A clustering-based failure mode and effect analysis model and its application to the edible bird nest industry

Failure mode and effect analysis (FMEA) is a popular safety and reliability analysis tool in examining potential failures of products, process, designs, or services, in a wide range of industries. While FMEA is a popular tool, the limitations of the traditional Risk Priority Number (RPN) model in FMEA have been highlighted in the literature. Even though many alternatives to the traditional RPN model have been proposed, there are not many investigations on the use of clustering techniques in FMEA. The main aim of this paper was to examine the use of a new Euclidean distance-based similarity measure and an incremental-learning clustering model, i.e., fuzzy adaptive resonance theory neural network, for similarity analysis and clustering of failure modes in FMEA; therefore, allowing the failure modes to be analyzed, visualized, and clustered. In this paper, the concept of a risk interval encompassing a group of failure modes is investigated. Besides that, a new approach to analyze risk ordering of different failure groups is introduced. These proposed methods are evaluated using a case study related to the edible bird nest industry in Sarawak, Malaysia. In short, the contributions of this paper are threefold: (1) a new Euclidean distance-based similarity measure, (2) a new risk interval measure for a group of failure modes, and (3) a new analysis of risk ordering of different failure groups. © 2014 The Natural Computing Applications Forum.

A clustering-based failure mode and effect analysis model and its application to the edible bird nest industry

Failure mode and effect analysis (FMEA) is a popular safety and reliability analysis tool in examining potential failures of products, process, designs, or services, in a wide range of industries. While FMEA is a popular tool, the limitations of the traditional Risk Priority Number (RPN) model in FMEA have been highlighted in the literature. Even though many alternatives to the traditional RPN model have been proposed, there are not many investigations on the use of clustering techniques in FMEA. The main aim of this paper was to examine the use of a new Euclidean distance-based similarity measure and an incremental-learning clustering model, i.e., fuzzy adaptive resonance theory neural network, for similarity analysis and clustering of failure modes in FMEA; therefore, allowing the failure modes to be analyzed, visualized, and clustered. In this paper, the concept of a risk interval encompassing a group of failure modes is investigated. Besides that, a new approach to analyze risk ordering of different failure groups is introduced. These proposed methods are evaluated using a case study related to the edible bird nest industry in Sarawak, Malaysia. In short, the contributions of this paper are threefold: (1) a new Euclidean distance-based similarity measure, (2) a new risk interval measure for a group of failure modes, and (3) a new analysis of risk ordering of different failure groups.

Measuring the effect of motorcycle rider training on psychosocial influences for risk taking

Aim: Whilst motorcycle rider training is commonly incorporated into licensing programs in many developed nations, little empirical support has been found in previous research to prescribe it as an effective road safety countermeasure. It has been posited that the lack of effect of motorcycle rider training on crash reduction may, in part, be due to the predominant focus on skills-based training with little attention devoted to addressing attitudes and motives that influence subsequent risky riding. However, little past research has actually endeavoured to measure attitudinal and motivational factors as a function of rider training. Accordingly, this study was undertaken to assess the effect of a commercial motorcycle rider training program on psychosocial factors that have been shown to influence risk taking by motorcyclists. Method: Four hundred and thirty-eight motorcycle riders attending a competency-based licence training course in Brisbane, Australia, voluntarily participated in the study. A self-report questionnaire adapted from the Rider Risk Assessment Measure (RRAM) was administered to participants at the commencement of training, then again at the conclusion of training. Participants were informed of the independent nature of the research and that their responses would in no way effect their chance of obtaining a licence. To minimise potential demand characteristics, participants were instructed to seal completed questionnaires in envelopes and place them in a sealed box accessible only by the research team (i.e. not able to be viewed by instructors). Results: Significant reductions in the propensity for thrill seeking and intentions to engage in risky riding in the next 12 months were found at the end of training. In addition, a significant increase in attitudes to safety was found. Conclusions: These findings indicate that rider training may have a positive short-term influence on riders’ propensity for risk taking. However, such findings must be interpreted with caution in regard to the subsequent safety of riders as these factors may be subject to further influence once riders are licensed and actively engage with peers during on-road riding. This highlights a challenge for road safety education / training programs in regard to the adoption of safety practices and the need for behavioural follow-up over time to ascertain long-term effects. This study was the initial phase of an ongoing program of research into rider training and risk taking framed around Theory of Planned Behaviour concepts. A subsequent 12 month follow-up of the study participants has been undertaken with data analysis pending.

