Brazilian Stock Research Articles

Dynamic Connectivity and Contagion Risk Among Bank Stocks in Brazil

Dynamic Connectivity and Contagion Risk Among Bank Stocks in Brazil

The Impact of Dividend Payments on Stock Price: Empirical Evidence From Companies Listed on the Brazilian Stock Exchange

The Impact of Dividend Payments on Stock Price: Empirical Evidence From Companies Listed on the Brazilian Stock Exchange

Impact of Fiscal Policy on Corporate Innovation in an Emerging Market Economy: Evidence from Brazil

This study investigates the impact of fiscal policy on corporate innovation in an emerging market economy, focusing on Brazil. Utilizing a comprehensive dataset of firms listed on the B3 Brazilian Stock Exchange from 2010 to 2020, we employ panel data analysis and the difference-in-differences (DiD) method to examine the effects of tax incentives, government subsidies, and public investment in innovation infrastructure on corporate innovation activities. Our findings reveal that tax incentives significantly enhance innovation outputs by reducing the financial burden of R&D investments. Similarly, government subsidies are shown to lower the cost and risk associated with R&D projects, thereby fostering greater innovation. Furthermore, public investment in innovation infrastructure plays a crucial role in creating an enabling environment for corporate innovation. These results provide robust evidence supporting the effectiveness of fiscal policy in promoting innovation in emerging markets, offering valuable insights for policymakers aiming to foster sustainable economic growth and competitiveness.

Lottery stocks in Brazil: investigating risk premium and investor behavior

PurposeThis study investigates the paradox of lotteries in financial markets, challenging traditional utility models predicated on rational behavior amid uncertainty. It explores why investors are drawn to lotteries despite the potential trade-off between risk-adjusted returns and sporadically substantial gains.Design/methodology/approachEmploying a multifaceted approach, the study first scrutinizes diverse theories elucidating the perplexing behavior of lottery investors. Subsequently, it assesses the premium attached to lottery stock shares in the Brazilian financial market using distinct methodologies, thereby offering a comprehensive analysis of this phenomenon. Finally, the study estimates the risk premium associated with the lottery stocks applying an extended Fama–French multifactor model and searching for evidence of overlap with other risk-based anomalies.FindingsThis research unveils theories underpinning seemingly irrational investor behavior vis-à-vis lotteries, revealing the motivations propelling investors to willingly exchange risk-adjusted returns for the allure of substantial but infrequent gains. Empirical evidence delineates the extent of the premium paid for lottery stocks in the Brazilian market.Originality/valueThe study’s novelty lies in its amalgamation of theoretical exploration, empirical analysis and the application of the Fama–French factor model to gauge the risk premium associated with lottery-related behavior. Furthermore, its investigation of lottery stocks within the Brazilian market introduces a distinctive dimension, elucidating market dynamics and investor behaviors unique to the region.

Portfolio resampling in the Brazilian stock market

Markowitz optimization plays a crucial role in modern portfolio theory. However, it is well known that Markowitz optimization is highly affected by estimation errors in the mean vector and covariance matrix, resulting in extreme and/or unrealistic portfolio weights, lack of diversification, and poor out-of-sample performance. In response to these challenges, Michaud and Michaud (1998) proposed a heuristic portfolio resampling approach aimed to deliver more diversified and better out-of-sample portfolio performance. This approach has received both criticism and praise among academics and practitioners, with the main critique being the unclear economic benefits of applying this method to empirical data. To contribute to this ongoing debate, our study assess the performance of the Michaud and Michaud (1998) portfolio resampling approach using data from the Brazilian stock market. Additionally, we evaluate whether a resampling approach based on factor structure can yield superior out-of-sample performance. Our findings indicate no evidence of superiority over Markowitz optimization, reinforcing criticisms of the portfolio resampling approach.

Global Financial Factors and the COVID-19 Pandemic: What Drove the Degree of (In)Efficiency of the Brazilian Stock Market in the Recent Period?

Global Financial Factors and the COVID-19 Pandemic: What Drove the Degree of (In)Efficiency of the Brazilian Stock Market in the Recent Period?

