Modelo de avaliação de risco no sector bancário português

A globalização dos sistemas financeiros, ao longo dos anos, tem estimulado uma crescente necessidade de supervisão bancária nas instituições financeiras. O Comité de Supervisão Bancária de Basileia tem tido um papel crucial nesta área, estabelecendo princípios por via dos seus acordos entre as várias entidades nacionais de regulação e supervisão das maiores economias mundiais. Em 1988, foi criado o Acordo de Basileia (Basileia I) pelo Comité de Supervisão Bancária de forma a harmonizar os padrões de supervisão bancária. Este acordo estabeleceu mínimos de solvabilidade para o sistema bancário internacional no sentido de reforçar a sua solidez e estabilidade. Com o desenvolvimento de novas potências económicas e novas necessidades regulamentares, em Junho de 2004, foi publicado o novo Acordo de Capital – o Basileia II. Este acordo pretendia tornar os requisitos de capital mais sensíveis ao risco, promover a atuação das autoridades de supervisão e a disciplina de mercado (através do seu Pilar II) e encorajar a capacidade de cada instituição mensurar e gerir o seu risco. Em Setembro de 2010, o Acordo de Basileia III, com adoção prevista até 2019, veio reforçar estas medidas com a criação de um quadro regulamentar e de supervisão mais sólido, por parte das instituições de crédito. Surge, assim neste contexto, o Modelo de Avaliação de Risco (MAR) para o sector bancário. Em Portugal, o MAR tem como objetivo avaliar o perfil de risco das instituições de crédito, sujeitas à supervisão do Banco de Portugal, assim como apresentar o perfil de risco e a solidez da situação financeira de cada instituição de crédito. Este trabalho pretende avaliar o surgimento e a caracterização deste modelo e identificar as variáveis a ter em conta nos modelos de avaliação de risco a nível qualitativo e quantitativo.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Avaliação do Impacto da Formação no sector da hotelaria e restauração

O mundo é cada vez mais, mais veloz, voraz e global, o que origina, se não mesmo força, alterações constantes nos comportamentos dos consumidores, originando inovadoras e criativas formas de diferenciação. O setor da Hotelaria e Restauração, um dos mais dinâmicos no atual paradigma da economia global, é também um dos que mais pronto responde a essas exigências; recorrendo, em muitas das situações à formação como resposta à exigência de melhoria constante e continuada dos serviços que presta e dos produtos que oferece. Isto porque essa qualidade passa inevitavelmente pelos recursos humanos, cabendo à formação o papel preponderante na sua qualificação e adequação a novos produtos, serviços e públicos. Por força desse relevo e de uma crescente e permanente pressão para a majoração dos resultados obtidos pelas organizações, também a Formação se viu obrigada a avaliar o impacto da sua ação/intervenção, para que se possa de forma clara pesar o seu contributo para a melhoria dos resultados das organizações. Este projeto procurou identificar qual, ou quais, de entre os modelos disponíveis, melhor se adaptam e adequam ao setor que é tão sui generis na forma como capta, treina e gere os seus recursos humanos!

Landslide susceptibility assessment in Karanganyar regency - Indonesia - Comparison of knowledge-based and Data-driven Models

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Analysis of mental health service financial models with a particular emphasis of Ireland

ABSTRACT: Financing is a critical factor in ensuring the optimal development and delivery of a mental health system. The primary method of financing worldwide is tax-based. However many low income countries depend on out-of-pocket payments. There is a report on Irish Health Care funding but none that deals exclusively with mental health care. This paper analyses the various financial models that exist globally with respect to financing the mental health sector, examines the impact of various models on service users, especially in terms of relative ‘financial burden’ and provides a more detailed examination of the current mental health funding situation in Ireland After extensive internet and hardcopy research on the above topics, the findings were analysed and a number of recommendations were reached. Mental health service should be free at the point of delivery to achieve universal coverage. Government tax-based funding or mandatory social insurance with government top-ups, as required, appears the optimal option, although there is no one funding system applicable everywhere. Out-of-pocket funding can create a crippling financial burden for service users. It is important to employ improved revenue collection systems, eliminate waste, provide equitable resource distribution, ring fence mental health funding and cap the number of visits, where necessary. Political, economic, social and cultural factors play a role in funding decisions and this can be clearly seen in the context of the current economic recession in Ireland. Only 33% of the Irish population has access to free public health care and the number health insurance policy holders has dramatically declined, resulting in increased out-of-pocket payments. This approach risks negatively impacting on the social determinants of health, increasing health inequalities and negatively affecting economic productivity. It is therefore important the Irish government examines other options to provide funding for mental health services.

