Brazilian Market Research Articles

How explain on-grid PV systems diffusion? Review and application in Brazil

This paper examines the remarkable growth of photovoltaic (PV) solar energy technology in Brazil, which stands out among the leading countries in photovoltaic installations. The recent implementation of Law 14300 on grid-connected PV systems has caused a stir in the Brazilian market, with investors anticipating installations to avoid reductions in benefits. This phenomenon, previously observed in Europe, instigates an understanding of the variables underlying the exponential growth of the Brazilian market. This study seeks to identify the predictors that explain the PV systems diffusion in Brazil, in two stages: a systematic review of the literature to map approaches and methods, followed by the construction of a database and the application of predictive models. The literature revealed 24 methods in six approaches, with 44 predictors. For Brazil, the database contains 90,129 instances, 22 predictors, and covers all 5570 municipalities. The results highlight the crucial importance of the electricity tariff as the main predictor, followed by irradiation and municipal Gross Domestic Product. Predictors such as the number of companies, minimum wage, HDI education, demographic density, and vehicle fleet prove to be relevant. In conclusion, the spatially explicit analysis highlights the complexity of the market, offering valuable implications for energy planners and stakeholders.

European Union–Mercosur Accord's effects on Brazilian milk powder

AbstractMilk is one of the few agricultural products in which Brazil is not competitive. The domestic market is served by domestic production and imports from Argentina and Uruguay. The Mercosur–European Union Biregional Association Agreement provides for the elimination of tariffs and the harmonization of nontariff measures between the parties. Because the EU is one of the most competitive regions in the world market for powdered milk, this study analyzes the effects of the agreement on the links in this production chain in the Brazilian market. A constant, nested, multisectoral, and vertically integrated elasticity of substitution model is structured incorporating uncertainty in the estimates of Armington elasticities through Monte Carlo simulations, as in Hallren and Opanasets. The model allows projecting the price effect (Armington) and the preference effect in the market shares of Brazil, Mercosur, and the EU on the domestic market. The results, in the most ambitious scenario of the agreement and in the most conservative estimate, show that Brazil would lose 71.7 percentage points in the domestic market. This means reducing Brazilian production by 475 thousand tons of powdered milk. The national agricultural link in this scenario would lose 15% of the current dairy demand. This loss benefits the EU, which would participate in the domestic market with a market share of 58.75%. Mercosur would add 13.41 percentage points to its current share of the Brazilian market [EconLit Citations: F13, F14].

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.

Environmental certifications in Brazilian aquaculture

Environmental certificates in aquaculture are becoming important market tools throughout the world. However, there are important regional and national differences, and Brazil, due to the low number of certified companies, deserves specific research. A preliminary analysis of the Brazilian aquaculture market shows a large market with strong growth and more than 25 cultivated species, but where 80% of the turnover is focused on tilapia, tambaqui, and white shrimp, primarily targeting the domestic market with very few exceptions to the external market. These particular conditions seem to explain the low number of certified aquaculture companies, even when compared to other countries in the region with similar or smaller aquaculture industries. This study interviewed managers from 80 companies in the Brazilian aquaculture production chain, including all certified companies. The results seem to be in line with previous studies conducted in different parts of the world. The main benefits associated with aquaculture certifications are access to new markets and production improvement, while the main barriers to certification are high costs, lack of awareness, bureaucracy, or lack of government support. Certified Brazilian aquaculture companies share similar characteristics among themselves but differ from most companies in Brazil; they are all large-scale firms, mainly related to tilapia production and oriented towards the international market. The low number of certified companies seems to be linked to the large demand for aquatic products in Brazil that even Brazilian aquaculture firms cannot satisfy.

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.

An overview on Brazilian Energy Market

Abstract Brazil is a major player in the global energy market, with the seventh largest electricity generation capacity in the world. The country's energy sector is characterized by a strong reliance on hydropower, but there is also a growing trend towards renewable energy sources such as wind and solar power. This article makes a general overview on Brazilian energy market, focusing on legal framework, regulatory authorities and transport and distribution system both on electricity and oil and gas sectors. It is also presented the today market situation. Finally, the article concentrates on energy produced from renewable sources and make a parallel on renewable energy market comparing the situation in Brazil, India and China.

The cigarette market in Brazil: new evidence on illicit practices from the 2019 National Health Survey

ObjectiveTo explore new evidence on illicit practices, such as selling legal brands below the minimum legal price (MLP), and smugglers selling illicit brands at or above the MLP.MethodsFor the first...

