Private equity regulation: what are the consequences of the alternative investment fund managers directive (AIFMD) on private equity managers?

The recent global financial crisis brought significant regulatory changes in the worldwide financial industry. In Europe and in the alternative asset sector specifically, a new regulation by the name of Alternative Investment Fund Managers Directive saw the daylight in 2010. This far-reaching and complex Directive with the main goal of regulating and overseeing alternative investment funds has triggered many discussions and represents an industry game-changer. Thus, this research will focus on the impact and consequences of the Directive on private equity fund managers and the role of regulators. In other words, what are the effects, what does that mean in a quantitative and qualitative sense, and how is it likely to influence the outlook of this asset class? In order to provide the reader with an extensive view on the topic, the paper will first discuss relevant theory and literature, using mix-methods and legal-dogmatic approaches. Further, descriptive case studies, analysis of existing surveys, and interviews with industry experts will supplement the paper in order to understand primary implications of the Directive with the goal of providing useful insights for further private equity regulation research.

In cash we trust: cash holdings in the brazilian equity fund industry

We study cash allocation ability as a possible explanatory factor that allows equity fund managers to produce high levels of adjusted returns (not explained by the risk factors they are exposed to). In order to do so, we explore the non-indexed Brazilian equity fund industry during the period of January 2006 to February 2015, evaluating cash allocation ability by level and effectiveness of cash deployment using return-based and holding-based approaches to explore a database of monthly invested assets and returns. We found that even though market timing is a rare skill in the industry, the flexibility to hold high levels of cash played a significant role in the result of over performing managers.

Compliance com os requisitos de divulgação do IFRS - International Financial Reporting Standards e sua relação com o erro de previsão dos analistas de mercado

O objetivo deste estudo é fazer uma análise da relação entre o erro de previsão dos analistas de mercado quanto à rentabilidade das empresas listadas na BM&FBOVESPA S.A. (Bovespa) e os requerimentos de divulgação do International Financial Reporting Standards (IFRS). Isto foi feito através da regressão do erro de previsão dos analistas, utilizando a metodologia de dados em painel no ano de implantação do IFRS no Brasil, 2010, e, complementarmente em 2012, para referenciamento desses dados. Partindo desse pressuposto, foi determinado o erro de previsão das empresas listadas na Bovespa através de dados de rentabilidade (índice de lucro por ação/earnings per share) previstos e realizados, disponíveis nas bases de dados I/B/E/S Earnings Consensus Information, providos pela plataforma Thomson ONE Investment Banking e Economática Pro®, respectivamente. Os resultados obtidos indicam uma relação negativa entre o erro de previsão e o cumprimento dos requisitos de divulgação do IFRS, ou seja, quanto maior a qualidade nas informações divulgadas, menor o erro de previsão dos analistas. Portanto, esses resultados sustentam a perspectiva de que o grau de cumprimento das normas contábeis é tão ou mais importante do que as próprias normas. Adicionalmente, foi verificado que quando a empresa listada na BM&FBOVESPA é vinculada a Agência Reguladora, seu erro de previsão não é alterado. Por fim, esses resultados sugerem que é importante que haja o aprimoramento dos mecanismos de auditoria das firmas quanto ao cumprimento dos requerimentos normativos de divulgação, tais como: penalidades pela não observância da norma (enforcement), estruturas de governança corporativa e auditorias interna e externa.

An essay on private equity: the history and fundamentals of fundraising in Brazil

O impacto positivo dos investimentos de Private Equity e Venture Capital (PE/VC) na economia e no mercado de capitais está amplamente documentado pela literatura acadêmica internacional. Nos últimos 40 anos, diversos autores têm estudado a influência desta classe de ativos na criação, no desenvolvimento e na transformação de milhares de empresas ao redor do mundo, especialmente nos Estados Unidos. Entretanto, os estudos sobre os determinantes da captação de recursos de PE/VC têm se desenvolvido apenas mais recentemente, e seus resultados estão longe de ser uma unanimidade. No Brasil, a pesquisa sobre a indústria de PE/VC ainda é escassa. Embora a indústria local venha crescendo rapidamente desde 2006, tendo alcançado US$36,1 bilhões em capital comprometido em 2009, ainda não há estudos sobre as variáveis que influenciam na alocação de capital pelos investidores nesta modalidade de investimento no Brazil. Entender esta dinâmica é importante para o equilíbrio e a eficiência de mercado. Baseado no trabalho de Gompers e Lerner (1998) sobre os determinantes da indústria de PE/VC nos Estados Unidos, este trabalho contribui com a literatura de PE/VC ao: (i) revisitar o começo desta indústria no Brasil; e (ii) identificar quais as variáveis influenciam no desenvolvimento da indústria de PE/VC local. Os resultados deste estudo contribuem para o desenvolvimento acadêmico da indústria de PE/VC no Brasil. Além disso, as discussões aqui apresentadas poderão impactar outras áreas de estudo que são permeadas pelo tema, tais como Gestão de Investimentos, Governança Corporativa, Empreendedorismo e Estratégia. Profissionais de mercado também deverão se interessar no trabalho. As discussões sobre a história e os fundamentos da indústria fornecem aos investidores, empreendedores, gestores de investimentos e formuladores de políticas públicas, entre outros, um melhor entendimento sobre como o ecossistema de PE/VC funciona no Brasil.

A influência da alavancagem financeira na construção do custo de capital próprio: um estudo voltado para o mercado brasileiro

No contexto do Capital Asset Pricing Model (CAPM), este trabalho investiga a significância da alavancagem financeira na construção do risco sistemático. Testamos com dados brasileiros o procedimento de desalavancagem e realavancagem do beta comumente realizado por analistas financeiros para a construção do custo de capital próprio de empresas não negociadas em bolsa de valores. Os resultados apontam que a inclusão do tax shield na fórmula de desalavancagem/realavancagem e a utilização de valores de mercado produzem resultados mais robustos, ao passo que as divisões por setores possuem pouca capacidade como segmentadores de classe de risco sistemático.

