(1) Background: Since the current crises that has inevitably impacted the financial market, market prediction has become more crucial than ever. The question of how risk managers can more accurately predict the evolution of their portfolio, while taking into consideration systemic risks brought on by a systemic crisis, is raised by the low rate of success of portfolio risk-management models. Sentiment analysis on natural language sentences can increase the accuracy of market prediction because financial markets are influenced by investor sentiments. Many investors also base their decisions on information taken from newspapers or on their instincts. (2) Methods: In this paper, we aim to highlight how sentiment analysis can improve the accuracy of regression models when predicting the evolution of the opening prices of some selected stocks. We aim to accomplish this by comparing the results and accuracy of two cases of market prediction using regression models with and without market news sentiment analysis. (3) Results: It is shown that the nonlinear autoregression model improves its goodness of fit when sentiment analysis is used as an exogenous factor. Furthermore, the results show that the polynomial autoregressions fit better than the linear ones. (4) Conclusions: Using the sentiment score for market modelling, significant improvements in the performance of linear autoregressions are showcased.

Purpose: This study investigates the influence of economic conditions, healthcare system capacity, and health-related variables on the proportion of the older adult population (Population ages 65 and above) in European Union countries. It aims to identify how factors such as GDP, unemployment, inflation, healthcare expenditure, hospital bed availability, and the prevalence of chronic diseases impact the aging demographic.Methods: This study explores the dynamic interactions and temporal relationships between economic stability, healthcare capacity, chronic disease prevalence, and demographic aging patterns. The research employs a mixed-method approach, utilizing System GMM and wavelet coherence analysis on panel data from 27 EU countries between 2000 and 2021.Results: The findings reveal significant positive associations between economic prosperity and healthcare resources with the size of the older adult population. Increased GDP, efficient healthcare spending, and hospital bed availability are positively correlated with a larger older adult demographic. In contrast, high unemployment and inflation are linked to negative outcomes for the older adult population, reducing available resources and access to healthcare. Wavelet coherence analysis further uncovers how fluctuations in the prevalence of chronic diseases influence aging trends across different periods and frequencies.Conclusion: The study highlights the importance of integrated economic and healthcare policies to support the growing older adult population. Ensuring economic stability, enhancing healthcare infrastructure, and effectively managing chronic diseases are essential for improving quality of life and promoting sustainable aging in EU societies.

(1) Background: In the field of creativity studies there is always space for expansion and new conceptualizations of the methods involved. Therefore, we will present in this paper a brief arrangement of the methods used to enhance creativity and consider whether visual mnemonic devices can increase creativity. The devices are used in the teaching process in order to ease the remembering process by creating a visual representation. Visual mnemonic devices are techniques that increase creativity as part of their own performance. (2) Methods: We will use a quasi-experimental, nonequivalent group design, the procedure involving the use of visual mnemonic devices. (3) Results: The results show that the degree of abstracting increased after using visual mnemonic devices, along with fluency and other creativity dimensions. (4) Conclusions: The paper shows that the creativity increased, based on a national percentile system (along with standard creativity index), after using the visual mnemonics devices, thus demonstrating a case for integrating the visual mnemonic devices among methods to foster creativity.

This study explores the potential of data science software solutions like Customer Relationship Management Software (CRM) for increasing the revenue generation of businesses. We focused on those businesses in the accommodation and food service sector across the European Union (EU). The investigation is contextualized within the rising trend of data-driven decision-making, examining the potential correlation between data science applications and business revenues. By employing a comprehensive evaluation of Eurostat datasets from 2014 to 2021, we used both univariate and multivariate analyses, assessing the percentage of companies that have e-commerce sales across the EU countries, focusing on the usage of big data analytics from any source and the use of CRM tools for marketing purposes or other activities. Big data utilization showed a clear, positive relationship with enhanced e-commerce sales. However, CRM tools exhibited a dualistic impact: while their use in marketing showed no significant effect on sales, their application in non-marketing functions had negative effects on sales. These findings underscore the potential role of CRM and data science solutions in enhancing business performance in the EU’s accommodation and food service industry.

This study investigates the complex interplay between public sentiment, as captured through news titles and descriptions, and the stock prices of three major tech companies: Microsoft (MSFT), Tesla (TSLA), and Apple (AAPL). Leveraging advanced analytical methods including Pearson correlation, wavelet coherence, and regression analysis, this research probes the degree to which stock-price fluctuations can be attributed to the polarity of media sentiment. The methodology combines statistical techniques to assess sentiment’s predictive power for stock opening and closing prices, while wavelet coherence analysis unveils the temporal dynamics of these relationships. The results demonstrate a significant correlation between sentiment polarity and stock prices, with description polarity affecting Microsoft’s opening prices, title polarity influencing Tesla’s opening prices, and a positive impact of title polarity on Apple’s closing prices. However, Tesla’s stock showed no significant coherence, indicating a potential divergence in how sentiment affects stock behavior across companies. The study highlights the importance of sentiment analysis in forecasting stock-market trends, revealing not only direct correlations but also lagged influences on stock prices. Despite its focus on large-cap tech firms, this research provides a foundational understanding of sentiment’s financial implications, suggesting further investigation into smaller firms and other market sectors.

In the economic growth models, technological progress is either exogenous or endogenous. The endogenized theory is based on analytical modeling of the economic process in order to include the event of innovating. Theory around the subject innovation and economic growth also includes several independent parameters that have a strong impact over innovation. However, few of them established creativity as an independent parameter of innovation. The present paper aims to extend the endogenized theory in order to include creativity as an independent parameter of innovation, based on the evidence of a panel data of 28 countries, through 8 years. A theoretical model, a multiple linear regression, an ANOVA analysis and correlational matrixes were used in order to fulfill our purpose. Results show that innovation is determined by the level of knowledge twice as much as the level of creativity. A conceptual framework for an extension of endogenous growth models, in order to include creativity, is presented in the paper. The model can enhance economic growth by fostering creativity or knowledge and thus, the size of innovation, which is the main driver for economic growth in the model presented.