Evidence of speculative bubbles on the BOVESPA : an application of the Kalman filter

A existência de bolhas nos preçoos dos ativos é um assunto de grande importância para governos e investidores devido às suas possíveis repercussões. No caso das ações, a presença de bolha de preços pode ser constatada pela comparação dos preços e dos respectivos dividendos no longo prazo. Este trabalho buscou verificar a ocorrência de bolhas de preços no mercado acionário brasileiro, através da comparação do IBOVESPA, como índice de preço, e um índice de dividendos distribuídos, construído a partir da metodologia do IBOVESPA. A bolha foi considerada um vetor estado não observável em um modelo estado-espaço e foi estimada com o filtro de Kalman. Os resultados foram comparados com o modelo de valor presente e o modelo de intrinsic bubbles (Froot & Obstfeld, 1991). Apesar de o modelo constatar a presença de bolhas, o modelo de intrinsic bubbles (Froot & Obstfeld, 1991) apresentou resultado semelhante e maior precisão. _________________________________________________________________________________ ABSTRACTThe existence of bubbles in asset prices is a matter of great importance to governments and investors due to possible serious effects they may have on economies. In the case of shares, the presence of a price bubble can be seen by comparing prices and dividends in the long run. This study aimed to assess the occurrence of price bubbles in the Brazilian stock market, by comparing the IBOVESPA as price index and an index of dividends, built based on the methodology of IBOVESPA. The bubble was considered a unobserved state vector in a state-space model and was estimated using the Kalman filter. The results were compared with the standard present value model and intrinsic bubbles model (Froot and Obstfeld, 1991). Although the model establishes the presence of bubbles, the intrinsic bubbles model (Froot and Obstfeld, 1991) showed similar results with greater accuracy

EFEITO MANADA NO MERCADO DE CAPITAIS: UM ESTUDO COM GERENTES DE BANCOS PÚBLICOS DO DISTRITO FEDERAL

O objetivo com este trabalho foi verificar se os gerentes de bancos estatais, autorizados a recomendar investimentos, sofrem influência de opiniões externas em decisões de aquisição de ativos financeiros. A pesquisa se justifica em razão da necessidade de se saber se mesmo agentes com elevado conhecimento em finanças e acesso à informação poderiam sofrer influência da opinião emitida por analistas de mercado no momento da decisão de compra desses ativos. Para tal, foram aplicados 80 questionários a gerentes autorizados a recomendar investimentos, em três bancos públicos localizados no Distrito Federal. Para a operacionalização estatística, foram utilizados testes de hipóteses para se verificar se existiam diferenças significativas entre a escolha de gerentes sob influência externa e de outros sem essa interferência. Concluiu-se que a opinião do analista não influencia a forma de qualificar as ações da empresa, porém foram achadas fortes relações entre a opção de compra e a opinião do analista. Palavras-chave: Finanças comportamentais. Efeito manada. Assimetria de informação

Potenciais interações de drogas em pacientes de terapia antirretroviral: uma revisão integrativa: Potential drug interactions in antiretroviral therapy patients: an integrative review

Possíveis interações medicamentosas devem ser levadas em consideração ao selecionar um regime antirretroviral. Uma revisão detalhada dos medicamentos concomitantes pode ajudar na criação de um regime que minimize as interações indesejáveis. O potencial para interações medicamentosas deve ser avaliado quando qualquer novo medicamento (incluindo agentes de venda livre) é adicionado a um regime antirretroviral existente. A maioria das interações medicamentosas com medicamentos antirretroviral é mediada por inibição ou indução do metabolismo hepático de medicamentos. Este estudo trata-se de uma revisão integrativa, cujo objetivo foi compreender as possíveis interações de drogas em pacientes com infecção pelo HIV em processo de terapia antirretroviral. Após análise dos dados, concluiu-se que há riscos reais de interações medicamentosas a partir do uso de 5 ou mais medicamentos, por um tempo superior a seis anos. Os principais riscos apontados nesse sentido foram interferência na resposta terapêutica, aumento de reações adversas toxidade nos sistemas cardiovascular e nervoso central e dificuldades para detecção de resistência do HIV aos medicamentos antirretrovirais

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications