Brazilian Stock Research Articles

Effects of monetary policy news on financial assets: Evidence from Brazil on a bivariate VAR-GARCH model (2006–17)

The impact of news releases related to the inflation targeting regime on the financial market is analyzed by estimating a bivariate VAR GARCH-BEKK-in-mean model. We use daily data, from January 2006 to May 2017, of stock prices index (IBOVESPA), exchange rate (BRL/USD) and interbank deposit rate (DI360). We developed a positive and negative news index to measure the impact of news releases based on Caporale et al. (2016) and Caporale et al. (2018). Although the literature on the subject is vast, this paper fills relevant gaps in three ways. First, we investigate the bidirectional relationship between monetary policy related news releases and the behavior of asset prices before and after the 2008 crisis in Brazil. Second, we consider the relationship between the second moments of the variables of interest, using the conditional volatility as a proxy for uncertainty. Third, we provide a time series approach to measure the effect of macroeconomic related news releases on financial asset returns. The results indicate there are mean spread effects from news for the exchange rate and the Brazilian stock index: (i) the GARCH-in-mean parameter is statistically significant for positive and the difference of news for the DI360; (ii) monetary policy and external shocks are statiscally significant as expected with exception of the external shocks for the Brazilian stock index; and (iii) there are volatility spillovers and changes of this volatility after the crisis for stock index and DI360.

The Brazilian financial market reaction to COVID-19: A wavelet analysis

We study the Brazilian stock market response to the COVID-19 pandemic. Considering the COVID-19 data from January 22, 2020, to August 31, 2021, and a daily dataset comprised of the Bovespa index - the main performance indicator of the stocks in the Brazilian capital market -, its sector components, and COVID-19 cases and deaths in the most affected countries, we employ the wavelet tools of partial coherences, partial phase differences, dissimilarities, and VaR ratio. We find significant partial coherence spots, decrease in dissimilarity, and increase in VaR ratio suggesting the Brazilian stock market responded forcefully to COVID-19 local and international data and that this response varies over time and frequencies being modulated by the local stage of outbreak. The results also suggest a higher response to deaths data and that both market wide response and the sector contagion are more evident on longer term frequencies.

Multiobjective Model Predictive Control for portfolio optimization with cardinality constraint

Model Predictive Control has been shown to be adequate to solve portfolio optimization problems because of its ability to perform the dynamic readjustment of the portfolio considering the market expectations. To consider both wealth and risk and real issues imposed by the financial market, this work proposes a Multiobjective Model Predictive Control strategy with cardinality constraints, besides transaction costs, self-financing, and upper and lower limits. The objective functions are the expected portfolio wealth and the expected Variance and Conditional Value at Risk as the portfolio risk measures. The optimization is performed by a multiobjective genetic algorithm, with operators proposed to control the number of assets in each portfolio and respect the prediction horizon perspective. Finally, an insightful case study is designed using the Brazilian Stock Exchange data in 2019 and 2020. An in-sample analysis explores the relationship between prediction horizon length, cardinality, optimal portfolio composition, risk-free asset, and objective functions on performance. An out-of-sample analysis considers the cumulative wealth, Sharpe ratio, maximum Drawdown, and the monthly accumulated return. Numerical experiments indicate that the proposed strategy outperforms the myopic portfolio selection, beats the primary Brazilian benchmark, a modified Markowitz model, and some top Brazilian investment funds even in crisis times like during the COVID-19 pandemic.

Impact of macroeconomic variables on the topological structure of the Brazilian stock market: A complex network approach

Complex networks is an interdisciplinary field of study, effective in modeling various phenomena of strategic and/or market interest. Complex correlation networks between financial assets are mathematical abstractions that represent the relations between the financial returns of certain assets in a given period. The present work analyzed the Brazilian stock market, as well as the macroeconomic variables and indicators correlated to it in the context of complex networks. Based on the concept moving networks, 43 monthly complex networks were developed with relationships based on Pearson correlations between the logarithms of individual asset returns. To evaluate the impact of the oscillations of macroeconomic indicators on the topological structure of the network of assets, autoregressive vector models were used, as well as variance decomposition and Granger causality. The results of the Granger causality tests suggest that Gross Domestic Product, Risk Brazil, Ibovespa points and Interest rate influence the metrics density and number of components. The macroeconomic variables Gross Domestic Product, Risk Brazil and Ibovespa points presented, in general, higher explanatory power in relation to the variances of the density, transitivity and components number metrics. Among the positive and practical aspects related to this work, it is possible to highlight the use of global metrics of complex networks of assets as a support tool for investors and financial analysts in the detection of risk and volatility through oscillations in macroeconomic variables and policies.

