Fabiano Guasti Lima

Uma proposta metodológica para o cálculo do custo de capital no Brasil

O Capital Asset Princig Model (CAPM) oferece conceitos validos e aceitos na definicao do risco dos ativos. Essa metodologia de calculo e medida pela relacao entre a covariância dos retornos de mercado e da companhia e a variância dos retornos da empresa. Por tratar-se de uma metodologia aplicada em mercados estaveis, as conclusoes favoraveis ao CAPM precisam, no entanto, ser reavaliadas em mercados emergentes, como o brasileiro. Sao discutidos os principais indicadores financeiros do mercado brasileiro e justificada, por meio de fundamentos estatisticos, a inconsistencia dos resultados. No estudo, mostrou-se a necessidade de apurar o custo de oportunidade dos investidores brasileiros utilizando o benchmark de uma economia mais estavel. O objetivo neste trabalho e sugerir um modelo que utiliza padroes de benchmark, sendo descritos os diversos ajustes necessarios ao calculo do custo de oportunidade dos acionistas das companhias brasileiras. De forma original, o modelo sugerido do custo de capital incorpora, alem do risco-pais, a volatilidade do mercado acionario brasileiro, demonstrando, portanto, a compatibilidade no desenvolvimento de uma metodologia de calculo do custo do capital no Brasil.

Crescimento econômico e comércio exterior: teoria e evidências para algumas economias asiáticas

A relacao entre comercio exterior e crescimento economico tem sido tema de longos debates na literatura economica. A principal controversia desse debate se da quanto a verdadeira contribuicao do comercio no crescimento economico e sua separacao de outros efeitos que podem exercer influencia tanto no comercio exterior quanto no crescimento economico e a separacao desses efeitos nao sao de forma alguma triviais. Neste trabalho, por meio da analise em painel, mostra-se que, mesmo com diversas tecnicas de estimacao por painel, o comercio exterior exerce influencia positiva e significativa no crescimento economico.

IFRS, sincronicidade e crise financeira: a dinâmica da informação contábil para o mercado de capitais brasileiro

This study aims is to investigate the synchronicity levels of shares traded on the spot market of the São Paulo Stock, Commodities, and Futures Exchange (BM&FBOVESPA) in relation to the accounting convergence process towards International Financial Reporting Standards (IFRS) in Brazil. The term synchronicity refers to the amount that company-specific information and market information are reflected in stock prices. The more share prices reflect company-specific information rather than market information, the greater the informational content of these prices will be in terms of representing the economic value of a particular company. For this investigation, information on companies and shares from 2005 to 2015 was collected, excluding the financial sector. The data were analyzed using cross-sectional and panel regressions. The results indicate a reduction in the synchronicity levels of stocks in the period of full adoption of IFRS in Brazil from 2010 onwards. From 2008 to 2009, which includes the partial adoption of IFRS in Brazil, statistically significant results were not found for the synchronicity levels of shares. However, for times of financial crisis, evidence was found of a reduction in the relevance of accounting information even with the adoption of international accounting standards. The results obtained for the Brazilian context do not support the idea that the adoption of IFRS necessarily causes an increase in the informational content of financial statements and that relevant information is consequently reflected in stock prices.

Risk management and value creation: new evidence for Brazilian non-financial companies

ABSTRACT The practice of financial risk management with derivatives has received attention both from the academia and the market. In Brazil, there is a growing use of these instruments by companies, in line with the growth of such market in the global economy. This article aims to investigate the relationship between the financial risk management and the value creation to the shareholder for non-financial Brazilian companies. The sample was made up of 1794 firm-year observations from 2006 to 2014. Results obtained via panel data, including the GMM, point out that companies which used derivatives did not add value during the period analysed. An explanation for this result is that most of the companies use derivatives in order to manage the cash flow and not to add value.

Performance of the different RAROC models and their relation with the creation of economic value: A study of the largest banks operating in Brazil

This article approaches several different methodologies forcalculation of the RAROC (Risk Adjusted Return on Capital)for Brazilian banks. Two questions gave reason to the study:whether the application of different methods for calculation ofthe RAROC would generate significantly different results?,and checking what is the connection between the RAROC andthe generation of economic value, measured by the EVA (EconomicValue Added), for the largest banks with operations inBrazil? The following methodologies for verification of theRAROC were applied: Buch’s Method (2011); Prokopczuk’sMethod (2006); Prokopczuk’s Method (2006) with applicationof the VaR technique; Saunders’s Method (2007); Chapelle’sMethod (2008); and the Smithon & Hayt Method (2001), byapplying these parametric and non-parametric statistics in orderto check the sensibility of the differences between models.This study has evidenced that, when we compare the methodologybased on minimum capital with other methodologies,there are no significant differences, except in the few cases indicated.It is important to notice it only occurred in the case ofthe Bank of Brazil and it was concentrated in the comparisonof the Creditmetrics models and in the methodology in whichthere is equivalence by the reference equity.

