Banks represent important subjects in business, with dominant positions in the financial system in the world. Banks developed various financial products and services that can cover most market needs. As a result of adequate portfolio diversifications, banks recorded positive profitability rates. In addition to being adjusted to competition, banks should also focus on the environment. Therefore, banks have recognized an opportunity to offer green products and services and support environmentally-friendly initiatives and projects. The aim of this paper is to identify whether crucial determinants of bank profitability are moderated by the presence of green loans in the bank portfolio. For this purpose, a panel fixed-effects approach was applied to data from the Republic of Serbia (2014–2021). The obtained results indicate that the presence of green loans in a bank’s portfolio moderates the influences of a bank’s liquidity on the bank’s profitability measured by return on assets (ROA) and return on equity (ROE). The contribution of the conducted research is that it is, according to the authors’ knowledge, the first measurement and estimation of the moderating effects of green loans’ presence in banks’ portfolios on their profitability. In addition to financial, marketing implications were considered.

In this paper various topics related to programming, statistics and financial modelling were addressed with the main idea of establishing a trading strategy. As discussed in the paper, no research has been done on this topic. On the other hand, much research has been done on which model is better, which distribution or confidence level is more appropriate or provides better forecasting capabilities. No one has investigated whether these differences could lead to a development of trading strategy. The paper starts with a definition of the gap in literature and practice. Then the research methodology is outlined in detail. Formulas and parameters are defined and presented. The main conclusion of this paper is the importance of GARCH VaR and the possibility of creating trading strategies. As long as the difference between the GARCH VaR and the other two VaRs does not exceed 1.5%, there is no need to leave the market. Should this situation change, one should leave the market as long as these differences do not fall below 1.50%.

One of the basic types of portfolio valuation as well as valuation of individual company shares is the CAPM (Capital Asset Pricing) model, which uses a well-known measure of systemic risk in its analysis, which is beta. The CAPM model in its analysis uses the link between the systemic risk measure (beta) and the expected market return. Guided by this model, the analysis of monthly returns of selected shares on the Belgrade Stock Exchange in the period from 2011 to 2021 was performed in this research. In the research, the beta coefficient of selected shares was calculated with the help of the covariance of market return and stock return. The results and their statistical value were confirmed by the linear regression test. The rest of the research tests the applicability of the CAPM model to selected actions and in the same way, the SML (security market line) is devised, which is a graphical representation of the model. The research indicated that the basic assumptions of the CAPM model are not applicable as a predictor of future expected returns of selected shares on the Belgrade Stock Exchange due to various other elements that affect price movements and returns of selected shares not covered by the model.

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Value added tax is a significant tax form worldwide. The importance of this tax is manifested in the scope, stability and efficiency of revenue collection. With respect to macroeconomic conditions and challenges, fiscal authorities have to pay attention to the elasticity of VAT revenues. The paper is aimed at identifying VAT elasticity in the Benelux countries, as well as determining the main macroeconomic factors that affect the changes in VAT elasticity. Empirical results have shown the presence of VAT elasticity in the Benelux countries, as well as a statistically significant impact of gross domestic product, final consumption, unemployment, inflation, government expenditures and standard VAT rate on VAT elasticity for the period 2011-2022.