectivity, and several network indicators become statistically significant predictors of standardized 7-day returns. In particular, global efficiency and harmonic centrality repeatedly emerge as dominant covariates, with coefficient signs varying across window lengths, consistent with multi-timescale market behavior. The sample is split into a pre-2020 training set and a post-2020 testing set to stress-test robustness under extreme events. The findings highlight heterogeneous horizons in oil price dynamics and the value of NVG features for practical forecasting and monitoring.