A Study of the Impact between the Macroeconomic Variables and the Brazilian Stock Exchange Index Through the Vector Autoregression and the Vector Error Correction

The current scenery of the economical conjuncture states that Brazil presents solid economical indexes, able to provide a suitable financial system for the growth of the stock market in the country. Therefore, the aim of this study was to analyze the correlation between a set of specific macroeconomic variables and the assets return in the Brazilian stock market, making use of the methodology of the multivaried model VAR. The variable used are: the GDP, the interest rate (SELIC), the Exchange rate, the inflation (IPCA), the price of a petrol barrel, the gold rate (BM&F) and the return of the Brazilian stock market, represented by the Indice da Bolsa de Valores de Sao Paulo (Ibovespa). Thus, it was intended to contribute for the understanding of how the internal macroeconomic variables can affect the decision taking on investment through the stock market in order to provide an additional tool for the decision-taking by the market agents as well as the authorities who, somehow, interfere in the conduction of the country´s monetary and exchange rate policy.

Stock Prices in an Artificial Stock Market with Optimistic and Pessimistic Agents

This research aims to investigate, through simulation models, how the interaction among agents in an artificial stock market can affect the dynamics of asset prices. Thus, the study follows a different methodology for the analysis of prices by exploring the simulation of agents’ behavior in an artificial stock market. From the defining characteristics of heterogeneous agents, we set up an artificial stock market in which individuals interact, by demanding and supplying assets, driving the price of a stock to an equilibrium value. The results suggest that, under the assumption of utility maximizers agents with different expectations about future dividends, asset prices may under-react. The gradual change of prices observed in the sub-reaction confronts the efficient market hypothesis, in which all information is instantly

The Recursive Partitioning Algorithm (RPA): A Nonparametric Classification System

Leo Breiman (Breiman et al., 1984, 1998) was a statistician who was fond of practical applications, and this led him to develop several original studies. Based on the work begun by Friedman (1977), he developed a very accurate classification system, without the need for statistical assumptions, since it is a nonparametric methodology. The aim of this study is to present the work of Breiman known as the Recursive Partitioning Algorithm. The RPA will be introduced as a nonparametric approach to credit analysis, allowing for the incorporation of the costs of misclassifications. Several studies, such as Novak and LaDue (1999) and Marais, Patais and Wolfson (1984), have shown its applicability in the analysis and granting of credit. A long road has been traveled from the early work of Friedman (1977) to the CART model developed by Steinberg and Golovnya (2006). This paper – apart from presenting the fundamentals and possibilities for use of the RPA – seeks to show the effectiveness of the results attained through a comparison with a parametric model, the Discriminant Analysis, considered the most traditional and classical method of analysis. The results show the RPA to be a superior technique, as well as a technique of easy intuition by analysts. The conclusion of the paper confirms that the RPA system – little known and discussed by academics and market professionals – is a powerful classificatory tool, with the advantage of being nonparametric.

ommodity price forecasting using ARIMA-GARCH models and neural networks with wavelets: old technologies - new results

The main objective of this study was to explore the possibility of applying a methodology capable of decomposing a time series through wavelets, in conjunction with econometric and neural network models, to forecast variables. The authors also compared the quality of the forecasts of chronological successions as applied to the study of a commodity, soy. The distinguishing feature of this study is based on the realization of the forecasts within the subseries decomposed by a wavelet and on obtaining estimates through reconstruction of the time series. From the analysis of the data for a 60 kg sack of soy, the results obtained were particularly satisfactory when using a wavelet filter in a recurrent neural network.

Complexity theory and adaptation landscapes: aplicaciones en estrategia

En este articulo, se tiene como objetivo investigar la dinamica de la posicion estrategica de empresas, segun el punto de vista de la teoria de la complejidad. Por medio de la aplicacion del concepto de paisaje adaptativo, se desarrolla un algoritmo basado en el modelo NK(C) de Kauffman, que posibilita, a partir de una analogia con la evolucion en biologia, evaluar como elementos asociados a las complejidades organizacionales afectan la estructura competitiva de una industria. En este estudio, se simulan varias combinaciones de escenarios, en los que variables relevantes de las organizaciones son interdependientes internamente, asi como dependientes de variables externas. Los resultados sugieren que: cuando hay alta complejidad interna, ventajas competitivas sustentables pueden ocurrir, en funcion de la habilidad de gestion de competencias y recursos; cuando hay complejidad externa, la dificultad de optimizacion en un paisaje adaptativo accidentado puede implicar la necesidad de adopcion de una estrategia de integracion vertical; cuando las barreras de entrada son altas, la industria esta caracterizada por carga genetica elevada, lo que implica gran diversidad estrategica y baja eficacia; y la posibilidad de reestructuracion puede evitar inercia, llevando a que, en ambientes complejos, se alcancen puntos de mayor desempeno.