The Effect of Energy Prices on Stock Indices in the Period of COVID-19: Evidence from Russia, Turkey, Brazil, and India

Petroleum and natural gas, which are among the most used energy sources in the world, have a significant impact on financial markets and macroeconomic indicators as they are used as raw materials in many fields. For this reason, Russia, Turkey, Brazil, and India, as energy importers and developing countries, may be affected positively or negatively by changes in energy prices. The main purpose of this study is to examine the correlation between Brent oil, crude oil (WTI), and natural gas (NG) prices and Moscow Stock Exchange Index (RTSI), Borsa Istanbul Index (XU100), Bovespa Brazilian Stock Exchange Index (BVSP), and Indian National Stock Exchange Nifty 50 Index (NSEI). In the study, weekly data between 16.02.2020 and 26.12.2021 were examined. Vector autoregressive (VAR) model was used to examine the correlation between the variables included in the analysis, and the direction of the correlation between the variables was determined by the Granger causality test. According to the results of the VAR model, Brent oil and crude oil prices have significant effects on the indices included in the analysis; however, natural gas price does not have a significant effect on indices, Brent oil, and crude oil prices. On the other hand, the results of the Granger causality test confirm the findings of the VAR analysis. Granger causality test results reveal that in Granger's sense, only BVSP and NSEI are the cause of Brent oil price, RTSI, BVSP, NSEI, and XU100 are the cause of WTI, and WTI is the cause of NSEI.

Adding value, profitability and indebtedness: an approach to companies listed on the B3 stock exchange in the pandemic period

The objective of this work was to analyze the degree of explanation of the size factor, the economic value added and the profitability as a function of equity on the level of indebtedness of the main companies listed on the Brazilian Stock Exchange. The discussion of the health crisis caused by Covid-19 is incorporated as a determining factor, as well as the theoretical discussion that the stock market indicator can be an important estimator of the behavior of the economy. The methodology used was a dynamic panel based on the methodology developed by Arellano and Bond in 1991, justified by the nature of the data. The results support the hypotheses launched in the study, where the variation in value addition has a positive impact on indebtedness for the pandemic period, and increases in profitability reduce companies' financial risk exposure. The effects of each of the variables are notable according to the analyzed interval, that is, in the pre- and pandemic period. The main contribution of this article is to provide a broad and rigorous empirical approach in order to assess the impact of the studied variables. In addition, this study considers companies with greater volume and liquidity serving as a proxy for the sectors of the Brazilian economy.

Can extreme returns predict the cross-section of expected returns in the Brazilian market?

This article extends the evidence of maximum (MAX) and minimum (MIN) daily return effects on stock performance to the Brazilian market. Our sample includes data on daily and monthly stock returns of the firms listed on the Brazilian stock exchange between January 2001 and December 2018. To test whether extreme returns can predict the cross-section of expected returns, we perform univariate and bivariate portfolio analyses and the Fama-MacBeth regression. The results suggest a negative (positive) relationship between MAX (MIN) and the cross-section of future stock returns, which supports the hypothesis that idiosyncratic lottery-like payoffs are priced in equilibrium. This work is of interest to investors seeking insight into how to analyze high-risk and reward opportunities in the Brazilian stock market.

Female representation on boards of directors and environmental disclosure: evidence of the Brazilian GHG protocol program

PurposeThis study aims to identify a relationship between the presence of women on the board of directors (BOD) of Brazilian companies and the firms’ disclosure and participation in projects or initiatives to reduce greenhouse gas (GHG) emissions.Design/methodology/approachThe research used an adaptation of the model by Ben-Amar et al. (2017), added two other gender variables and analyzed a sample of 42 companies listed on the Brazilian stock exchange that participate in the Brazilian GHG protocol program. As for the models with the variables of interest, the most significant was the female percentage, Blau’s index, the dummy of female presence, the number of women on BOD, total years with the woman on board and the number of committees the board women were.FindingsThe results for the sample showed that women were present on the BOD 475 times, against a male presence of 4,538 times. Empirical evidence confirms the research hypothesis that there is a positive relationship between the presence of women on the BOD and the likelihood of participation in the Brazilian GHG protocol program.Research limitations/implicationsThe fact that few companies are listed on Brasil, Bolsa and Balcão and participate in the Brazilian GHG protocol program. Therefore, the impact of these findings may be reduced when compared with countries presenting more listed companies that have joined this type of program to diminish GHG emissions.Originality/valueThis study contributes to the literature on accounting, discussing carbon accounting in the field of environmental accounting and emphasizing that climate change-related risks greatly influence business and corporate assets. According to an article published by the World Resources Institute Brasil (2019), Brazil is the seventh country with the highest GHG emissions in the world.

