Leonardo Badea

This study examines how literature has conceptualized and structured the relationship between capital-market-based finance and SME financing in Europe. The analysis combines systematic literature review with bibliometric mapping, using a dataset extracted from the Web of Science database. Following a structured search and screening process, 328 records were retained for bibliometric analysis, while 59 studies were selected for qualitative synthesis based on their relevance to SME finance, credit access and financing constraints. The results show that the field is interdisciplinary and positioned at the intersection of finance, economics, entrepreneurship, innovation, sustainability and European institutional studies. The qualitative synthesis indicates that capital-market-based finance is not treated as a substitute for bank lending, but as a complementary component of a broader SME financing architecture. Bibliometric results reveal distinct thematic clusters related to SME access to finance, credit-market imperfections, equity finance, venture capital, capital structure and alternative financing instruments. Citation and co-citation networks show that the field is built on several intellectual foundations, including trade credit, internal finance, information asymmetry, financial intermediation, innovation finance and entrepreneurial finance. The country citation network confirms the visible contribution of European research and its connection with bank dependence, market fragmentation and the policy rationale of the Capital Markets Union. A short projection of publication activity suggests that scientific interest in this topic is likely to remain active in the medium term. The findings also contribute to financial analysis by showing that SME access to market-oriented instruments depends on firm transparency, investor readiness, market depth and institutional integration.

This paper explores the relative stock market performance of well-diversified gender equality equity indices in comparison with the overall market, taking both a cross-sectoral and a financial sector approach, for the period January 2017 to March 2020, with a sample of 11 indices and 834 daily observations, and using several different statistical and econometric methods. Our results show a high level of dynamic conditional correlation of daily returns among the gender equality and the overall indices. We also found comparable levels of conditional volatility (resulting from an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH)model) and an elevated degree of synchronization of the volatility regimes (identified by a Markov switching model). Calibrating simple linear quantile regressions, we found that the value of the slope coefficients of the hypothetical linear relationship between the gender equality indices and the overall market indices are close to one, and relatively stable in relation with the value of the quantile. Using separate Vector Autoregressive (VAR) models for the cross-sectoral indices and for the financial sector indices, we found only very little evidence of causality and spill-over effects. Based on these results, we argue that the daily returns of the gender equality indices exhibited very similar characteristics with the daily returns of the overall market indices. In our interpretation, this could mean that, limited to our sample and methods of investigation, there were not significant differences in the investors’ preferences towards the equity issued by public companies committed to supporting gender equality, in comparison with their approach towards listed equity in general. It could also mean that investors do not yet anticipate the significantly different financial performance of listed companies stemming from their approach towards gender equality.

This paper explores the sensitivity of Romanian collective investment undertakings’ returns to changes in equity, fixed income and foreign exchange market returns. We use a sample of 80 open-end investment funds and pension funds with daily returns between 2016 and 2018. Our methodology consists of measuring changes in the daily conditional volatility for the fund returns (EGARCH) and changes in their conditional correlation with selected market risk factors (DCC MV-GARCH) throughout different volatility regimes identified using a Markov Regime Switching model. We argue that, on average, the level of conditional correlations between funds and market risk factors remained stable and unconcerned by the volatility regimes. In addition, for only less than half of the funds in the sample, their volatility regimes were synchronized with those of the selected market risk factors. We found that, on average, fund returns are more correlated with equity returns and less correlated with changes in local bond yields, while not being significantly influenced by changes in foreign bond yields or changes in foreign exchange. During the period investigated equity returns were the most volatile while the funds returns volatility were, on average, much more reduced. Overall, our results show the resilience of the Romanian collective investment sector to the selected market risk factors, during the investigated period.

One of the most significant problems in economic domain is the dispose of human preference and choice forecasting. Recently, the economists have focused their researches to use the fuzzy concepts and the artificial learning procedures in the theory of economic choice. This paper extends the work done in this direction and offers a new algorithm for finding the matrix representation of the fuzzy binary relation which describes a preference relation.