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

Proposal to improve the regulatory framework of the Brazilian free energy market with a focus on sugar-energy bioelectricity

PurposeBioelectricity from sugarcane presents possibilities of gaining prominence as an energy source in the coming years, contributing to sustainable development and being a relevant pillar of Brazil’s energy matrix, based on its advantages and the measures that can stimulate it. The purpose of this study is to contribute to a new framework for improving the regulatory framework for Brazilian sugarcane bioelectricity that facilitates the governance of its stakeholders and their respective relationships.Design/methodology/approachExploratory and qualitative research, adopting, in addition to theoretical and practical research, consultations with experts, combined with analysis of documents relating to sustainability reports released by companies in the sector.FindingsIn the observed reports of 23 companies, it was found that 14 give full relevance to bagasse energy, and it can be attested that sugar-energy bioelectricity includes social, economic and environmental dimensions. In addition, the work presented elements that can benefit cogeneration, such as reduction or exemption of the distribution system use tariff for energy generation from bagasse; freedom for full commercialization in the free energy market, including small consumers; contractual simplification and solidification of financial compensation for clean energy production.Originality/valueThe work contributes to the advancement of theoretical references of business economics and competitiveness for practical application in competitive sustainability environments.

Influence of friction between wood and support elements in the design of timber structures for roofing

Throughout history, wood has played a crucial role in all phases of building construction. Despite existing prejudices in Brazil regarding its use in structural systems, primarily due to the lack of dissemination of technical information, wood is gradually gaining more space in the market as a viable and environmentally sustainable alternative. With exceptional mechanical properties, wood is compatible with other widely used construction materials in the Brazilian structural market, such as concrete and steel. In this context, this research aims to analyze the influence of considering the friction coefficient caused by the sliding of the support with free horizontal displacements in isostatic trusses, investigating its impact on the design of the components that make up the truss. Such sliding generates a lateral friction force that promotes a restraining effect on the structure, potentially relieving stresses on the lower chord members. For this purpose, the Finite Element Method (FEM) is used as an analytical tool, supported by the iTruss verification software to validate the obtained results. By considering the frictional force generated on the support links of the analyzed trusses, the numerical results revealed changes in the design of structural profiles for all existing wood strength classes (D20, D30, D40, D50, and D60) in situations of friction between wood and wood, and between wood and concrete. A reduction in the volume of wooden pieces was observed, ranging from 5.88% to 8.54%, suggesting that the inclusion of the friction coefficient during structural calculations can result in savings, not only from a financial standpoint but also promoting environmental benefits by encouraging a more responsible use of wood in civil construction.

Impacts of Forced Immigration: The Venezuelan Diaspora and the Brazilian Labor Market

ABSTRACT This article estimates the impact of immigrant influxes on local labor markets, taking advantage of a natural experiment generated by a massive wave of forced migration of Venezuelans to Roraima, a state in northern Brazil, from 2016 onward. Estimates show that a 1% increase in the share of migrants in the state population due to immigration resulted in 1.1% higher earnings for native workers in the formal sector, 0.3% fewer hours worked weekly, and 2.3% higher wages. Results are confirmed by employing a synthetic control method.

Reflections of including key audit matters in the audit quality and audit fees of publicly traded companies in Brazil

Considering the context of the changes implemented by the revised ISA 700, which required including items such as Key Audit Matters (KAMs), this article aimed to examine the effects of the changes in ISA 700 on audit quality and fees. Accounting and market data, information on the responsible audit firms, and the number of KAMs disclosed by publicly traded companies in Brazil were collected from 2014 to 2017. Overall, the results did not demonstrate evidence of improvement in audit quality after adopting the revised ISA 700. Audit fees also did not show statistically significant changes when comparing the period before and after adopting the new requirement. So, the study concluded that, during the four-year period surrounding the adoption of the new requirements, there was no evidence of an increase in audit quality or auditor fees for publicly traded companies in Brazil. This article expands academic discussions in the Brazilian capital market regarding the implications of including KAMs in audit reports, as well as the analysis of the practical effects of applying standards issued by regulatory bodies.

Market Practices and Structuring Practices on Market Making: Sustainable Certified and Specialty Coffee Market Dynamics in Brazil

On this paper, in a five years longitudinal study, the theoretical framework the constructivist market studies (CMS) were used to analyze how market practices interacted with structuring practices in the making of market arrangements throughout the sustainable and specialty coffee market development process in Brazil. Through the historical reconstruction of the UTZ certification program in Brazil and the Cup of Excellence (COE) coffee quality competition, based on document analysis and in-depth interviews, it was possible to identify the main market practices adopted by the actors involved in the organization and in market designing. It was possible to select specific translation moments that resulted in different market framings, showing how rules, devices and practices shaped the Brazilian coffee market. Main representational, normalizing and exchange practices were identified and it was highlighted the role of a new analytical category called “market structuring practices”, which acts as an important mechanism for the making of market arrangements and for the shaping and consolidation of market practices (marketization process).

