6 resultados para Compactification and String Models

em Repositório digital da Fundação Getúlio Vargas - FGV


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In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

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This paper presents evidence on the key role of infrastructure in the Andean Community trade patterns. Three distinct but related gravity models of bilateral trade are used. The first model aims at identifying the importance of the Preferential Trade Agreement and adjacency on intra-regional trade, while also checking the traditional roles of economic size and distance. The second and third models also assess the evolution of the Trade Agreement and the importance of sharing a common border, but their main goal is to analyze the relevance of including infrastructure in the augmented gravity equation, testing the theoretical assumption that infrastructure endowments, by reducing trade and transport costs, reduce “distance” between bilateral partners. Indeed, if one accepts distance as a proxy for transportation costs, infrastructure development and improvement drastically modify it. Trade liberalization eliminates most of the distortions that a protectionist tariff system imposes on international business; hence transportation costs represent nowadays a considerably larger barrier to trade than in past decades. As new trade pacts are being negotiated in the Americas, borders and old agreements will lose significance; trade among countries will be nearly without restrictions, and bilateral flows will be defined in terms of costs and competitiveness. Competitiveness, however, will only be achieved by an improvement in infrastructure services at all points in the production-distribution chain.

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This paper studies the Bankruptcy Law in Latin America, focusing on the Brazilian reform. We start with a review of the international literature and its evolution on this subject. Next, we examine the economic incentives associated with several aspects of bankruptcy laws and insolvency procedures in general, as well as the trade-offs involved. After this theoretical discussion, we evaluate empirically the current stage of the quality of insolvency procedures in Latin America using data from Doing Business and World Development Indicators, both from World Bank and International Financial Statistics from IMF. We find that the region is governed by an inefficient law, even when compared with regions of lower per capita income. As theoretical and econometric models predict, this inefficiency has severe consequences for credit markets and the cost of capital. Next, we focus on the recent Brazilian bankruptcy reform, analyzing its main changes and possible effects over the economic environment. The appendix describes difficulties of this process of reform in Brazil, and what other Latin American countries can possibly learn from it.

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Behavioral finance, or behavioral economics, consists of a theoretical field of research stating that consequent psychological and behavioral variables are involved in financial activities such as corporate finance and investment decisions (i.e. asset allocation, portfolio management and so on). This field has known an increasing interest from scholar and financial professionals since episodes of multiple speculative bubbles and financial crises. Indeed, practical incoherencies between economic events and traditional neoclassical financial theories had pushed more and more researchers to look for new and broader models and theories. The purpose of this work is to present the field of research, still ill-known by a vast majority. This work is thus a survey that introduces its origins and its main theories, while contrasting them with traditional finance theories still predominant nowadays. The main question guiding this work would be to see if this area of inquiry is able to provide better explanations for real life market phenomenon. For that purpose, the study will present some market anomalies unsolved by traditional theories, which have been recently addressed by behavioral finance researchers. In addition, it presents a practical application of portfolio management, comparing asset allocation under the traditional Markowitz’s approach to the Black-Litterman model, which incorporates some features of behavioral finance.

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Asset allocation decisions and value at risk calculations rely strongly on volatility estimates. Volatility measures such as rolling window, EWMA, GARCH and stochastic volatility are used in practice. GARCH and EWMA type models that incorporate the dynamic structure of volatility and are capable of forecasting future behavior of risk should perform better than constant, rolling window volatility models. For the same asset the model that is the ‘best’ according to some criterion can change from period to period. We use the reality check test∗ to verify if one model out-performs others over a class of re-sampled time-series data. The test is based on re-sampling the data using stationary bootstrapping. For each re-sample we check the ‘best’ model according to two criteria and analyze the distribution of the performance statistics. We compare constant volatility, EWMA and GARCH models using a quadratic utility function and a risk management measurement as comparison criteria. No model consistently out-performs the benchmark.

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A quantificação do risco país – e do risco político em particular – levanta várias dificuldades às empresas, instituições, e investidores. Como os indicadores econômicos são atualizados com muito menos freqüência do que o Facebook, compreender, e mais precisamente, medir – o que está ocorrendo no terreno em tempo real pode constituir um desafio para os analistas de risco político. No entanto, com a crescente disponibilidade de “big data” de ferramentas sociais como o Twitter, agora é o momento oportuno para examinar os tipos de métricas das ferramentas sociais que estão disponíveis e as limitações da sua aplicação para a análise de risco país, especialmente durante episódios de violência política. Utilizando o método qualitativo de pesquisa bibliográfica, este estudo identifica a paisagem atual de dados disponíveis a partir do Twitter, analisa os métodos atuais e potenciais de análise, e discute a sua possível aplicação no campo da análise de risco político. Depois de uma revisão completa do campo até hoje, e tendo em conta os avanços tecnológicos esperados a curto e médio prazo, este estudo conclui que, apesar de obstáculos como o custo de armazenamento de informação, as limitações da análise em tempo real, e o potencial para a manipulação de dados, os benefícios potenciais da aplicação de métricas de ferramentas sociais para o campo da análise de risco político, particularmente para os modelos qualitativos-estruturados e quantitativos, claramente superam os desafios.