Evolution and Challenges of Environmental, Social, and Governance Practices: An Analysis of the Brazilian Stock Exchange’s Corporate Sustainability Index

Environmental, social, and governance (ESG) practices are increasingly recognized as critical for corporate sustainability and market competitiveness, driven by heightened expectations from investors, governments, and consumers. This study examines the evolution of ESG practices among companies listed on the Brazilian Stock Exchange’s Corporate Sustainability Index (ISE B3) from 2005 to 2022. We analyzed the index portfolio’s composition, focusing on changes in ESG dimensions over time. The only six long-lived companies in this index, from retail, banking, and energy sectors, were selected for in-depth analysis. We further evaluated the quality and consistency of ESG disclosures in company reports. Findings indicate relevant fluctuations in the number of companies included in the ISE B3 and variations in ESG scores for the companies. These variations may be attributed to the voluntary nature of ESG practices and the absence of standard disclosure. This study reveals a lack of homogeneity in ESG reporting, which could be addressed by establishing more straightforward guidelines and global standards. This research underscores Brazilian companies’ challenges navigating diverse ESG frameworks to align with evolving societal and environmental expectations.

Price Trend Forecasting in the Brazilian Stock Market using Discrete-Time Markov Chain

Price Trend Forecasting in the Brazilian Stock Market using Discrete-Time Markov Chain

ESG integration strategy with a multivariate normal distribution

Purpose: The paper aims to present a new framework for ESG integration strategies in portfolio optimization problems. The optimization in the new structure focuses on the portfolio level, and the procedure is not focused on utility functions or on preliminary weights applied to the asset level. It applies the resampling technique, and all the portfolios are optimal portfolios in the mean-variance space. It uses a filtering process where only optimal portfolios with lower ESG risks are considered. Therefore, this technique works only with optimized portfolios, avoids concentration bias, and considers estimation errors in the expected returns and in the covariance matrix. Design/methodology/approach: The sample mean returns and covariance matrices generated by a multivariate normal distribution are applied in mean-variance optimization to generate several portfolios in the efficient frontiers. An ESG filtering process is used to select portfolios with lower ESG risks from a sample of 42 companies listed on the Brazilian stock exchange with returns from the period of 2018/01/01 to 2024/04/22.Findings: Integration strategy costs may be lower than the best-in-class strategy costs and may be similar to the costs of a negative screening strategy. Social implications: The paper presents a framework that considers social, environmental, and governance factors in the portfolio optimization process.Originality: The main contribution of this paper is to present a new framework that combines resampling of returns’ mean and covariance based on a multivariate normal distribution with an ESG portfolio filtering process.

Machine Learning for liquidity classification and its applications to portfolio selection

Liquidity refers to the ease of asset conversion into cash, playing a crucial role in investment decisions for achieving optimal returns. This study proposes a novel stock liquidity classification method using machine learning algorithms, trained, and tested on ten years of Brazilian stock market (B3) data. Achieving an accuracy of 99.2%, the classifier, when integrated with the mean-variance portfolio optimization model, reduces portfolio uncertainty by preventing an average of 11.5% of illiquid asset sales.

Machine Learning-Enhanced Pairs Trading

Forecasting returns in financial markets is notoriously challenging due to the resemblance of price changes to white noise. In this paper, we propose novel methods to address this challenge. Employing high-frequency Brazilian stock market data at one-minute granularity over a full year, we apply various statistical and machine learning algorithms, including ARIMA, Bidirectional Long Short-Term Memory (BiLSTM) with attention, Transformers, N-BEATS, N-HiTS, Convolutional Neural Networks (CNNs), and Temporal Convolutional Networks (TCNs) to predict changes in the price ratio of closely related stock pairs. Our findings indicate that a combination of reversion and machine learning-based forecasting methods yields the highest profit-per-trade. Additionally, by allowing the model to abstain from trading when the predicted magnitude of change is small, profits per trade can be further increased. Our proposed forecasting approach, utilizing a blend of methods, demonstrates superior accuracy compared to individual methods for high-frequency data.

Predicting the Brazilian Stock Market with Sentiment Analysis, Technical Indicators and Stock Prices: A Deep Learning Approach

Predicting the Brazilian Stock Market with Sentiment Analysis, Technical Indicators and Stock Prices: A Deep Learning Approach

Sociodemographic Profile of Blood Donations and Ways to Encourage Them.