DETERMINANTS OF THE DEGREE OF INNOVATION IN THE INDUSTRIES LISTED ON THE B3

The study aims to identify the determinants of the degree of innovation of industries listed on the Brazilian Stock Exchange - B3. To this end, it used as sample 129 industries that trade their shares on the B3. From the principal component analysis, it was found that the innovation indicators are combined into two distinct factors. Therefore, it can be said that the degree of innovation of the firms takes into account the combination of indicators referring to the innovation strategies of exploitation and exploration, and, by encompassing two distinct factors, it is valid to mention that the degree of innovation has a two-dimensional character, suggesting the existence of a synergy between the innovation strategies.

Readability as a measure of textual complexity: determinants and evidence in Brazilian companies

ABSTRACT The aim of this article was to evaluate the effect of company earnings and of harmonization with IFRS on the readability of Management Reports in the Brazilian stock market. There is a gap to be filled both in the elaboration and adaptation of readability measures to the context studied, as the studies tend to replicate the original formulas, and in identifying the determinants of the readability of Brazilian company reports, as the research in this field remains in its infancy and the results are inconclusive. The results provide indications for investors to identify complex textual information and may help public policymakers to establish a simple writing manual, along the lines of the SEC’s 1998 Plain English Handbook. The modified metrics and the one developed overcome the criticisms regarding the use of readability formulas in accounting research and could be used in substitution of the original metrics in future studies. An econometric model was used that presents the determinants of readability. Readability was calculated for the Results Analysis section of the Management Report. The resulting construct is understood via three attributes: persistence, current performance, and the reference benchmark. Harmonization with IFRS is a dummy variable, which delimits the pre- and post-IFRS periods. The hypotheses were tested in a sample of Brazilian companies made up of 714 company-year observations covering the period from 2006 to 2019. The descriptive results show that there is an apparent improvement in the readability of the reports in the pre- and post-IFRS period comparison. The econometric evidence shows that, in general, companies with persistent and positive earnings present less complex reports and are more likely to have highly readable reports, because managers publish reports with better readability to signal positive results to the market.

Implications of regional agricultural land use dynamics and deforestation associated with sugarcane expansion for soil carbon stocks in Brazil

Implications of regional agricultural land use dynamics and deforestation associated with sugarcane expansion for soil carbon stocks in Brazil

The relationship between climate change mitigation strategies and the financial performance of Brazilian companies

AbstractStudies on the relationship between corporate sustainability strategies and financial performance are often dealt with in a broad manner, which can hinder the ability to consolidate knowledge on the subject. In order to add greater depth and understanding to the debate, this study focuses on the issue of climate change mitigation strategies (CCMS). This focus allows for a reduction in the complexity of the analyses of the relationship between environmental and financial performance, and a more thorough discussion of corporate sustainability strategy choices. To analyze the relationship between CCMS and financial performance, this research collected data from 61 companies that took part in the selection process for the Corporate Sustainability Index (ISE) of the Brazilian Stock Exchange (B3), which was published between 2013 and 2019, and contained 249 observations. The research used multivariate analysis with the panel data regression method. The results showed there to be a positive and statistically significant relationship between CCMS and the financial performance of companies, indicating that the corporate implementation of practices and policies for facing up to climate change can lead to both environmental and economic benefits for companies.

