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The purpose of this paper is to investigate whether the relationship of interdependence and contagion between BRICS countries and emerging non-BRICS countries is similar to that observed between developed countries and emerging BRICS countries.

The authors analyzed 15 markets: 5 BRICS, 5 developed (USA, Japan, Germany, England and France) and 5 emerging markets (Mexico, Indonesia, Turkey, Iran and Poland). Based on the time series of returns of the main stock indexes of each country, referring to the period from 2008 to 2018, the authors applied Granger causality tests, vector auto-regression and the dynamic conditional correlation-GARCH model.

The results led to the rejection of the main hypothesis and showed adherence to the behaviors predicted in the literature for the relations between the groups of markets.

This paper, besides analyzing the interdependence between markets in times of crisis, analyzes the effect of contagion between developed and emerging markets.

This paper aims to identify if there is an impact of the rating announcements issued by the agencies on the returns of the stocks of Brazilian companies listed on Brasil Bolsa Balcão, from August 2002 to August 2018, identifying which types of announcement (upgrade, downgrade or the same initial classification) cause variations in prices around the date of disclosure of the rating.

The event study methodology was applied to verify the market reaction around the announcement dates in a 21-day event window (−10, +10). The market model was used to calculate the abnormal returns (ARs), and subsequently, the accumulated ARs.

The hypotheses tests allowed to verify that the accumulated ARs are different, before and after the three types of rating announcements (upgrades, downgrades and the same classification); in upgrades, the mean of accumulated ARs increases in the days before the event, while in downgrades, this increase occurs after the event. This paper concluded that the rating announcements have an impact on the return of stock of the Brazilian market and that the market reaction occurs most of the time before the event happens, which indicates that the market can anticipate the information contained in the changes in credit ratings.

The results have considerable implications for portfolio managers, institutional investors and traders. It facilitates investment decision-making in the face of rating classification announcements. Market participants can pay more attention to their investment strategies and asset allocation during periods of risk rating announcements. Additionally, traders can understand the form of investment strategy for superior earnings.

The importance of the study is related to the fact that the results may explain the causes of specific movements in the Brazilian financial market related to a source of information that may or may not be able to influence the decisions of the financial agents that operate in this market. The justification is centred on the idea that, for investors who somehow react to the announcements, it is relevant to understand the impact of rating classifications on companies, as access to such information allows for more conscious decision-making.

Higher education institutions (HEIs) should assume their role as leaders in the search for a sustainable future. Consequently, such institutions need to incorporate sustainability into their activities. However, this needs to be done holistically and not with isolated and independent actions. Therefore, this study aims to develop a structure of sustainability action archetypes to help HEIs holistically incorporate sustainability in their strategies.

A systematic review of the literature was conducted focusing on the subject of sustainability in HEIs.

A structure of sustainability action archetypes for HEIs was proposed. Further, based on scientific literature, examples of actions were presented within each archetype.

This study provides HEI administrators and other organizations with a practical structure to enable the systemic incorporation of sustainability objectives and actions into institutional activities.

This study adapts the tool “sustainable business model archetypes” for a new purpose. This tool was initially developed to classify innovations of sustainable business models.

Higher education institutions (HEIs) must take on a leadership role in building a sustainable world, given their responsibility for preparing future professionals and leaders worldwide and considering the role they provide to society. To accomplish this goal, HEIs need to holistically embody sustainability in everything they develop. This study aims to help HEIs in this purpose by developing a method to integrate sustainability into the strategic planning process in these institutions.

In the first stage, the method was developed based on papers selected through a systematic literature review. The proposed method was then applied in a Brazilian HEI to validate and adjust it.

A method that adopts a participatory process to integrate sustainability into HEIs’ strategic planning was proposed.

This study provides university leaders with a simple and practical method to aid with elaborating on strategic plans for holistic sustainability integration.

This study uniquely applied a framework called “HEIs sustainability action archetypes” as the foundation for selecting sustainable objectives, goals and actions to be integrated into these institutions’ strategic planning.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

This study investigates the impacts of the Russia–Ukraine conflict on the cross-correlation between agricultural commodity prices and crude oil prices.

The authors used MultiFractal Detrended Fluctuation Cross-Correlation Analysis (MF-X-DFA) to explore the correlation behavior before and during conflict. The authors analyzed the price connections between future prices for crude oil and agricultural commodities. Data consists of daily futures price returns for agricultural commodities (Corn, Soybean and Wheat) and Crude Oil (Brent) traded on the Chicago Mercantile Exchange from Aug 3, 2020, to July 29, 2022.

The results suggest that cross-correlation behavior changed after the conflict. The multifractal behavior was observed in the cross correlations. The Russia–Ukraine conflict caused an increase in the series' fractal strength. The study findings showed that the correlations involving the wheat market were higher and anti-persistent behavior was observed.

The study was limited by the number of observations after the Russia–Ukraine conflict.

This study contributes to the literature that investigates the impact of the Russia–Ukraine conflict on the financial market. As this is a recent event, as far as we know, we did not find another study that investigated cross-correlation in agricultural commodities using multifractal analysis.

This study aims to investigate the occurrence of the decoy effect in stock investment decisions based on fundamental analysis.

In this study, the decoy effect was investigated by applying two questionnaires, one of them with the presence of a decoy alternative, to a set of 224 respondents with knowledge of business fundamentals, simulating investment decisions in stocks of companies listed on the Brazilian Stock Exchange. The data analysis was performed using the Fisher's exact test, Student's t-test and ANOVA. The research also aimed to detect a potential relationship between the variables gender, age, degree and professional experience with the type of decision made.

The results pointed to the occurrence of the decoy effect when analysing the general response data. However, such evidence was not confirmed when the sample was analysed by classes (gender, course, age and professional experience). There is no statistical evidence that the decoy effect influences classes.

The recent decoy effect literature is little explored in investment decision-making. This study is unique in examining the decoy effect in investment decisions in the Brazilian context.

The purpose of this paper is to test if companies with a greater concentration of management ownership (and thus more risk-averse managers) avoid less tax.

The authors use a regression analysis with panel data, using as a sample of Brazilian companies from 2001 to 2015. The authors investigate the impact of insider ownership on tax avoidance, testing how and how much different ownership levels of inside owner are associated with tax avoidance measured by effective tax rates and book-tax differences.

The results indicate that different levels of management ownership are associated with different levels of tax avoidance behavior.

This paper contributes to the literature showing that ownership and decision making are not always focused on only a few decision makers. The owners are likely to be more risk averse and therefore less willing to invest in risky projects such as tax avoidance.

The purpose of this paper is to evaluate the predictive capacity of market risk estimation models in times of financial crises.

For this, value-at-risk (VaR) valuation models applied to the daily returns of portfolios composed of stock indexes of developed and emerging countries were tested. The Historical Simulation VaR model, multivariate ARCH models (BEKK, VECH and constant conditional correlation), artificial neural networks and copula functions were tested. The data sample refers to the periods of two international financial crises, the Asian Crisis of 1997, and the US Sub Prime Crisis of 2008.

The results pointed out that the multivariate ARCH models (VECH and BEKK) and Copula-Clayton had similar performance, with good adjustments in 100 percent of the tests. It was not possible to perceive significant differences between the adjustments for developed and emerging countries and of the crisis and normal periods, which was different to what was expected.

Previous studies focus on the estimation of VaR by a group of models. One of the contributions of this paper is to use several forms of estimation.