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This paper aims to examine the Brazilian stock market behavior and volatility term structure of two portfolios that, theoretically, the companies that comprise them have different degrees of idiosyncratic risk: one portfolio consists of firms with good corporate governance and the other comprises firms with poor corporate governance.

The sample comprises corporate firms listed in the Brazilian stock market during the period from January 2008 to December 2017. Generalized autoregressive conditional heteroskedasticity models were applied.

The results show that the portfolio of firms with good corporate governance practices presents fluctuations that are more often temporary and reactive, with trends’ persistence of shorter durations, when considering the punctual volatility of the parameters estimated. This opposed expectation that the portfolio comprised of companies with good governance practices are better protected from short-term movements. However, over time and with standard error measures in consideration, both portfolios’ volatilities behave in similar ways. These findings may be related to Brazilian market characteristics, such as ownership concentration, ineffective corporate boards and the ever-developing nature of the stock market in Brazil. Any one of these characteristics present challenges to effective enforcement of the corporate governance practices in the Brazilian context.

The findings are potentially to the interest of researchers and practitioners for several reasons. First, this paper contributes to the growing literature on the relationship between corporate governance and market volatility. Second, it informs that volatility in the Brazilian context is likely only partially, if at all, influenced by corporate governance practices. Third, longitudinally, both indices follow the same pattern and converge to the same place.

This study identified how investor sentiment on Twitter is associated with Brazilian stock market return and trading volume.

The study analyzes 314,864 tweets between January 1, 2017, to December 31, 2018, collected with the Tweepy library. The companies’ financial data were obtained from Refinitiv Eikon. Using the netnographic method, a Twitter Investor Sentiment Index (ISI) was constructed based on terms associated with the stocks. This Twitter sentiment was attributed through machine learning using the Google Cloud Natural Language API. The associations between Twitter sentiment and market performance were performed using quantile regressions and vector auto-regression (VAR) models, because the variables of interest are heterogeneous and non-normal, even as relationships can be dynamic.

In the contemporary period, the ISI is positively correlated with stock market returns, but negatively correlated with trading volume. The autoregressive analysis did not confirm the expectation of a dynamic relationship between sentiment and market variables. The quantile analysis showed that the ISI explains the stock market return, however, only at times of lower returns. It is possible to state that this effect is due to the informational content of the tweets (sentiment), and not to the volume of tweets.

The study presents unprecedented evidence for the Brazilian market that investor sentiment can be identified on Twitter, and that this sentiment can be useful for the formation of an investment strategy, especially in times of lower returns. These findings are original and relevant to market agents, such as investors, managers and regulators, as they can be used to obtain abnormal returns.

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 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.

This study aims to analyze the influence of future expectations of the book-to-market ratio (B/M) and return on equity (ROE) in explaining the Brazilian capital market returns.

The study analyzed the explanatory power of risk-factor approach variables such as beta, size, B/M ratio, momentum and liquidity.

The results show that future expectations of the B/M ratio and ROE, when combined with proxies for risk factors, were able to explain part of the variations of Brazilian stock returns. With respect to risk factors approach variables, the authors verified the existence of size and B/M effects and a liquidity premium in the Brazilian capital market, during the period analyzed.

This research was limited to the non-financial companies with shares traded at Brasil, Bolsa and Balcão, from January 1, 1995 to June 30, 2015. This way, the conclusions reached are limited to the sample used herein.

The evidences herein presented can also contribute to establishing investment strategies, considering that the B/M ratio may be calculated through accounting information announced by companies. Besides, using historical data enable investors, in a specific year, to calculate the predictor variables for the B/M ratio and ROE in the next year, which enhance the explanatory power of the current B/M, when combined in the form of an aggregate predictor variable for stock returns.

The main contribution of this study to the literature is to demonstrate how the expected future B/M ratio and ROE may improve the explanatory capacity of the stock return, when compared with the variables traditionally studied in the literature.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

Investors label high (low) book-to-market (B/M) firms as value (growth) companies. The conventional wisdom supports that growth stocks grow faster than the value ones, creating greater shareholder value. The Purpose of this paper is to analyze how stocks of growth and value companies create value for their shareholders in Brazil, compared to the USA market. For this, the authors analyze three dimensions of return.