Stock splits and reverse splits in the Brazilian capital market

Stock splits and reverse splits in the Brazilian capital market

Methodology for Multi-Step Forecasting of Electricity Spot Prices Based on Neural Networks Applied to the Brazilian Energy Market

Forecasting electricity spot prices holds paramount significance for informed decision-making among energy market stakeholders. This study introduces a methodology utilizing a multilayer perceptron (MLP) neural network for multivariate electricity spot price prediction. The model underwent a feature selection process to identify the most influential predictors. In the validation phase, the model’s performance was evaluated using key metrics, including trend accuracy percentage index (TAPI), normalized root mean squared error (NRMSE), and mean absolute percentage error (MAPE). The results were obtained for a four-week forecast horizon in order to serve as an auxiliary tool to facilitate decision-making processes in the short-term energy market. The relevance of short-term electricity spot price forecasting lies in its direct impact on pricing strategies during energy contract negotiations, which allows for the making of assertive decisions in the energy trading landscape.

Multivariate realized volatility: an analysis via shrinkage methods for Brazilian market data

IntroductionRealized volatility analysis of assets in the Brazilian market within a multivariate framework is the focus of this study. Despite the success of volatility models in univariate scenarios, challenges arise due to increasing dimensionality of covariance matrices and lower asset liquidity in emerging markets.MethodsIn this study, we utilize intraday stock trading data from the Brazilian Market to compute daily covariance matrices using various specifications. To mitigate dimensionality issues in covariance matrix estimation, we implement penalization restrictions on coefficients through regressions with shrinkage techniques using Ridge, LASSO, or Elastic Net estimators. These techniques are employed to capture the dynamics of covariance matrices.ResultsComparison of covariance construction models is performed using the Model Confidence Set (MCS) algorithm, which selects the best models based on their predictive performance. The findings indicate that the method used for estimating the covariance matrix significantly impacts the selection of the best models. Additionally, it is observed that more liquid sectors demonstrate greater intra-sectoral dynamics.DiscussionWhile the results benefit from shrinkage techniques, the high correlation between assets presents challenges in capturing stock or sector idiosyncrasies. This suggests the need for further exploration and refinement of methods to better capture the complexities of volatility dynamics in emerging markets like Brazil.

Performance and Durability of Paints for the Conservation of Historic Façades

This paper analyzes the performance of various types of paints available in the Brazilian market, including PVA, matte acrylic, silicate, and lime paints within the context of their applicability to the conservation of historic building facades. Considering distinct suppliers and application methods, this study highlights the importance of tailoring paint selection to the preservation requirements of historic edifices, taking into account local preservation norms and the material characteristics of the buildings’ original construction. The paints were evaluated based on water vapor permeability, washability, and adhesion. Furthermore, the paints’ color variation with exposure to accelerated artificial aging was assessed. For testing purposes, specimens produced from cellular concrete slabs were used as substrates, which were coated with the paints under study. Based on the results, it was observed that, regarding the diffusion of water vapor, the silicate and lime paints presented the highest permeability values, and the acrylic and PVA paints had the lowest. Concerning washability, the silicate and lime paints showed the greatest wear. The adhesion tests revealed that, except for lime paint, detachment often occurred at the substrate. As for the accelerated aging test, lime paint exhibited the most significant color variation, losing its pigmentation considerably over time. With the results of this research and considering the main preservation requirements of historic coatings, silicate-based paints may be considered the most suitable.

Estimating time-varying factors’ variance in the string-term structure model with stochastic volatility

This paper presents a novel term structure of interest rate (TSIR) model with stochastic volatility and jumps (SVJ) that combines the market framework proposed by Brace et al. (1997) with the string-shock framework of Santa-Clara and Sornette (2001). In this model, the factors’ variance is estimated through the eigendecomposition of a variance–covariance matrix obtained with a measure of market volatility derived from out-of-the-money option prices and historical correlations of interest rates traded in the futures market. The stochastic evolution of the factors’ variance is governed by the 4/2 model developed by Grasselli (2017), including jumps. A novel method is employed to estimate the parameters of the SVJ model that minimizes the distance between the sample moments and the moments of a gamma distribution. The empirical application of the model in the Brazilian derivatives market demonstrates its effectiveness in accurately capturing the volatility smile of interest rate options.

Plant-based products: Analysis of international regulations and strategies used for designation and labeling in Brazil

The consumption of vegetarian/vegan products that mimic the taste and appearance of animal products has grown worldwide. The objective of this study was to investigate the designations of these products in the Brazilian market, focusing on terms that may mislead consumers. The designations were evaluated concerning four aspects: i) use of the terms “vegan," "vegetarian," or similar ones; ii) misuse of standardized animal product designations; iii) misspelling of standardized animal product designations; iv) use of the terms “type” or “flavor” associated with the name of the animal products. There were 335 samples analyzed, 93 from supermarkets and 242 from websites, corresponding to three categories of analogs: meat (n = 154), dairy (n = 148), and others (n = 33). The terms “vegan” and “vegetarian” were used in 44.5% of the samples. It was concluded that most products had the wrong designations, reinforcing the need for regulation of such products in Brazil.

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.