In line with the regulation brought in by Solvency II, the Superintendence of Private Insurance (Susep) introduced the market risk capital requirement at the end of 2015, with 50% of the minimum capital for this type of risk being required by December 31st 2016 and 100% the following year. This regulatory model consists of calculating parametric value at risk with a 99% confidence level and a three month time horizon, using the net exposure of expected cash flows from assets and liabilities and a covariance matrix updated with market data up to July 2014. One limitation of this regulatory approach is that the updating of the covariance matrix depends on prior approval by the National Council of Private Insurance, which can limit the frequency the covariance matrix is updated and the model’s adherence to the current market reality. As this matrix considers the period before the presidential election, the country’s loss of investment grade status, and the impeachment process, which all contributed to an increase in market volatility, this paper analyses the impacts of applying the regulatory model, considering the market volatility updated to December 31st 2015, for a special savings company (sociedade de capitalização), an insurance company, and an pension fund. Furthermore, the paper discusses the practical implications of the new market risk requirement for managing the investments of the entities supervised by Susep, listing the various assumptions that can be used in the regulated entities’ Asset and Liability Management decision models and possible trade-offs to be addressed in this process.
Purpose -The Brazilian government approved regulations to foster the corporate bond market. In 2009, Instruction 476 of the Comissão de Valores Mobiliários (the Brazilian capital market regulator) relaxed the requirements for issuing bonds. In 2011, Law 12,431 created infrastructure bonds, which give individuals tax exemptions. Since then, aggregate proceeds have more than tripled. We describe the Brazilian bond market and the characteristics of issues and issuers; and critically evaluate this evolution.Design/methodology/approach -Descriptive analysis. Data on aggregate issuances; bond characteristics (proceeds, maturity, yields, underwriting); issuer characteristics; secondary market (trading); performance (default and renegotiation rates); and allocation of issues.Findings -Bond issues are small and bonds present a short maturity. International agencies are the main ratings providers, using a Brazilianadjusted rating scale. Fixed-yield bonds are rare. The vast majority of regular bonds are linked to the interbank offered interest rate (DI or CDI). Only two local universal banks dominate the underwriting activity. These banks and their related parties receive more than half of the aggregate allocation. Less than half of issues have an investment grade, and more than half are not rated at all. The incidence of expost credit events is most frequently in the form of renegotiations of bond terms. Strict defaults are also high. Liquidity for bonds in the secondary market is low.Originality/value -To our knowledge, this is the first article to describe the microstructure of the Brazilian bond market.
The Agile approach is focused on individuals and customer satisfaction, based on the dynamic and streamlined work of a team that is capable of adapting, and adapting the project to changing scenarios and demands. However, amidst the COVID-19 pandemic, Agile teams accustomed to in-person communication have encountered the challenges of working from home. The main objective of this research is to analyze the challenges generated by the pandemic context, and the consequent social distance, for the development of software projects that use Agile approaches within a large state-owned company and identify the effect it had on the course and results of the projects. The research was qualitative in nature and had two exploratory diagnostic stages. The findings indicate that there were no negative impacts of relevance on project deliveries. On the one hand, results indicated losses in socialization, in spontaneous exchanges of knowledge, and in interaction among teams, as well as a demand for greater engagement of professionals. Additionally, limitations were revealed for more complex discussions and knowledge management. The study highlights solutions that were found and/or suggested for many challenges, contributing to the literature on best practices for the Agile approach, and is focused on the unprecedented context of the COVID-19 pandemic. Our findings can contribute to other companies with a similar profile that work with Agile projects, besides contributing to building a dialogue between the academic and business environments.
Resumo O número de alunos no ensino superior brasileiro aumentou muito recentemente. Mas a evasão tem sido alta e objeto de estudo de diversos pesquisadores. Este trabalho analisa microdados do Censo da Educação Superior de 2009 a 2017 sobre a volta aos estudos dos alunos que se evadiram do ensino superior. Os resultados mostram que grande parte dos alunos que se desvincularam voltou para o ensino superior posteriormente, e, apesar de não voltarem para cursos da mesma instituição, a maior parte volta para cursos na mesma área do curso originalmente evadido. Além disso, os cursos da área de Comércio e Administração são um destino importante dos alunos que se desvincularam de cursos superiores, independentemente da área de origem.