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Innovative medicines in the portuguese private health sector

The present dissertation aims at contributing to a strategic view over the use of innovative medicines in the portuguese private health sector, as a way of being complementary to public system that nowadays finances most of the innovative medicines. With the rationalization of expenses in the public health sector, pharmaceutical companies tend to look for opportunities of expansion to the private sector. The creation of innovative financial models for the private sector to cover innovative treatments is the proposed way of surpassing the restriction on the NHS sales of innovative medicines. This can be both for differentiating private health providers from the NHS or for the creation of premium services that can be differentiated from other private providers of the portuguese market.

Risk acceptance in the furniture sector: Analysis of acceptance level and relevant influence factors

Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

Search for low-scale gravity signatures in multi-jet final states with the ATLAS detector at s√ = 8 TeV

We search for evidence of physics beyond the Standard Model in the production of final states with multiple high transverse momentum jets, using 20.3 fb−1 of proton-proton collision data recorded by the ATLAS detector at s√ = 8 TeV. No excess of events beyond Standard Model expectations is observed, and upper limits on the visible cross-section for non-Standard Model production of multi-jet final states are set. Using a wide variety of models for black hole and string ball production and decay, the limit on the cross-section times acceptance is as low as 0.16 fb at the 95% CL for a minimum scalar sum of jet transverse momentum in the event of about 4.3 TeV. Using models for black hole and string ball production and decay, exclusion contours are determined as a function of the production mass threshold and the gravity scale. These limits can be interpreted in terms of lower-mass limits on black hole and string ball production that range from 4.6 to 6.2 TeV.

Behavior-based price discrimination in a multi-dimensional preferences market

NIPE WP 04/ 2016

Optimização do processo de recolha de resíduos: desenvolvimento de ferramentas de investigação operacional para o problema de orientação de equipas com multi-restrições

Tese de Doutoramento em Engenharia Industrial e de Sistemas.

A Multi-state model for the analysis of functional decline and mortality of frail elderly patients

L’objectiu d’aquest estudi, que correspon a un projecte de recerca sobre la pèrdua funcional i la mortalitat de persones grans fràgils, és construir un procés de supervivència predictiu que tingui en compte l’evolució funcional i nutricional dels pacients al llarg del temps. En aquest estudi ens enfrontem a l’anàlisi de dades de supervivència i mesures repetides però els mètodes estadístics habituals per al tractament conjunt d’aquest tipus de dades no són apropiats en aquest cas. Com a alternativa utilitzem els models de supervivència multi-estats per avaluar l’associació entre mortalitat i recuperació, o no, dels nivells funcionals i nutricionals considerats normals. Després d’estimar el model i d’identificar els factors pronòstics de mortalitat és possible obtenir un procés predictiu que permet fer prediccions de la supervivència dels pacients en funció de la seva història concreta fins a un determinat moment. Això permet realitzar un pronòstic més precís de cada grup de pacients, la qual cosa pot ser molt útil per als professionals sanitaris a l’hora de prendre decisions clíniques.

Modelo para la idenfiticación de grupos estratégicos basado en el análisis envolvente de datos: aplicación al sector bancario español

Este trabajo explora la formación de grupos estratégicos en el Sector Bancario Español, a partir de una definición alternativa de grupo estratégico (GE). Un GE se define como un conjunto de empresas capaces de responder del mismo modo a perturbaciones. La capacidad de respuesta, o capacidad de adaptar la estrategia competitiva, se define a partir de las relaciones marginales (RM) entre las variables estratégicas (la pendiente de la frontera en un punto), y sirve de base para examinar la presencia de barreras a la movilidad. El Análisis Envolvente de Datos (DEA) es la herramienta utilizada para el cómputo de las RM, aunque su uso genera dos problemas que son solucionados en este trabajo; la multiplicidad de RM para las empresas situadas en la frontera (líderes estratégicos), y la imposibilidad de encontrar RM para las empresas situadas por debajo de la misma (seguidores estratégicos).

On the relation between tax rates and evasion in a multi-period economy

We extend the basic tax evasion model to a multi-period economy exhibiting sustained growth. When individuals conceal part of their true income from the tax authority, they face the risk of being audited and hence of paying the corresponding fine. Both taxes and fines determine individual saving and the rate of capital accumulation. In this context we show that the sign of the relation between the level of the tax rate and the amount of evaded income is the same as that obtained in static setups. Moreover, high tax rates on income are typically associated with low growth rates as occurs in standard growth models that disregard the tax evasion phenomenon.