Assessment of value creation in private equity: the acquisition of Burger King by 3G Capital

This thesis elaborates the creation of value in private equity and in particular analyzes value creation in 3G Capital’s acquisition of Burger King. In this sense, a specific model is applied that composes value creation into several drivers, in order to answer the question of how value creation can be addressed in private equity investments. Although previous research by Achleitner et al. (2010) introduced a specific model that addresses value creation in private equity, the respective model was neither applied to an individual company, nor linked to indirect drivers that explain the dynamics and rationales for the creation of value. In turn this paper applies the quantitative model to an ongoing private equity investment and thereby provides different extensions to turn the model into a better forecasting model for ongoing investments, instead of only analyzing a deal that has already been divested from an ex post perspective. The chosen research approach is a case study about the Burger King buyout that first includes an extensive review about the current status of academic literature, second a quantitative calculation and qualitative interpretation of different direct value drivers, third a qualitative breakdown of indirect drivers, and lastly a recapitulating discussion about value creation and value drivers. Presenting a very successful private equity investment and elaborately demonstrating the dynamics and mechanisms that drive value creation in this case, provides important implications for other private equity firms as well as public firms in order to develop their proprietary approach towards value creation.

Speculative bubbles and contagion: analysis of volatility's clusters during the DotCom bubble based on the dynamic conditional correlation model

Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Analysis of forecasting capabilities of ground surfaces valuation using artificial neural networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

Social and financial aspects of the artisanal fisheries of Middle Sao Francisco River, Minas Gerais, Brazil

The presence or absence of motorized boats, partnerships and multispecies catches characterize the fisheries of Sao Francisco River, Minas Gerais, Brazil. Fishing activity based on 109 interviews, carried out in the wet (high water: February and March) and dry (low water: July and August) seasons, with professional fishermen are described. Aiming to identify the fishery income components, a covariance model was proposed, with the income as the response variable, related to the factors: fishing ground, use of motorized or paddle boat; seasonality; presence of fishing assistant, and the following covariates: capture in weight in the week Frier to the interview, fisherman experience in yrs; and distance (km) travelled for fishing. The results indicated that the main contributions to income were the absence of an engine (because of high price of the fuel), the absence of a partner (because of low capture) and the amount of fish caught by the fishermen.

Análise de risco da ocorrência de Sigatoka-negra baseada em modelos polinomiais: um estudo de caso

A Sigatoka-negra (Mycosphaerella fijiensis) ameaça os bananais comerciais em todas as áreas produtoras do mundo e provoca danos quantitativos e qualitativos na produção, acarretando sérios prejuízos financeiros. Faz-se necessário o estudo da vulnerabilidade das plantas em diversos estádios de desenvolvimento e das condições climáticas favoráveis à ocorrência da doença. Objetivou-se com este trabalho desenvolver um modelo probabilístico baseado em funções polinomiais que represente o risco de ocorrência da Sigatokanegra em função da vulnerabilidade decorrente de fatores intrínsecos à planta e ao ambiente. Realizou-se um estudo de caso, em bananal comercial localizado em Jacupiranga, Vale do Ribeira, SP, considerando o monitoramento semanal do estado da evolução da doença, séries temporais de dados meteorológicos e dados de sensoriamento remoto. Foram gerados mapas georreferenciados do risco da Sigatoka-negra em diferentes épocas do ano. Um modelo para estimar a evolução da doença a partir de imagens de satélite foi obtido com coeficiente de determinação R² igual a 0,9. A metodologia foi desenvolvida para a detecção de épocas e locais que reúnem condições favoráveis à ocorrência da Sigatoka-negra e pode ser aplicada, com os devidos ajustes, em diferentes localidades, para avaliar o risco da ocorrência da doença em polos produtores de banana.

Implementação de um sistema Collaborative Planning, Forecasting, and Replenishment em uma grande rede de fast food por meio de um prestador de serviços logísticos

A gestão colaborativa é, atualmente, um elemento-chave no contexto da gestão da cadeia de suprimentos. Neste artigo, o tema é abordado mediante a análise de um caso real, em que uma grande rede mundial de fast-food e seu prestador de serviço logístico (PSL) trabalharam conjuntamente no Brasil em um projeto-piloto para a implementação de um collaborative planning, forecasting, and replenishment (CPFR). O trabalho faz uso de uma metodologia de pesquisa-ação e apresenta as principais variáveis que influenciaram o projeto, abordando os processos necessários para a implementação e os pontos que favorecem o CPFR. Com base no caso estudado, o trabalho apresenta um conjunto de propostas sobre o papel dos agentes da cadeia em projetos dessa natureza. A gestão da cadeia de suprimentos por intermédio da coordenação direta de um PSL também permite demonstrar as possibilidades e dificuldades desse sistema, contribuindo com a visão colaborativa na cadeia de suprimentos a partir da relação entre seus agentes.

Sustainability and CDM projects in the Brazilian sugar cane sector: a discussion on the economic-financial aspects

The study discusses how the revenue from the sale of Certified Emission Reductions (CERs) can contribute to the attractiveness of investment in projects of bagasse-based cogeneration. It was observed that revenue from CERs is probably not enough to make these investments acceptable in the economic and financial aspect. However, this study speculates that Clean Development Mechanism projects will be strategic to build a positive image concerning the social responsibility and sustainability of the business in the Brazilian sugar cane sector.