Maintaining blood stocks in Brazil faces challenges; hence, it is crucial to develop effective strategies to recruit and retain donors, such as campaigns and social marketing programs to raise awareness, but there is a lack of studies about the donators' profiles, as well as their barriers or incentives. The objective of this study was to analyze the characteristics of donors and the factors that influence their decisions. This was a cross-sectional study carried out between April and November 2022 using a structured questionnaire sent through a community created on Facebook, addressing common people over 18 years old, containing closed questions, supported byGoogle Forms.Statistical analyses were carried out usingIBMSPSSStatistics for Windows, Version 17 (Released 2008; IBM Corp., Armonk, New York, United States) and the Chi-square and Fisher's exact tests, with p < 0.05. The sample relied on 1019 participants, women (72.8%), age group > 30 years (81.1%), the most represented blood type was O positive (37.5%), and men donated more frequently than women (76.5% vs. 40.6%). The main reasons for not donating are medical conditions (39.7%) and lack of time (33.8%). The main reasons for donating are helping voluntarily (97.6%) and donating to family/friends (96.4%). There was a significant difference between the genders of blood donors, with more men donating, especially those over 30 years old, and with income between 1-8 minimum wages. The main barriers to donating are lackof time and information. Based on this, it is possible to target campaigns at women, young people, and people with income above nine minimum wages. The main reasons for donating are altruism, obtaining test results, and financial benefits.

Oversight Mechanisms and the Reduction of Greenwashing

Purpose: This study aimed to identify oversight mechanisms that reduce greenwashing behavior. Method: Data come from Bloomberg and Refinitiv ESG scores of 88 Brazilian public companies listed on the Brazilian stock exchange B3 from 2010 to 2021. The estimation method was the FGLS (Feasible Generalized Least Squares). Result and Discussion: The results suggest the action of institutional investors, independent board members, and being an environmentally sensitive industry company can reduce greenwashing. However, a series of divergences in the results might indicate that the practice of greenwashing is due to unequal awareness and a developing regulatory framework. Research Implications: This study contributes to ESG policymakers, managers, and investors by exploiting oversight mechanisms to reduce greenwashing behavior and encourage companies' sustainable development. Originality/Value: ESG disclosure intentions and actions help stakeholders' decision-making process, especially investors, through sustainability reports. However, the unaudited content can be misleading by pointing out greenwashing behavior, which means what is said does not correspond to company actions. Such context is still to be intensely exploited, and that value to an extensive range of stakeholders.

Tax Litigation and Corporate Debt: A Brazilian Perspective

Objective: The study aims to explore the impact of tax litigation on the indebtedness levels of Brazilian firms. The research is motivated by Brazil's high volume of tax disputes and the lack of existing studies focusing on the relationship between tax litigation and firm indebtedness in this particular context.&#x0D; Method: The sample includes non-financial firms listed on the Brazilian stock exchange from 2017 to 2022. Linear regression methodology, utilizing panel data and fixed effects, was employed to analyze the relationship. Tax litigation was quantified by summing tax provisions and contingent liabilities, which were then relativized by the firms' total assets. Data were sourced from Comdinheiro software, with additional information manually gathered from company explanatory notes.&#x0D; Results or Discussion: The study found a positive relationship between tax litigation and firm indebtedness in Brazil. This suggests that companies involved in more tax disputes tend to have higher levels of debt, pointing towards a complex relationship between the two variables in the Brazilian economic landscape.&#x0D; Contributions: This research fills a gap in existing literature by investigating the effects of tax litigation on the capital structure of Brazilian firms. It provides valuable insights that can be beneficial for policymakers, regulatory bodies, and firms in understanding the implications of tax disputes on financial strategies.&#x0D;

The market`s (non) reaction to ministerial instability

This research analyzes the impact of the ministerial instability on the market value of Brazilian companies. We use a study of events to measure the abnormal returns of the companies in 26 events, covering the period from 2019 to 2022. The estimation window used was 252 previous returns to the event window. We select the 100 companies with the greatest participation in the Bovespa index, without considering holdings. Regarding abnormal returns, only two specific events stood out. Overall, at 90%, 95% and 99% confidence intervals, the results do not allow confirming or rejecting the hypothesis that the stock market reacted to ministerial instability during the government of Jair Bolsonaro. The lack of a relationship between the Brazilian stock market and politics reveals a possible disregard on the part of the market for and with the instabilities of public policies that may be promoted by ministerial instability.

