December 2006/January 2007: Space Shuttle Discovery Launch

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Cointegração e price discovery do risco soberano brasileiro

A lei do preço único afirma que o mesmo ativo negociado em diferentes mercados deve apresentar preços equivalentes. Este trabalho busca verificar se o risco de crédito soberano brasileiro negociado no mercado internacional é precificado de forma semelhante tanto nos tradicionais mercados de títulos quanto no novo e crescente mercado de derivativos de crédito. Adicionalmente, utiliza-se a análise de Price Discovery para examinar qual dos mercados se move mais rapidamente em resposta às mudanças nas condições de crédito da economia brasileira. A análise empírica é feita por meio de modelos de séries de tempo, mais especificamente análise de cointegração e vetor de correção de erros. Os resultados confirmam a predição teórica da lei do preço único de que o risco de crédito brasileiro, tanto nos mercados de títulos quanto no mercado de derivativos de crédito, movem-se juntos no longo prazo. Por fim, a maior parte do Price Discovery ocorre no mercado de derivativos de crédito.

Price discovery in dual-class shares across multiple markets

We extend the standard price discovery analysis to estimate the information share of dual-class shares across domestic and foreign markets. By examining both common and preferred shares, we aim to extract information not only about the fundamental value of the rm, but also about the dual-class premium. In particular, our interest lies on the price discovery mechanism regulating the prices of common and preferred shares in the BM&FBovespa as well as the prices of their ADR counterparts in the NYSE and in the Arca platform. However, in the presence of contemporaneous correlation between the innovations, the standard information share measure depends heavily on the ordering we attribute to prices in the system. To remain agnostic about which are the leading share class and market, one could for instance compute some weighted average information share across all possible orderings. This is extremely inconvenient given that we are dealing with 2 share prices in Brazil, 4 share prices in the US, plus the exchange rate (and hence over 5,000 permutations!). We thus develop a novel methodology to carry out price discovery analyses that does not impose any ex-ante assumption about which share class or trading platform conveys more information about shocks in the fundamental price. As such, our procedure yields a single measure of information share, which is invariant to the ordering of the variables in the system. Simulations of a simple market microstructure model show that our information share estimator works pretty well in practice. We then employ transactions data to study price discovery in two dual-class Brazilian stocks and their ADRs. We uncover two interesting ndings. First, the foreign market is at least as informative as the home market. Second, shocks in the dual-class premium entail a permanent e ect in normal times, but transitory in periods of nancial distress. We argue that the latter is consistent with the expropriation of preferred shareholders as a class.

KittyCat: a cognitive model of structure-form discovery

Cognition is a core subject to understand how humans think and behave. In that sense, it is clear that Cognition is a great ally to Management, as the later deals with people and is very interested in how they behave, think, and make decisions. However, even though Cognition shows great promise as a field, there are still many topics to be explored and learned in this fairly new area. Kemp & Tenembaum (2008) tried to a model graph-structure problem in which, given a dataset, the best underlying structure and form would emerge from said dataset by using bayesian probabilistic inferences. This work is very interesting because it addresses a key cognition problem: learning. According to the authors, analogous insights and discoveries, understanding the relationships of elements and how they are organized, play a very important part in cognitive development. That is, this are very basic phenomena that allow learning. Human beings minds do not function as computer that uses bayesian probabilistic inferences. People seem to think differently. Thus, we present a cognitively inspired method, KittyCat, based on FARG computer models (like Copycat and Numbo), to solve the proposed problem of discovery the underlying structural-form of a dataset.

Macroeconomic announcements, price discovery, and order flow efects in the stock market: evidence from incomplete data and multiple financial markets

This paper investigates heterogeneity in the market assessment of public macro- economic announcements by exploring (jointly) two main mechanisms through which macroeconomic news might enter stock prices: instantaneous fundamental news im- pacts consistent with the asset pricing view of symmetric information, and permanent order ow e¤ects consistent with a microstructure view of asymmetric information related to heterogeneous interpretation of public news. Theoretical motivation and empirical evidence for the operation of both mechanisms are presented. Signi cant in- stantaneous news impacts are detected for news related to real activity (including em- ployment), investment, in ation, and monetary policy; however, signi cant order ow e¤ects are also observed on employment announcement days. A multi-market analysis suggests that these asymmetric information e¤ects come from uncertainty about long term interest rates due to heterogeneous assessments of future Fed responses to em- ployment shocks.

Price discovery using a regime-sensitive cointegration approach

This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.

The historic religious buildings of Ribeira Grande: implementation of christian models in the early colonies, 15th till 17th century, on the example of Cape Verde Islands

Rui Carita

SysPRE: systematized process for requirements engineering in knowledge discovery projects

The domain of Knowledge Discovery (KD) and Data Mining (DM) is of growing importance in a time where more and more data is produced and knowledge is one of the most precious assets. Having explored both the existing underlying theory, the results of the ongoing research in academia and the industry practices in the domain of KD and DM, we have found that this is a domain that still lacks some systematization. We also found that this systematization exists to a greater degree in the Software Engineering and Requirements Engineering domains, probably due to being more mature areas. We believe that it is possible to improve and facilitate the participation of enterprise stakeholders in the requirements engineering for KD projects by systematizing requirements engineering process for such projects. This will, in turn, result in more projects that end successfully, that is, with satisfied stakeholders, including in terms of time and budget constraints. With this in mind and based on all information found in the state-of-the art, we propose SysPRE - Systematized Process for Requirements Engineering in KD projects. We begin by proposing an encompassing generic description of the KD process, where the main focus is on the Requirements Engineering activities. This description is then used as a base for the application of the Design and Engineering Methodology for Organizations (DEMO) so that we can specify a formal ontology for this process. The resulting SysPRE ontology can serve as a base that can be used not only to make enterprises become aware of their own KD process and requirements engineering process in the KD projects, but also to improve such processes in reality, namely in terms of success rate.

Fé & Cia. LTDA: consumo religioso na sociedade contemporânea

The present work is an exercise of analysis from the cultural exercises related to movie high one of its raised status more with the deity, the human being surrenders it Religion leaving puzzleds the prophets of its end. The purpose of this work is to show that the religious phenomenon is one of the essential components of the socialization human being. The religious dimension, although to have been kept out of society in modernity - it was cybernetics, is an indispensable compassing to guide the human being in the discovery of its true existencial direction. For this, to attenuate the legacy without appropriate title, overwhelming and despairing of the producing and consumer goods society, it is indispensable to add as basic part to the practical one of the religion. And this practice is specify at the acquirement as of commodities objects , than it is to they are consecrate, exercising um magical power under the assistants from the religion. The fair religious Expo Religious, like the Expo Crest (fair as of commodities and service of the Evangelist) and the one Expo Catholic (fair as of commodities and service of the Catholics), appears at the I initiate from the century 21 at the association Brazilian about to cater the litigation of the market religious at every their segments. The and objective of this research is bring forward those two fairs in the format as of Expo and your contribution at the dynamic from the religion crest at the association he acts

Chicken skeletal muscle-associated macroarray for gene discovery

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)