942 resultados para equilibrium asset pricing models with latent variables
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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia
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O processo de globalização, na esfera dos mercados financeiros, exigiu às instituições bancárias opções de investimento estratégico na plataforma internacional. O movimento de implantação dos bancos portugueses no estrangeiro acompanhou esse processo, permitindo a oferta de serviços bancários de captação e financiamento nos principais mercados de destino das exportações e emigração. A presente dissertação tem como objetivo o estudo do processo de internacionalização do setor bancário português centrado na seguinte questão geral de investigação: “Quais os fatores determinantes das variáveis que caraterizam a evolução do setor bancário português no exterior?” O desenvolvimento desta questão é conduzido através da construção de um modelo explicativo dos impactos de um conjunto de determinantes, selecionados a partir da revisão de literatura, sobre os indicadores que traduzem a dinâmica do negócio bancário no exterior. Neste contexto, pretendeu-se obter evidência empírica desses efeitos através de uma metodologia que consiste na estimação de modelos de dados em painel, utilizando uma amostra de seis bancos com relevância ao nível de investimento no mercado externo relativos ao período compreendido entre 2004 e 2014. Os resultados empíricos sugerem a existência de relações estatisticamente significativas entre as variáveis consideradas nos modelos. Foram encontrados indícios que associam consistentemente as variáveis emigração, Investimento Direto Estrangeiro, Produto Interno Bruto em Portugal e nos países de acolhimento, ativo bancário e inflação, com a evolução da atividade bancária no exterior. Adicionalmente, os resultados revelam que o desemprego e o rácio do crédito em relação ao ativo são estatisticamente significativos na sua influência sobre o indicador da rendibilidade dos bancos. Conclui-se que a significância dos fatores selecionados permite explicar o comportamento dos indicadores de negócio no exterior para os bancos estudados e, consequentemente, a validade do modelo de análise proposto. No entanto, não se exclui que outros elementos explicativos não ponderados no estudo tenham igualmente preponderância explicativa no processo de internacionalização do setor bancário.
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INTRODUCTION: There are several risk scores for stratification of patients with ST-segment elevation myocardial infarction (STEMI), the most widely used of which are the TIMI and GRACE scores. However, these are complex and require several variables. The aim of this study was to obtain a reduced model with fewer variables and similar predictive and discriminative ability. METHODS: We studied 607 patients (age 62 years, SD=13; 76% male) who were admitted with STEMI and underwent successful primary angioplasty. Our endpoints were all-cause in-hospital and 30-day mortality. Considering all variables from the TIMI and GRACE risk scores, multivariate logistic regression models were fitted to the data to identify the variables that best predicted death. RESULTS: Compared to the TIMI score, the GRACE score had better predictive and discriminative performance for in-hospital mortality, with similar results for 30-day mortality. After data modeling, the variables with highest predictive ability were age, serum creatinine, heart failure and the occurrence of cardiac arrest. The new predictive model was compared with the GRACE risk score, after internal validation using 10-fold cross validation. A similar discriminative performance was obtained and some improvement was achieved in estimates of probabilities of death (increased for patients who died and decreased for those who did not). CONCLUSION: It is possible to simplify risk stratification scores for STEMI and primary angioplasty using only four variables (age, serum creatinine, heart failure and cardiac arrest). This simplified model maintained a good predictive and discriminative performance for short-term mortality.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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Introduction The primary strategy for tuberculosis control involves identifying individuals with latent tuberculosis. This study aimed to estimate the prevalence of latent tuberculosis in chronic kidney disease (CKD) patients who were undergoing hemodialysis in Campo Grande, State of Mato Grosso do Sul, Brazil, to characterize the sociodemographic and clinical profiles of patients with latent tuberculosis, to verify the association between sociodemographic and clinical characteristics and the occurrence of latent tuberculosis, and to monitor patient adherence to latent tuberculosis treatment. Methods This epidemiological study involved 418 CKD patients who were undergoing hemodialysis and who underwent a tuberculin skin test. Results The prevalence of latent tuberculosis was 10.3%. The mean patient age was 53.43±14.97 years, and the patients were predominantly men (63.9%). The population was primarily Caucasian (58.6%); half (50%) were married, and 49.8% had incomplete primary educations. Previous contact with tuberculosis patients was reported by 80% of the participants. Treatment adherence was 97.7%. Conclusions We conclude that the prevalence of latent tuberculosis in our study population was low. Previous contact with patients with active tuberculosis increased the occurrence of latent infection. Although treatment adherence was high in this study, it is crucial to monitor tuberculosis treatment administered to patients in health services to maintain this high rate.
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Tese de Doutoramento em Ciências Empresariais.
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The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.
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Studies of the spin, parity and tensor couplings of the Higgs boson in the H→ZZ∗→4ℓ , H→WW∗→eνμν and H→γγ decay processes at the LHC are presented. The investigations are based on 25 fb−1 of pp collision data collected by the ATLAS experiment at s√=7 TeV and s√=8 TeV. The Standard Model (SM) Higgs boson hypothesis, corresponding to the quantum numbers JP=0+, is tested against several alternative spin scenarios, including non-SM spin-0 and spin-2 models with universal and non-universal couplings to fermions and vector bosons. All tested alternative models are excluded in favour of the SM Higgs boson hypothesis at more than 99.9% confidence level. Using the H→ZZ∗→4ℓ and H→WW∗→eνμν decays, the tensor structure of the HVV interaction in the spin-0 hypothesis is also investigated. The observed distributions of variables sensitive to the non-SM tensor couplings are compatible with the SM predictions and constraints on the non-SM couplings are derived.
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Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the "best fit" model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate.
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When habits are introduced multiplicatively in a capital accumulation model, the consumers' objective function might fail to be concave. In this paper we provide conditions aimed at guaranteeing the existence of interior solutions to the consumers' problem. We also characterize the equilibrium path of two growth models with multiplicative habits: the internal habit formation model, where individual habits coincide with own past consumption, and the external habit formation (or catching-up with the Joneses) model, where habits arise from the average past consumption in the economy. We show that the introduction of external habits makes the equilibrium path inefficient during the transition towards the balanced growth path. We characterize in this context the optimal tax policy.
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Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.
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Expectations about the future are central for determination of current macroeconomic outcomes and the formulation of monetary policy. Recent literature has explored ways for supplementing the benchmark of rational expectations with explicit models of expectations formation that rely on econometric learning. Some apparently natural policy rules turn out to imply expectational instability of private agents’ learning. We use the standard New Keynesian model to illustrate this problem and survey the key results about interest-rate rules that deliver both uniqueness and stability of equilibrium under econometric learning. We then consider some practical concerns such as measurement errors in private expectations, observability of variables and learning of structural parameters required for policy. We also discuss some recent applications including policy design under perpetual learning, estimated models with learning, recurrent hyperinflations, and macroeconomic policy to combat liquidity traps and deflation.
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In previous work we have applied the environmental multi-region input-output (MRIO) method proposed by Turner et al (2007) to examine the ‘CO2 trade balance’ between Scotland and the Rest of the UK. In McGregor et al (2008) we construct an interregional economy-environment input-output (IO) and social accounting matrix (SAM) framework that allows us to investigate methods of attributing responsibility for pollution generation in the UK at the regional level. This facilitates analysis of the nature and significance of environmental spillovers and the existence of an environmental ‘trade balance’ between regions. While the existence of significant data problems mean that the quantitative results of this study should be regarded as provisional, we argue that the use of such a framework allows us to begin to consider questions such as the extent to which a devolved authority like the Scottish Parliament can and should be responsible for contributing to national targets for reductions in emissions levels (e.g. the UK commitment to the Kyoto Protocol) when it is limited in the way it can control emissions, particularly with respect to changes in demand elsewhere in the UK. However, while such analysis is useful in terms of accounting for pollution flows in the single time period that the accounts relate to, it is limited when the focus is on modelling the impacts of any marginal change in activity. This is because a conventional demand-driven IO model assumes an entirely passive supply-side in the economy (i.e. all supply is infinitely elastic) and is further restricted by the assumption of universal Leontief (fixed proportions) technology implied by the use of the A and multiplier matrices. In this paper we argue that where analysis of marginal changes in activity is required, a more flexible interregional computable general equilibrium approach that models behavioural relationships in a more realistic and theory-consistent manner, is more appropriate and informative. To illustrate our analysis, we compare the results of introducing a positive demand stimulus in the UK economy using both IO and CGE interregional models of Scotland and the rest of the UK. In the case of the latter, we demonstrate how more theory consistent modelling of both demand and supply side behaviour at the regional and national levels affect model results, including the impact on the interregional CO2 ‘trade balance’.
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Rebound is the extent to which improvements in energy efficiency fail to translate fully into reductions in energy use because of the implicit fall in the price of energy, when measured in efficiency units. This paper discusses aspects of the rebound effect that are introduced once energy is considered as a domestically produced commodity. A partial equilibrium approach is adopted in order to incorporate both energy use and production in a conceptually tractable way. The paper explores analytically two interesting results revealed in previous numerical simulations. The first is the possibility that energy use could fall by more than the implied improvement in efficiency. This corresponds to negative rebound. The second is the finding that the short-run rebound value can be greater than the corresponding long-run value.
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BACKGROUND: Zebrafish is a clinically-relevant model of heart regeneration. Unlike mammals, it has a remarkable heart repair capacity after injury, and promises novel translational applications. Amputation and cryoinjury models are key research tools for understanding injury response and regeneration in vivo. An understanding of the transcriptional responses following injury is needed to identify key players of heart tissue repair, as well as potential targets for boosting this property in humans. RESULTS: We investigated amputation and cryoinjury in vivo models of heart damage in the zebrafish through unbiased, integrative analyses of independent molecular datasets. To detect genes with potential biological roles, we derived computational prediction models with microarray data from heart amputation experiments. We focused on a top-ranked set of genes highly activated in the early post-injury stage, whose activity was further verified in independent microarray datasets. Next, we performed independent validations of expression responses with qPCR in a cryoinjury model. Across in vivo models, the top candidates showed highly concordant responses at 1 and 3 days post-injury, which highlights the predictive power of our analysis strategies and the possible biological relevance of these genes. Top candidates are significantly involved in cell fate specification and differentiation, and include heart failure markers such as periostin, as well as potential new targets for heart regeneration. For example, ptgis and ca2 were overexpressed, while usp2a, a regulator of the p53 pathway, was down-regulated in our in vivo models. Interestingly, a high activity of ptgis and ca2 has been previously observed in failing hearts from rats and humans. CONCLUSIONS: We identified genes with potential critical roles in the response to cardiac damage in the zebrafish. Their transcriptional activities are reproducible in different in vivo models of cardiac injury.