First, the authors perform portfolios to analyze the growth rates of shareholders’ return. Then, the authors perform regressions to study the explanatory power of the B/M in growth. The data come from Thomson Reuters Eikon database and the Brazilian Institute of Geography and Statistics. The authors select all non-financial firms with available data from 1997 to 2017.

The profitability of growth firms is higher than the value ones, in almost every year after the portfolios’ formation, with little variation. Contrary to the findings for the US market, growth companies in Brazil show higher dividend growth than value companies.

It is possible that the database does not contain complete and entirely reliable accounting data, which may partially affect the results.

The findings contradict those exposed in the USA. The implications are the inverse of the US study: the duration-based explanation could be a vital factor for the value premium in the Brazilian stock market. Also, the findings support the standard valuation techniques and help the growth rates estimation in the valuation process (top-down approach).

This study is the first to compare the profitability and dividend growth of growth/value stocks in the Brazilian market. Overall, growth stocks have considerable profitability, and dividend growth compared to value stocks.

This paper analyzes alternative performance evaluation models applied to equity mutual funds under conditional and unconditional approaches in the Brazilian market.

The analysis is conducted using CAPM's single factor, Fama–French three and five factors, under their conditional and unconditional versions in a sample of 896 equity mutual funds from 2008 to 2019.

The results suggest that the use of three- or five-factor models is especially relevant to reduce the effect of market anomalies in performance assessment. Additionally, results show that conditional approaches, adding time-varying alphas and betas with macroeconomic variables, provide higher explanatory power than their unconditional peers.

The results are relevant in the unique economic environment characterized by historically high interest rate and high market volatility.

This chapter simultaneously investigates the most important calendar anomalies in stock returns: day of the week, turn of the month, turn of the year and holiday periods, in four of the most important Latin American stock markets: Argentina, Brazil, Mexico and Chile. Previous evidence available for these countries is very limited. Our results indicate that the three markets show a rather similar pattern regarding return seasonality. A day of the week effect, consisting in negative returns on Mondays, is reported for all the stock markets but the Mexican. The turn of the year effect is observed only in Argentina, and moderate holiday and turn of the month effects are reported in the Brazilian and the Mexican markets, respectively. In addition, significant levels of first-order return autocorrelation are reported for the four stock markets. The contemporary financial crisis has dramatically affected the behaviour of stock prices worldwide, causing, among other effects, a huge increase in price volatility and probably changing the behaviour of participants in financial markets. We have also investigated to what extent our results have been affected by the current abnormal situation.

Corporate social responsibility (CSR) and corporate sustainability have gained prominence in the major capital markets. In Brazil, the São Paulo Stock Exchange (BM&FBovespa) has created the Corporate Sustainability Index (ISE) and the Carbon Efficient Index (ICO2), responsible for indicating the performance of sustainable companies. Therefore, this study proposes to examine and compare the stock returns of the sustainability index member companies with the returns of companies out of these indexes. In this methodology we selected the two principal negotiability indexes of that market (IBOV and IBrX50), which are indexes that meet the most traded stocks of BM&FBovespa, and calculated the average daily returns of the four indexes in order to make performance comparisons over the period 2005–2014, based on nonparametric statistical tests. Our findings indicate that the average returns of sustainability indexes were higher, but these differences were not statistically significant, confirming previous evidence. Additionally, by means of a cointegration test, we found that the indexes are cointegrated in the long term. These findings are limited to the analyzed emerging market and are also subject to the limitations of the estimated models. Thus, we can infer that presence in the sustainability indexes does not indicate statistically significant higher returns, which means that companies with sustainable practices in Brazil are not only concerned with economic performance, but also with social, cultural, and environmental issues. The main findings are aligned with the concept of triple bottom line, even in the case of an emerging market.