One of the basic problems in finance is the choice of assets for investment. The first method to solve this problem was developed by Markowitz in 1952 with the analysis of how the variance of the returns of an asset impacts in the portfolio risk in which the same is inserted. Despite the importance of its contribution, the method developed for the portfolio optimization does not consider characteristics as the existence of round lots and transaction costs. This work presents an alternative approach for the portfolio optimization problem using Genetic Algorithms. For that three algorithms are used, the Simple Genetic Algorithm, the Multi Objective Genetic Algorithm (MOGA) and the Non Dominated Sorting Genetic Algorithm (NSGA II). The performance presented for the Genetic Algorithms in this work shows the perpective for the solution of this so important and complex problem, getting solutions of high quality and with lesser computational effort.
Forecasting interest rates structures plays a fundamental role in the fixed income and bond markets. The development of dynamic modeling, especially after Nelson and Siegel (1987) work, parsimonious models based in a few parameter shed light over a new path for the market players. Despite the extensive literature on the term structure of interest rates modeling and the existence in the Brazilian market of various yield curves from different traded asset classes, the literature focused only in the fixed rate curve. In this work we expand the existing literature on modeling the term structure of Brazilian interest rates evaluating all the yield curves of Brazilian market using the methodology proposed by Nelson and Siegel. We use Non Linear Least Squares (NLLS) to estimate the model parameters for almost 10 years of monthly data and model these parameters with the traditional VAR/VEC model. The results show that it is possible to estimate the Nelson Siegel model for the Brazilian curves. It remains for future research the modeling of their variances as well as the possibility to develop a global Brazilian model using Kalman Filter using the Diebold. Li. and Yue (2006) approach.
Clean energy is currently a top priority on the global agenda, and green bonds have emerged as a key response from financial markets. However, while these bonds aim to reduce carbon emissions, they may create perverse incentives. Brazil has made significant investments in eolic parks in recent years, with players issuing green bonds to finance these activities. One region that has seen high levels of investment is the interior of Bahia state, which has historically had low levels of economic and social development. Unfortunately, the production of wind energy in this region has been marked by several social conflicts. Despite this, these conflicts have largely gone unnoticed, as the appeal of clean energy has overshadowed them. Social issues such as land disputes are critical but often overlooked in green finance mechanisms. In some cases, these financial incentives may incentivize land grabbing from vulnerable populations in the name of clean energy production.
Resumo A estatística é uma das bases da ciência e seu ensino em programas de pós-graduação tem influência direta na formação da próxima geração de pesquisadores. Este trabalho traz um panorama geral das disciplinas relacionadas à estatística na pós-graduação stricto sensu no Brasil, a partir da análise das ementas das 176.823 disciplinas, sendo 12.552 com conteúdos relacionados à estatística. Dentre os fatos encontrados temos que poucos programas possuem disciplinas obrigatórias relacionadas à estatística. Quanto maior o conceito da pós-graduação na Capes, maior a quantidade média de disciplinas relacionadas à estatística ofertadas. Entretanto, essa relação não está presente nas disciplinas obrigatórias. Com relação ao conteúdo das disciplinas, elas se dividem em dois grandes grupos. Um grupo com base teórica em probabilidade e estatística, outro com foco em aplicações e utilização de ferramentas. Existe um pequeno terceiro grupo de disciplinas, ofertadas na língua inglesa. Por fim, a oferta de disciplinas relacionadas a técnicas avançadas (Machine Learning) é, se comparada à oferta das disciplinas relacionadas à estatística, muito pequena e se concentra, principalmente, nos programas de Engenharia e Ciências Exatas e da Terra.
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