Vilnius University Press Scholarly Journals
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Comparative Analysis of Deep Learning Models for Cryptocurrency Price Predictions: Evidence Based on Bitcoin (BTC), Ethereum (ETH), Ripple (XRP) and Solana (SOL)
No full textThis research examines deep-learning and machine-learning models for cryptocurrency price prediction, with a keen focus on Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Solana (SOL). Cryptocurrencies exhibit high volatility, non-linear behavior and are able to react strongly to exogenous events, making their prediction and forecasting challenging. The primary aim of this research is to determine which predictive models yield optimal performance in characterizing these complexities and to provide empirical guidance on real-life investment and risk-management applications. Four approaches were used for this forecasting: Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), a combination of LSTM-GRU models, and Stochastic Gradient Descent (SGD) regression. The daily historical data were used to train and test each model on different forecast horizons, and performance was measured accordingly by Mean Squared Error (MSE) and Mean Absolute Error (MAE) values. As shown in the results, it can be observed that GRU exhibited the lowest error rates in the majority of the assets, particularly in short-term predictions. LSTM demonstrated a promising ability to capture long dependencies, whereas the hybrid LSTM-GRU system showed a similar performance proficiency by combining the relative superiorities of the two respective models. On the other hand, the conventional SGD regression was the worst among all the deep-learning algorithms, thereby demonstrating the extreme capability of these algorithms in modelling non-linear time sequences. The results confirm GRU as the most viable model for AI-powered crypto prediction and demonstrate the potential of hybrid architecture, at least in certain situations. This study will contribute to the existing debates about the role of deep learning in predicting financial outcomes and provide valuable insights to traders, analysts, and researchers navigating the uncertainties of the digital asset world
The Dark Side of The Moon: Unmasking Behavioral Risk Behind Fintech Adoption Among Digital Natives
No full textThe rapid expansion of financial technology ( fintech) has reshaped financial behavior, especially among digital natives in Indonesia. This study examines the impact of financial inclusion and financial literacy on online loan decisions and impulsive buying behavior, with online loan decisions serving as a mediator. A survey was conducted with 334 respondents, focusing on digital natives who have used online loan services. Using Structural Equation Modeling (SEM), the study found that financial inclusion positively influences online loan decisions, while financial literacy negatively impacts both online loan decisions and impulsive buying behavior. Notably, online loan decisions partially mediate the relationship between financial inclusion, financial literacy, and impulsive buying behavior. These findings highlight the complex role of fintech in promoting financial inclusion while also introducing behavioral risks. The study underscores the importance of financial literacy in mitigating impulsive financial behaviors among digital natives
FDI Spillovers in Emerging Markets: Does Economic Policy Uncertainty and Geopolitical Risk Matter?
No full textThis study investigates the influence of economic policy uncertainty (EPU) and geopolitical risk (GPR) on the spillovers of foreign direct investment (FDI) within emerging markets, represented by the BRICS (Brazil, Russia, India, China, and South Africa) nations. Using a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model and a dynamic Diebold and Yilmaz (DY) (2012) spillover index, the research assesses the interconnectedness and spillover effects of FDI flows among the BRICS countries over a 25-year period (1998–2023). The findings reveal significant spillover effects in the FDI of the BRICS nations, with Russia being a net transmitter and China a net receiver. Moreover, EPU and GPR significantly influence these FDI spillovers, with the effect of GPR being more predominant, highlighting the increased sensitivity of emerging markets to economic and geopolitical risks. Therefore, these findings underscore the role of coordinated policy measures in mitigating systemic risks and enhancing resilience against geopolitical and economic shocks. Overall, this study represents a novel contribution to existing literature by providing insight into the impacts of economic policy and geopolitical uncertainties on spillovers of foreign financial flows in emerging markets, particularly the BRICS nations
XXII-osios Jaunųjų mokslininkų psichologų konferencijos pranešimų santraukų leidinys
No full textConference of Junior Researchers in Psychology is an annual event organised by the doctoral students of the Institute of Psychology of Vilnius University. The conference provides an opportunity for psychology students and young researchers from Lithuanian and foreign universities to present their research and discoveries. This year\u27s conference was dedicated to exploring the challenges and opportunities of everyday life in a changing world. Jaunųjų mokslininkų psichologų konferencija – kasmetinis Vilniaus universiteto Psichologijos instituto doktorantų organizuojamas renginys. Konferencija suteikia galimybę Lietuvos ir užsienio universitetų psichologijos studentams ir jauniesiems mokslininkams pristatyti savo mokslinius tyrimus ir atradimus. Šių metų konferencija buvo skirta nagrinėti kasdienybę kintančiame pasaulyje, apibūdinančius iššūkius ir galimybes  