A Multicriteria Decision Trading System Based on Prospect Theory: A Risk Return Analysis of the TODIM Method

This paper proposes a trading system (TS) based on a multicriteria decision aid (MCDA) process known as TODIM, (Multicriteria Interactive Decision Making) a Portuguese acronym for interactive and multicriteria decision-making. MCDA has been employed to solve financial questions because of its ability to deal with a complex environment populated with different sorts of criteria and alternatives, such as financial markets. The aim is to propose a general and adaptive tool for supporting the trading strategies of investors and market practitioners in such an environment. The reason for selecting TODIM among the different MCDA methods is that it is based on prospect theory, which assumes that the risk profile of the investor varies according to different situations, considering the risk of loss or gain. A list of simulations using some of the most prominent Brazilian stocks is performed, and the results are compared with the Buy-and-Hold benchmark and a TS based on an ensemble method for selecting trading rules. The results show that, compared to Buy-and-Hold, a TODIM-based TS provides the same level of return with a lower level of risk exposure. The consequence is superior risk adjustment parameters. As a result, we have a model with similar results in profit, but with superior results in relation to risk-based performance, which makes the method advantageous in relation to similar ones.

The effects of integrated food and bioenergy cropping systems on crop yields, soil health, and biomass quality: The EU and Brazilian experience

AbstractIntegrated food and bioenergy production is a promising way to ensure regional/national food and energy security, efficient use of soil resources, and enhanced biodiversity, while contributing to the abatement of CO2 emissions. The objective of this study was to assess alternative crop rotation schemes as the basis for integrating and enhancing the sustainable biomass production within the food‐energy agricultural context. Sunn hemp (Crotalaria spp.) in rotation with wheat (Triticum spp.) in the EU and with sugarcane (Saccharum spp.) in Brazil were evaluated. Sunn hemp did not negatively affect crop's productivity and soil fertility; wheat grain yields were maintained around the mean regional production levels (6, 7, 3 and Mg ha−1 in Greece, Italy, and Spain, respectively), and the cumulative biomass in the extended rotation (wheat straw+sunn hemp) was between 1.5 and 2.0 times higher than in the conventional rotation. In Brazil, sugarcane stalks yield in clay soils increased by around 15 Mg ha−1 year−1 under sunn hemp rotation in comparison with bare fallow. Moreover, sunn hemp in the EU rotations did not have negative effects on soil available macronutrients, organic matter, pH, and cation exchange capacity, neither on C and N stocks in Brazil. The qualitative characteristics (mineral, ash, and hemicelluloses contents) of the cumulated biomass were somehow higher (in average +26%, +35%, and +3.4%, respectively) than in the conventional system. In summary, in temperate and tropical climates the integration of dedicated biomass legume crops within conventional systems could lead to enhanced biomass availability, crop diversification, and efficient use (in space and time) of the land resources.

How do stock price indices absorb the COVID-19 pandemic shocks?

To assess the resiliency of stock price indices during the COVID-19 crisis, this study provides a distinctive perspective; that is, we evaluate the ability of stock price indices to absorb COVID-19 shocks. We construct the measures of absorptive intensity and duration to identify a stock price’s absorptive capacity. We then employ the Granger causality test and a topology network approach to investigate the interactions of absorptivity among stock price indices. Our results show that stock price absorptivity varies over time and across countries and industries. The US and the Brazil stock indices have relatively high absorptive intensity while short duration. The health care industry shows distinctive trend in absorptive intensity from the other industries. The intensity of the non-cyclical industries such as utilities and consumer staples is high, while the cyclical industries such as banking, real estate, and energy have lower absorptive intensity. Moreover, the utilities, consumer staples, and financials industries are the main resiliency transmitters.

Sentiment Analysis Applied to News from the Brazilian Stock Market

Investments in the stock market have grown in Brazil in recent years, especially considering the individual number of investors. According to data from April 2020, the Brazilian stock market reached the historic mark of 2.38 million active investors, and with this scenario, there is an increasing need to study the Brazilian financial market, seeking to better understand its fluctuations. Recent work in the literature indicates that a companys stock values can be influenced by published news. Therefore, this work contributes to the automatic sentiment analysis applied to news written in Portuguese and related to the Brazilian stock market. For this, we performed three sentiment analysis strategies: two based on machine learning, using the Naive Bayes classifier and a Multilayer Perceptron neural network; and the other based on the lexical approach. Also, we proposed two dictionaries, focused on the financial domain and adapted to Portuguese. Our results show that the Naive Bayes classifier and the Multilayer Perceptron overcomes the best lexical approach. It is worth mentioning that the accuracy achieved by the best lexical approach was with the adapted dictionary proposed here.

Impact of COVID-19 Outbreak on the Stock Market: An Evidence from Select Economies

COVID-19 quickly spread all over the world and dramatically affected the financial markets in almost everycountry. Its spread created havoc in the market, and investors fearing risk suffereda significant amount of financialloss in a very short time. This article aims to analyze the impact of COVID-19 on stock markets in the top six affected countries based on the total number of cases confirmed. In addition, it also analyzes the stock market volatility caused by the virus and the abnormal returns generated by the markets during the pandemic. We employevent study methodology in different sub-periods to examine the most volatile event periods with the daily rise in the Covid cases and subsequent returns generated by the markets during these sub-periodsin relation to the daily rise in the case. The increase in volatility and the presence of significant abnormal returns among the sample indices show the impact of COVID-19 on stock markets. The result reveals that Brazilian stock indices show the highest decline among the selected countries, with a fall of more than 50% during the pandemic, while Mexican indices show the lowest fall of around 30% during the same period.

Macroeconomic and Financial Variables’ Influence on Brazilian Stock and Real Estate Markets: A Comparative Analysis in the Period from 2015 to 2019

Numerous studies have sought to investigate the relationship between macroeconomic variables and financial market evolution. Such analyses, however, have focused on the stock market. The present research, as a distinction, included the index of real estate funds (IFIX) in its approach. In this context, the study comparatively analyzed the impact of macroeconomic indicators (interest rates, inflation, industrial production, and the exchange rate) and financial indicators (the S&P 500 and the oil price) on the Ibovespa and the IFIX from January 2015 to December 2019. This period was chosen due to the peculiar characteristics of the resumption of economic growth after the 2014-2016 recession in the context of changes in the degree of intervention in the economy. The research addressed the historical evolution of stock and real estate fund indices, such as the Ibovespa and the IFIX, respectively, which showed a positive trajectory, especially from 2016 onward. To achieve its objective, the research applied the vector with error correction (VEC) econometric model to determine whether there is a possibility of diversification between the two markets. Among the results obtained were relatively convergent behavior of the Ibovespa and the IFIX in the face of macroeconomic and financial shocks, according to the impulse response functions of the estimated econometric model, which prevents diversification between the two markets.

Improving Portfolio Selection by Balancing Liquidity-Risk-Return: Evidence from Stock Markets

The Modern Portfolio Theory was mathematically structured on the basis of the risk-return tradeoff: in other words, the riskier the investment, the greater the required potential return. Traditional portfolio optimization models, however, implicitly consider that all assets can be traded at any time and in any quantity, which is unrealistic. The aim was to propose a two-stage method that includes the prior classification of liquidity based on the bid-ask spread and a mathematical optimization model that uses liquidity as a defined participation constraint. Simulations were carried out using twenty years of data from the American (NYSE) and Brazilian (B3) stock exchanges. The results showed that the method developed offers a broader range of the alternatives that comprise the MV model with a more realistic approach to liquidity. The proposed method can form portfolios that respect the risk-return rules once the investor’s risk profile has been defined, making it a useful recommendation tool for institutional investors. From a conservative point of view, the developed method also showed the potential for reducing uncertain sales by 10.3% on average.

Are Natural-RBV Strategies Profitable? A Longitudinal Study of the Brazilian Corporate Sustainability Index

Purpose – The aim of this research is to analyze whether natural resource-based view (NRBV) strategies lead to financial performance, represented by market value in the Brazilian stock exchange (B3) Corporate Sustainability Index (ISE).Theoretical framework – The NRBV foresees three green strategies to achieve sustainable competitive advantage: pollution prevention, product stewardship and sustainable development. Many studies have tested one or two of those strategies. We tested if all three strategies are related to the financial performanceof companies in the ISE index.Design/methodology/approach – We collected five years of data from 18 companies that compose the ISE index and employed panel data analysis in this longitudinal study.Findings – All three strategies of the NRBV are related to the companies’ market value in different ways. The results diverge from the current literature because we found positive and negative links between environmental strategies and financial performance.Practical & social implications of research – This study contributes with empirical results from the B3 to analyze the ISE index using the NRBV approach as a theoretical basis. It suggests that not all environmental initiatives increase companies’ market value, as some actions may end up achieving the opposite outcome. Investors and society, in general, are entitled to know how companies implement sustainable strategies that go beyond those required by law. Originality/value – The major contribution of this study is it addresses all three NRBV strategies to investigate if it pays to be green in terms of market value, by analyzing the Brazilian sustainable organizations that compose the ISE index.Keywords – NRBV, corporate sustainability, financial performance, market value, sustainable development.