Saddle-point approach: backtesting VaR models in the presence of extreme losses

The Basel Committee for Banking Supervision requires every financial institution to carry out efficient Risk Management practices, so that these are able to face adverse days in the market and, thus, avoid another potential meltdown of the financial system, such as the 'Black Monday' in 1987 or the 'Subprime' crisis in 2007. To do so, traditional backtesting techniques assess the quality of commercial banks’ risk forecasts based on the number of the exceedances. However, these backtests are not sensitive to the size of the exceedances, which could lead to inaccurate risk models to be accepted. This way, this dissertation presents the Saddle-point backtest, a size-based procedure developed by Wong (2008) that evaluates risk models through the Tail-Risk-of-VaR. This approach is believed to constitute a reliable size counterpart to the Basel II Agreements, hence deserving an important role in backtesting. However, the Saddle-point backtest shows some drawbacks regarding its application to non-parametric risk models, which is explored throughout this dissertation’s empirical analysis.O Comité de Basileia para a Supervisão Bancária requer a todas as instituições financeiras que levem a cabo práticas de Gestão de Risco eficientes, de modo a que estas sejam capazes de enfrentar dias adversos no mercado e, desta forma, evitar outro eventual colapso do sistema financeiro, tal como a 'Segunda-feira Negra' em 1987 ou a crise do 'Subprime' em 2007. Para tal, as técnicas tradicionais de avaliação de modelos de risco aferem a qualidade das previsões dos bancos com base no número de excedências. No entanto, estes métodos não são sensíveis ao tamanho das excedências, o que pode levar a que modelos de risco pouco fiáveis sejam aceites. Assim sendo, esta dissertação apresenta o teste de Saddle-point, um procedimento baseado no tamanho das excedências desenvolvido por Wong (2008), que avalia modelos de risco através do Risco-da-Cauda do Valor em Risco. Crê-se que esta abordagem baseada no tamanho das excedências constitui uma fiável contraparte dos Acordos de Basileia II, merecendo, portanto, desempenhar um papel importante na avaliação de modelos de risco. No entanto, o teste de Saddle-point apresenta algumas falhas no que toca à sua aplicação a modelos de risco não paramétricos, algo que é explorado no decorrer da análise empírica desta dissertação

Diagnóstico de manifestações patológicas em pavimento flexivel / Diagnosis of patologic manisfestations in flexivel pavimento

A pesquisa desenvolvida apresenta um estudo de caso de duas vias, identificadas como Secundária 2A e Secundária 2B, executadas no interior de um condomínio de galpões e áreas de armazenamento, localizado no Município do Cabo de Santo Agostinho - PE. Apesar das vias em estudo disporem pouco tempo de utilização foi identificado danos ao longo do pavimento, conduzindo assim à necessidade de conhecimento dos fatores responsáveis. O tráfego considerado no dimensionamento do projeto originalmente concebido para execução das vias foi N = 5 x 106, sendo então este tráfego considerado nas análises. Para avaliação das condições dos pavimentos foram realizados levantamentos deflectométricos com o uso de equipamento do tipo FWD e abertura de janelas de inspeção. Para cada janela de inspeção foram avaliadas as camadas de reforço do subleito, sub-base e base. A camada de revestimento asfáltico não foi avaliada por apresentar-se, em muitos pontos, bastante danificada e contaminada com o solo local. Os resultados obtidos indicam a utilização de materiais de baixa qualidade e o emprego de procedimentos de execução inadequados. Estas constatações foram feitas a partir da obtenção de dados de deflexões excessivas, camadas muito espessas, reduzidos graus de compactação, elevada umidade e solo com baixa capacidade de suporte e alta plasticidade. 

Carbamazepine inhibits angiotensin I-converting enzyme, linking it to the pathogenesis of temporal lobe epilepsy

We find that a common mutation that increases angiotensin I-converting enzyme activity occurs with higher frequency in male patients suffering from refractory temporal lobe epilepsy. However, in their brains, the activity of the enzyme is downregulated. As an explanation, we surprisingly find that carbamazepine, commonly used to treat epilepsy, is an inhibitor of the enzyme, thus providing a direct link between epilepsy and the renin-angiotensin and kallikrein-kinin systems. Translational Psychiatry (2012) 2, e93; doi:10.1038/tp.2012.21; published online 13 March 2012INNTConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Universidade Federal de São Paulo, Dept Biophys, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Pathol, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Neurol & Neurosurg, BR-04023032 São Paulo, BrazilUniv São Paulo, Sch Arts Sci & Humanities, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Sci & Technol, BR-04023032 São Paulo, BrazilNove de Julho Univ UNINOVE, Dept Rehabil Sci, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Biophys, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Pathol, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Neurol & Neurosurg, BR-04023032 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Sci & Technol, BR-04023032 São Paulo, BrazilWeb of Scienc

