Non-Gaussian structural time series models.

This thesis aims to develop a class of state space models for non-Gaussian time series. Our models are based on distributions of the exponential family, such as the Poisson, the negative-binomial, the binomial and the gamma. In these distributions the mean is allowed to change over time through a mechanism which mimics a random walk. By adopting a closed sampling analysis we are able to derive finite dimensional filters, similar to the Kalman filter. These are then used to construct the likelihood function and to make forecasts of future observations. In fact for all the specifications here considered we have been able to show that the predictions give rise to schemes based on an exponentially weighted moving average (EWMA). The models may be extended to include explanatory variables via the kind of link functions that appear in GLIM models. This enables nonstochastic slope and seasonal components to be included. The Poisson, negative binomial and bivariate Poisson models are illustrated by considering applications to real data. Monte Carlo experiments are also conducted in order to investigate properties of maximum likelihood estimators and power studies of a post sample predictive test developed for the Poisson model

Interest rate risk measurement in Brazilian sovereign markets

Os mercados emergentes de renda fixa são alternativas interessantes para investimentos. Devido ao elevado nível de incerteza existente em tais mercados, a mensuração dos riscos de mercado de uma carteira de investimentos é fundamental para que se evite um nível elevado de perdas. Uma das medidas de risco de mercado mais utilizadas é o Value at Risk, baseado na distribuição de probabilidades de perdas-ganhos da carteira sob análise. A estimação desta distribuição requer, no entanto, a estimação prévia da distribuição de pro-babilidades das variações da estrutura a termo da taxa de juros. Uma possibilidade interessante para a estimação de tal distribuição é efetuar uma decomposição da função de spread da estrutura a termo em uma combinação linear de Polinômios de Legendre. Exemplos numéricos do mercado internacional de títulos soberanos brasileiros são apresentados para ilustrar o uso prático desta nova metodologia.Fixed income emerging markets are an interesting investment alternative. Measuring market risks is mandatory in order to avoid unexpected huge losses. The most used market risk measure is the Value at Risk, based on the profit-loss probability distribution of the portfolio under consideration. Estimating this probability distribution requires the prior estimation of the probability distribution of term structures of interest rates. An interesting possibility is to estimate term structures using a decomposition of the spread function into a linear combination of Legendre polynomials. Numerical examples from the Brazilian sovereign fixed income international market illustrate the practical use of the methodology

Estimação de provisões IBNR – incurred but not reported - no mercado de seguros Brasileiro utilizando modelos GAS Estimation of IBNR provisions - incurred but not reported - in the Brazilian insurance market using GAS models

Neste artigo foram feitas aplicações dos modelos GAS, apresentados inicialmente em 2008 pelos pesquisadores Creal, Koopman e Lucas, distintas das até então publicadas na literatura. Utilizamos os modelos GAS com distribuições Gama e Log-normal para modelar as estruturas de dependências entre os dados de seguros e estimamos as reservas IBNR para duas coberturas (Casco e RCFV). Os dados em questão se apresentam em um formato chamado triângulo de run-off, cujos valores estão expostos como uma série temporal em painel. Para avaliar a aderência dos modelos GAS propostos utilizamos o método Chain-ladder (Mack, 1993) como benchmark. Os critérios de avaliação (MAPE, EQM e R2), a dimensão das reservas estimadas e os cocientes de variação apontaram para uma maior aderência dos modelos GAS aos dados de seguros de automóveis

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Estimação do Impacto do El Niño/La Niña na Intensidade dos Ventos do Nordeste Brasileiro

A energia eólica é hoje uma das mais promissoras fontes de energia do mundo por ser limpa e abundante. O estudo de fenômenos que estão relacionados com alterações na circulação atmosférica, como o El Niño, são de extrema importância pela possibilidade de afetarem a geração eólica. A fim de explorar o possível efeito de tais fenômenos nos ventos da região Nordeste do Brasil, é realizada uma análise estatística para a quantificação desse efeito através do modelo Generalized Autoregressive Score (GAS). Este permite a modelagem de séries temporais para diferentes distribuições de probabilidade. Nesse estudo, o modelo GAS é aplicado às séries de velocidade do vento a partir da distribuição Gama. Os resultados do modelo mostraram que o El Niño possui influência no comportamento do vento, ainda que esta seja pequena em magnitud