INFLUENCE OF THE LEVEL OF TAX AGGRESSIVENESS ON THE PROFITABILITY OF PUBLICLY TRADED COMPANIES OF INDUSTRIAL GOODS LISTED ON B3

Tax aggressiveness represents the most advantageous legal method of taxation chosen by taxpayers, after exploring the ambiguities and uncertainties contained in the tax legislation. In this sense, this study aims to verify the influence of the tax aggressiveness level on the profitability of publicly traded companies of industrial goods listed on B3 (Brazilian Stock Market) in the period from 2010 to 2019. The information was collected in the Economatica@ database and 52 companies were analyzed by means of multiple and quantile regressions. The results pointed out, based on the mean functions of the MQO method, that the level of tax aggressiveness does not influence the profitability. However, when considering the conditional quantile functions of the MEA method, the GAAP ETR starts to present statistical significance and negative coefficient as expected for the Q50 and Q75 quintiles of NM (Net Margin), ROA (Return on Assets) and ROE (Return on Equity) and for the Q90 quintile of NM and ROA and then, the hypotheses H1a, H1b and H1d that the tax aggressiveness level positively influences the NM, the ROA and the ROE of the investigated companies are not rejected. Having said that, in general, it is concluded that the higher the tax aggressiveness the higher the profitability of the publicly traded companies of industrial goods listed on B3 and that, even with issues not fully resolved, the theme can be very useful for various users of accounting information, such as tax legislators, regulators, investors, company directors and academic researchers.

Price effects after one-day abnormal returns and crises in the stock markets

We investigate price effects after one-day abnormal returns during crises in US, Japanese, Chinese, Russian and Brazilian stock markets, using the ANOVA, Mann–Whitney, t-tests, the modified cumulative abnormal return approach, regression analysis with dummy variables, and the trading simulation approach. The results suggest that the momentum effect is the most typical case of price behaviour after the days with positive abnormal returns, especially in emerging markets in pre and post crisis periods. Interestingly the momentum effect in developed markets changes into contrarian during crisis periods. However, in emerging markets the momentum effect prevails even in crisis periods. However, the power of the detected effects is weak. These effects do not provide opportunities to beat the market and might result from prevailing positive returns in these stock markets.

The Impacts of the Interest Rate, the Exchange Rate, and the Market Index on the Stock Returns of the Brazilian Banks

Abstract This paper aims to analyze the impact of interest rate, exchange rate, and market on the returns and volatility of the stocks of banks listed on the Brazilian Stock Exchange. This analysis used two statistical models: the linear model estimated using Ordinary Least Squares and the ARCH/GARCH time series volatility models. The econometric studies considered the daily data of 15 financial institutions listed on the stock exchange during the period from January 2009 to December 2021. Regarding the market effect, the Ibovespa index for the period was considered; for the interest rate, the CDI (Certificate of Interbank Deposit) was used; and, about the exchange rate, the dollar rate was adopted as a reference. The results indicate that the distribution of stock returns is asymmetrical, with an elongated tail on the right. It was observed, based on the econometric model applied, that the daily returns of the shares are significantly influenced by the market, and the interest rate exerts the least impact on the returns. These findings are relevant to the scientific community exploring the topic and provide valuable insights for bankers, analysts, market investors, regulatory authorities, and society in the decision-making process. JEL classification numbers: C32, G00, G21. Keywords: Banking, Interest rates, Exchange rate, Bank stocks.

Effects of CPC 47 (IFRS 15) from the perspective of revenue management in the brazilian stock market

This study analyzed the effect of adopting CPC 47 (IFRS 15) for revenue recognition on the quality of accounting information from the perspective of revenue management in the Brazilian stock market. The study sample has a total of 560 observations corresponding to 112 companies from 2016 to 2020. The models by specific discretionary accruals of revenues proposed by Caylor (2010) and Stubben (2010) were considered to measure the management levels. As a method of analysis, we used regression models with panel data and tests at a significance level of 5%. According to the results obtained, it was impossible to confirm that adopting CPC 47 (IFRS 15) affected the quality of accounting information from the increase in revenue management levels, as well as whether the effects on the specific sectors indicated by the literature as more impacted were more significant than the other sectors in the Brazilian capital market. The research is relevant because it advances existing studies by using two different revenue management models to analyze the effects of specific accruals after adopting the standard and, in addition, extends the period and sample of Brazilian companies. Therefore, this research contributes to deepening discussions on the effects of applying accounting standards and assists in the analysis of regulatory bodies, preparers, auditors, and financial information on the effects of the new accounting standard after adoption, especially in the Post-Implementation Review (PIR) process of IFRS15.