6 research outputs found

    EUROPEAN FISHERIES FUND – NEW DEVELOPMENT OPPORTUNITIES FOR ROMANIA

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    This article analyses the financial support given by the European Union to the member states on the purpose of enduring development of their fishing area, as well as the new development opportunities for Romania. The main financing instrument of the common fisheries policy is the European Fisheries Fund, which is managed alike the structural funds. This fund supports the European fisheries and aquaculture area in its effort to adapt a new fleet, whose competitiveness must be consolidated, and encourages the application of some measures meant to protect and improve the environment. In the case of Romania, the increase of the European Fisheries Fund’s absorption has become a priority for the Managing Authorities of this Fund, in order to stimulate the development of the Romanian market for fishing products, a market having a great potential

    Sustainable development goals and the triangle of ESG investments

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    The concept of sustainable development has had an enormous effect on the world in recent decades. A company’s economic activities need to be organized in a way that takes into account how they will affect society, the environment, and corporate governance standards (ESG). This is what sustainable development means. One of the key trends in the growth of the international business community has been the ESG approach. Many people assert that the financial sector is the engine that drives behind ESG because of its goals to protect the environment, the general public, and to promote responsible investment. The Sustainable Development Goals (SDGs) and their recent evolution are explained in this article using a qualitative research methodology. We’ll also demonstrate how the 17 goals are intended to guide society’s cautious development. We will contrast the first 10 sustainability-focused funds available on the market in light of the evidence that financial instruments have emerged on the market to enable businesses to undertake an ESG transformation more easily. At the same time, using the SDG indicators from the European Union, can compare the period before and during COVID 19. In this particular case, the primary focus will be on their contribution to the acceptance of the idea of sustainable development as well as their importance in the development of ESG principles affected by pandemics. The paper concentrates on the dependency between SDGs and ESG in light of the expanding significance of the sustainable development concept

    Detecting financial sustainability risk of the assets using MAMDANI fuzzy controller

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    The paper aims to develop a MAMDANI fuzzy controller for detecting the financial sustainability risk of the assets owned by the company. This type of risk indicates when an asset no longer produces economic benefits to the company, or the benefits are small enough to no longer justify the asset maintaining in working order. The proposed fuzzy controller has as input variables the asset operating expenses and the variation of this category of expenses from one analysis period to another. The controller's objective function is to keep operating costs at their initial state and thus reducing the financial sustainability risk. The controller's output variable is represented by the economic benefits variation, considered to be an essential component in the financial sustainability risk analysis. The obtained results were interpreted taking into account the objective function of the controller as well as the evolution of the input variables. Two simulations for fuzzy controllers were made, with the mention that the variation ranges for the input variables were delimited. In practice, fuzzy controllers can be generated according to company policies to keep under control the expense categories that accompany the asset exploitation

    European Fisheries Fund – New Development Opportunities For Romania

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    This article analyses the financial support given by the European Union to the member states on the purpose of enduring development of their fishing area, as well as the new development opportunities for Romania. The main financing instrument of the common fisheries policy is the European Fisheries Fund, which is managed alike the structural funds. This fund supports the European fisheries and aquaculture area in its effort to adapt a new fleet, whose competitiveness must be consolidated, and encourages the application of some measures meant to protect and improve the environment. In the case of Romania, the increase of the European Fisheries Fund’s absorption has become a priority for the Managing Authorities of this Fund, in order to stimulate the development of the Romanian market for fishing products, a market having a great potential.fishing, aquaculture, enduring development, European fisheries fund, financial allowances

    Composite financial performance index prediction – a neural networks approach

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    Financial indicators are the most used variables in measuring the business performance of companies, signaling about the financial position, comprehensive income, and other significant reporting aspects. In a competitive environment, the performance measurement model allows performing comparative analysis in the same industry and between industries. This paper aims to design a composite financial index to determine the financial performance of listed companies, further used in predicting business performance through neural networks. Principal components analysis was used to build a composite financial index, employing four traditional accounting indicators and four value-based indicators for the period 2011–2018. Five experiments were conducted to predict business performance through the composite financial index. The results showed that observations from two years, of the first three experiments, indicate a better predictive behavior than the same experiments using observations from one year. Therefore, we concluded that observations from more than one year are necessary to predict the value of the financial performance index. Findings led us to the conclusion that recurrent neural networks model predicted better financial performance composite index when taken into consideration more real data for the financial performance index (2012–2018) instead of just for one year (2018)

    Analyzing Financial Health of the SMES Listed in the AERO Market of Bucharest Stock Exchange Using Principal Component Analysis

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    In this paper we aimed to build a composite financial index for measuring the financial health of the companies listed in the AERO (Alternative exchange in Romania) market of the Bucharest Stock Exchange. We used a principal component analysis in order to build this composite financial index using the rates of return, liquidity and the management of 25 companies listed in the AERO market for the period 2011–2018. We conceived this composite indicator as a score function that established according to the numerical values that result from its application when a company was financially healthy, when it had a poor financial health and when it was financially stable. In order to test the financial health of the selected SMEs (small and medium enterprises), we used the one sample t-test under the model of the study and the three classifications of Z (Z < 0—companies with poor financial health, 0 ≤ Z ≤ 0.5—companies with good financial health and Z > 0.5—companies with very good financial health). In this study we also aimed to identify the possible correlations between the solvency rate and the financial health index and between solvency rate and the evolution of some economic and financial measures of the companies’ activities. The results of the regression analysis using panel data showed a positive and statistically significant relation between solvency and the three rates (rates of return, of liquidity and of management, respectively) determined using the analysis of the principal components. The former model of the solvency rate identified correctly 94.9% of the SMEs with poor financial health, 40% of the SMEs with stable financial health and 72.2% of the SMEs with good financial health
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