SARS-CoV-2 introductions and early dynamics of the epidemic in Portugal

Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration with more than 50 laboratories distributed nationwide. Methods By applying recent phylodynamic models that allow integration of individual-based travel history, we reconstructed and characterized the spatio-temporal dynamics of SARSCoV-2 introductions and early dissemination in Portugal. Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from European countries (namely the United Kingdom, Spain, France, Italy, and Switzerland), which were consistent with the countries with the highest connectivity with Portugal. Although most introductions were estimated to have occurred during early March 2020, it is likely that SARS-CoV-2 was silently circulating in Portugal throughout February, before the first cases were confirmed. Conclusions Here we conclude that the earlier implementation of measures could have minimized the number of introductions and subsequent virus expansion in Portugal. This study lays the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlights the need for systematic and geographically-representative genomic surveillance.We gratefully acknowledge to Sara Hill and Nuno Faria (University of Oxford) and Joshua Quick and Nick Loman (University of Birmingham) for kindly providing us with the initial sets of Artic Network primers for NGS; Rafael Mamede (MRamirez team, IMM, Lisbon) for developing and sharing a bioinformatics script for sequence curation (https://github.com/rfm-targa/BioinfUtils); Philippe Lemey (KU Leuven) for providing guidance on the implementation of the phylodynamic models; Joshua L. Cherry (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health) for providing guidance with the subsampling strategies; and all authors, originating and submitting laboratories who have contributed genome data on GISAID (https://www.gisaid.org/) on which part of this research is based. The opinions expressed in this article are those of the authors and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government. This study is co-funded by Fundação para a Ciência e Tecnologia and Agência de Investigação Clínica e Inovação Biomédica (234_596874175) on behalf of the Research 4 COVID-19 call. Some infrastructural resources used in this study come from the GenomePT project (POCI-01-0145-FEDER-022184), supported by COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).info:eu-repo/semantics/publishedVersio

Lidar Observations in South America. Part I - Mesosphere and Stratosphere

South America covers a large area of the globe and plays a fundamental function in its climate change, geographical features, and natural resources. However, it still is a developing area, and natural resource management and energy production are far from a sustainable framework, impacting the air quality of the area and needs much improvement in monitoring. There are significant activities regarding laser remote sensing of the atmosphere at different levels for different purposes. Among these activities, we can mention the mesospheric probing of sodium measurements and stratospheric monitoring of ozone, and the study of wind and gravity waves. Some of these activities are long-lasting and count on the support from the Latin American Lidar Network (LALINET). We intend to pinpoint the most significant scientific achievements and show the potential of carrying out remote sensing activities in the continent and show its correlations with other earth science connections and synergies. In Part I of this chapter, we will present an overview and significant results of lidar observations in the mesosphere and stratosphere. Part II will be dedicated to tropospheric observations

Lidar Observations in South America. Part II - Troposphere

In Part II of this chapter, we intend to show the significant advances and results concerning aerosols’ tropospheric monitoring in South America. The tropospheric lidar monitoring is also supported by the Latin American Lidar Network (LALINET). It is concerned about aerosols originating from urban pollution, biomass burning, desert dust, sea spray, and other primary sources. Cloud studies and their impact on radiative transfer using tropospheric lidar measurements are also presented

Maize Yield Prediction with Machine Learning, Spectral Variables and Irrigation Management

Predicting maize yield using spectral information, temperature, and different irrigation management through machine learning algorithms provide information in a fast, accurate, and non-destructive way. The use of multispectral sensor data coupled with irrigation management in maize allows further exploration of water behavior and its relationship with changes in spectral bands presented by the crop. Thus, the objective of this study was to evaluate, by means of multivariate statistics and machine learning techniques, the relationship between irrigation management and spectral bands in predicting maize yields. Field experiments were carried out over two seasons (first and second seasons) in a randomized block design with four treatments (control and three additional irrigation levels) and eighteen sample repetitions. The response variables analyzed were vegetation indices (IVs) and crop yield (GY). Measurement of spectral wavelengths was performed with the Sensefly eBee RTK, with autonomous flight control. The eBee was equipped with the Parrot Sequoia multispectral sensor acquiring reflectance at the wavelengths of green (550 nm ± 40 nm), red (660 nm ± 40 nm), red-edge (735 nm ± 10 nm), and NIR (790 nm ± 40 nm). The blue length (496 nm) was obtained by additional RGB imaging. Data were subjected to Pearson correlations (r) between the evaluated variables represented by a correlation and scatter plot. Subsequently, the canonical analysis was performed to verify the interrelationship between the variables evaluated. Data were also subjected to machine learning (ML) analysis, in which three different input dataset configurations were tested: using only irrigation management (IR), using irrigation management and spectral bands (SB+IR), and using irrigation management, spectral bands, and temperature (IR+SB+Temp). ML models used were: Artificial Neural Network (ANN), M5P Decision Tree (J48), REPTree Decision Tree (REPT), Random Forest (RF), and Support Vector Machine (SVM). A multiple linear regression (LR) was tested as a control model. Our results revealed that Random Forest has higher accuracy in predicting grain yield in maize, especially when associated with the inputs SB+IR and SB+IR+Temp

Unveiling geographical gradients of species richness from scant occurrence data

Aim: Despite longstanding investigation, the gradients of species richness remain unknown for most taxa because of shortfalls in knowledge regarding the quantity and distribution of species. Here, we explore the ability of a geostatistical interpolation model, regression-kriging, to recover geographical gradients of species richness. We examined the technique with an in silico gradient of species richness and evaluated the effect of different configurations of knowledge shortfalls. We also took the same approach for empirical data with large knowledge gaps, the infraorder Furnariides of suboscine birds. Innovation: Regression-kriging builds upon two cornerstones of geographical gradients of biodiversity, the spatial autocorrelation of species richness and the conspicuous association of species with environmental factors. With this technique, we recovered a simulated gradient of richness using < 0.01% of sampling sites across the region. The accuracy of the regression-kriging is higher when input samples are more evenly distributed throughout the geographical space rather than the environmental space of the target region. Moreover, the accuracy of this method is more sensitive to the sufficiency of sampling effort within cells than to the quantity of sampled localities. For Furnariides birds, regression-kriging provided a geographical gradient of species richness that resembles purported patterns of other groups and illustrated ubiquitous shortfalls of knowledge about bird diversity. Main conclusions: Geostatistical interpolation, such as regression-kriging, might be a useful tool to overcome shortfalls in knowledge that plague our understanding of geographical gradients of biodiversity, with many applications in ecology, palaeoecology and conservation. © 2020 John Wiley & Sons Lt