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This study aims to examine the performance of environmental, social and governance (ESG) equity indices in Latin America (LA), evaluating their risk-return characteristics in comparison to conventional benchmark indices.

Using a quantitative empirical approach, the authors analyze ESG equity indices from Brazil, Mexico, Chile, Peru and Colombia, employing metrics such as Sharpe, Sortino and Omega ratios to measure risk-adjusted returns. Regression analysis is employed to assess the replicability of ESG indices by benchmark indices. Monte Carlo simulations are conducted to explore the potential increase in risk-adjusted returns when ESG equity indices are incorporated into portfolios.

The study addresses critical questions for investors: Can ESG indices outperform their benchmarks? Can these ESG indices be replicated by benchmark counterparts? Do ESG equity indices enhance portfolio diversification? The findings reveal that investing in ESG indices has the potential to enhance risk-adjusted returns and portfolio diversification.

While this study focuses on various LA economies, it’s important to note variations in currency and volatility.

For investors in LA, this study highlights the importance of considering ESG indices as part of their investment strategies. While not all ESG indices outperform conventional ones, some may improve diversification and risk-adjusted performance. Investors should carefully assess market-specific conditions and national factors when making investment decisions.

The primary contribution of this study is its focus on LA countries in the examination of diverse portfolios. The research provides valuable insights into the performance of ESG indices in this region compared to conventional benchmark indices. This approach addresses an important gap in the existing literature and offers a more comprehensive perspective on ESG investing and portfolio diversification.

Se examina el rendimiento de los índices-ESG en América Latina (AL), evaluando sus características de riesgo y retorno en comparación con los índices convencionales.

Utilizando un enfoque cuantitativo, analizamos los índices-ESG de Brasil, México, Chile, Perú y Colombia, empleando ratios de Sharpe, Sortino y Omega para medir los rendimientos ajustados al riesgo. Se utiliza análisis de regresión para evaluar la replicabilidad de los índices-ESG por parte de los índices de referencia. Se realizan simulaciones de Monte-Carlo para explorar el aumento en los rendimientos ajustados al riesgo cuando se incorporan los índices-ESG en las carteras.

El estudio aborda preguntas críticas: ¿Pueden los índices-ESG superar a sus índices de referencia? ¿Pueden estos índices-ESG ser replicados por sus contrapartes de referencia? ¿Mejoran los índices-ESG la diversificación de las carteras? Los hallazgos revelan que la inversión en índices-ESG tiene el potential de mejorar los rendimientos y la diversificación de las carteras de inversión.

Aunque este estudio se centra en diversas economías de AL, es importante tener en cuenta variaciones en moneda y volatilidad.

La principal contribución de este estudio radica en su enfoque en países de AL en el examen de carteras diversas; ofrece valiosos conocimientos sobre el rendimiento de los índices-ESG en esta región en comparación con los índices convencionales.

The purpose of this study is to construct the first short-term financial distress prediction model for the Spanish banking sector.

The concept of financial distress covers a range of different types of financial problems, in addition to bankruptcy, which is not common in the sector. The methodology used to predict financial problems was artificial neural networks using traditional financial variables according to the capital, assets, management, earnings, liquidity and sensibility system, as well as a series of macroeconomic variables, the impact of which has been proven in a number of studies.

The results obtained show that artificial neural networks are a highly suitable method for studying financial distress in Spanish credit institutions and for predicting all cases in which an entity has short-term financial problems.

This is the first work that tries to build a model of artificial neural networks to predict the financial distress in the Spanish banking system, grouping under the concept of financial distress, apart from bankruptcy, other financial problems that affect the viability of these entities.

The objective of this study is to review the main studies of social entrepreneurship (SE) in Latin America, to categorize them into four categories. To accomplish this, a bibliometric literature review is carried out based on data from the Web of Science database, to locate the Latin American collection of studies. In this way, the main studies are described and grouped, following a qualitative scheme that allows to substantiate the main findings of the Latin authors. Consequently, the progress made in the literature of the SE for Latin America is corroborated, by visualizing that the SE turns out to be a forceful fact to manage well-being, but that it is faced with an inconsistent development.