On k-fuzzy metric spaces with applications
No full textWith application point of view, Gopal et al. [D. Gopal, W. Sintunavarat, A.S. Ranadive, S. Shukla, The investigation of k-fuzzy metric spaces with the first contraction principle in such spaces, Soft Comput., 27:11081–11089, 2023] generalized the conceptions of a fuzzy metric space and introduced the definition of k-fuzzy metric space. Here a fuzzy set defined in k-fuzzy metric space is a membership function FY : X × X × (0, +∞)k -> [0; 1], that is, the fuzzy distance between two points of the set depends on more than one parameter, and then also introduced first contraction principle in this space. In this sequel, we extend the work on k-fuzzy metric spaces by generalizing Banach contraction principle by introducing various type of inequalities. Here we introduce Tirado-type k-fuzzy contraction condition and prove fixed point theorem for Tirado-type contractive mapping. We also discuss the k-fuzzy ψ-contractive mapping, where ψ ∈ Ψ, and Ψ is a class of mappings defined from ψ : [0; 1] -> [0; 1] that has certain properties, and also obtained fixed point for such class of mappings. Later, we define Ćirić-type contraction inequalities to prove fixed point results by restricting ourselves on l-natural property of the fuzzy space to ensure the existence of fixed point. Between all results, a set of supportive examples are also produced to validate the results. In application section, we discuss the solutions of Volterra-type integral equations and second-order nonlinear ordinary differential equation
Estimations for the convex modular of the aliasing error of nonlinear sampling Kantorovich operators
No full textIn this paper, we establish quantitative estimates for the nonlinear sampling Kantorovich operators in the general setting of modular spaces Lρ. To achieve this, we consider a notion of modulus of smoothness based on the convex modular functional ρ, which defines the space. The approach proposed is new in the sense that, in the literature, theorems for the order of approximation in Lρ are mainly qualitative, i.e., are proved considering functions belonging to Lipschitz classes; here the estimates are achieved for every function belonging to the whole Lρ. To show the effectiveness of the achieved results, several particular cases of modular spaces are presented in detail
Mitigating atmospheric carbon dioxide through deployment of renewable energy: A mathematical model
No full textIn recent decades, the widespread reliance on fossil fuels has grown substantially, leading to a rise in atmospheric carbon dioxide (CO2), which poses a major global concern. In this study, we develop and analyze a novel mathematical model to examine the interactions between atmospheric CO2, human population, and energy demand. The model assumes that human activities and energy production from traditional sources (oil, coal, and gas) contribute to increasing CO2 level, while a shift in energy dependence from traditional to renewable sources (hydro, solar, etc.) occurs as a result of environmental awareness. We derive sufficient conditions for both local and global stability of the system’s interior equilibrium. Numerical simulations demonstrate that when reliance on renewable energy sources is low, the system can exhibit oscillatory dynamics and various bifurcations. However, beyond a critical threshold of renewable energy dependency, the system stabilizes around the interior equilibrium, leading to a reduction in atmospheric CO2. Additionally, an optimal control problem is formulated to reduce atmospheric CO2 level while minimizing the associated implementation costs
Existence of solution for a fractional differential system on the chemical graph of glycerol
No full textIn this paper, we study the chemical graph for an important polyalcoholic compound with the molecular formula C3H8O3 by using 0 or 1 to label the elements of its molecular structure graph and formulating the corresponding fractional boundary value problem on each edge of the graph. Under the sense of Caputo’s fractional derivatives, the existence of solutions of the fractional boundary value problem on the glycerol graph is investigated by introducing some suitable growth conditions and combing with some fixed point theorems. A specific example is given to verify our results
Soliton stability and topological invariants in a generalized nonlinear Klein–Gordon equation: Existence, dynamics, and conservation laws
No full textThis paper investigates the stability and dynamical behavior of soliton solutions in generalized nonlinear Klein–Gordon equations defined on higher-dimensional manifolds. We establish the existence of stable multisoliton configurations using variational methods and demonstrate their stability under small perturbations through energy estimates and topological considerations. Furthermore, we explore topological invariants (particularly, the topological charge) in preventing certain types of instabilities and ensuring the long-term persistence of solitons
M-matrices and one-dimensional discrete Sturm–Liouville problems with nonlocal boundary conditions
No full textThis article is the second part of a survey dedicated to M-matrices and the application of the finite difference method to elliptic problems with nonlocal boundary conditions. Here, we examine cases in which the matrix of the resulting system of linear equations is an M-matrix. Here, we address the discrete Sturm–Liouville problem with nonlocal boundary conditions, describing its spectrum in one-dimensional case. This enables us to determine the values of the nonlocality parameters for which the finite difference scheme is represented by an M-matrix