A systematic component of the jump-risk premium in an AJD model

We develop an affine jump diffusion (AJD) model with the jump-risk premium being determined by both idiosyncratic and systematic sources of risk. While we maintain the classical affine setting of the model, we add a finite set of new state variables that affect the paths of the primitive, under both the actual and the risk-neutral measure, by being related to the primitive's jump process. Those new variables are assumed to be commom to all the primitives. We present simulations to ensure that the model generates the volatility smile and compute the "discounted conditional characteristic function'' transform that permits the pricing of a wide range of derivatives.

An SDF approach to hedge funds’ tail risk: evidence from Brazilian funds

The main purpose of this paper is to propose a methodology to obtain a hedge fund tail risk measure. Our measure builds on the methodologies proposed by Almeida and Garcia (2015) and Almeida, Ardison, Garcia, and Vicente (2016), which rely in solving dual minimization problems of Cressie Read discrepancy functions in spaces of probability measures. Due to the recently documented robustness of the Hellinger estimator (Kitamura et al., 2013), we adopt within the Cressie Read family, this specific discrepancy as loss function. From this choice, we derive a minimum Hellinger risk-neutral measure that correctly prices an observed panel of hedge fund returns. The estimated risk-neutral measure is used to construct our tail risk measure by pricing synthetic out-of-the-money put options on hedge fund returns of ten specific categories. We provide a detailed description of our methodology, extract the aggregate Tail risk hedge fund factor for Brazilian funds, and as a by product, a set of individual Tail risk factors for each specific hedge fund category.

Experimentally Testing the Effect of Parent-Adolescent Conflict on HIV Risk, and Investigation of a Neurobiological Moderator of This Effect

Human immunodeficiency virus (HIV) is a condition in which immune cells become destroyed such that the body may become unable to fight off infections. Engaging in risk-taking behaviors (e.g., substance use) puts people at heightened risk for HIV infection, with mid-to-late adolescents at increasing risk (Leigh & Stall, 1993). Environmental and neurological reasons have been suggested for increased risk-taking among adolescents. First, family-level precursors such as parent-adolescent conflict have been significantly associated with and may pose risk for engaging in substance use and risk-taking (Duncan, Duncan, Biglan, & Ary, 1998). Thus, parent-adolescent conflict may be an important proximal influence on HIV risk behaviors (Lester et al., 2010; Rowe, Wang, Greenbaum, & Liddle, 2008). Yet, the temporal relation between parent-adolescent conflict and adolescent HIV risk-taking behaviors is still unknown. Second, at-risk adolescents may carry a neurobiological predisposition for engaging in trait-like expressions of disinhibited behavior and other risk-taking behaviors (Iacono, Malone, & McGue, 2008). When exposed to interpersonally stressful situations, their likelihood of engagement in HIV risk behaviors may increase. To investigate the role of parent-adolescent conflict in adolescent HIV risk-taking behaviors, 49 adolescents ages 14-17 and their parent were randomly assigned to complete a standardized discussion task to discuss a control topic or a conflict topic. Immediately after the discussion, adolescents completed a laboratory risk-taking measure. In a follow-up visit, eligible adolescents underwent electrophysiological (EEG) recording while completing a task designed to assess the presence of a neurobiological marker for behavioral disinhibition which I hypothesized would moderate the links between conflict and risk-taking. First, findings indicated that during the discussion task, adolescents in the conflict condition evidenced a significantly greater psychophysiological stress response relative to adolescents in the control condition. Second, a neurobiological marker of behavioral disinhibition moderated the relation between discussion condition and adolescent risk-taking, such that adolescents evidencing relatively high levels of a neurobiological marker related to sensation-seeking evidenced greater levels of risk-taking following the conflict condition, relative to the control condition. Lastly, I observed no significant relation between parent-adolescent conflict, the neurobiological marker of behavioral disinhibition and adolescent engagement in real-world risk-taking behavior.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

Machine learning Vasicek model calibration with Gaussian processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.

Ajustamento pelo risco : da conceptualização à operacionalização

RESUMO - As organizações de saúde, em geral, e os hospitais, em particular, são frequentemente reconhecidos por terem particularidades e especificidades que conferem uma especial complexidade ao seu processo produtivo e à sua gestão (Jacobs, 1974; Butler, 1995). Neste sentido, na literatura hospitalar emergem alguns temas como prioritários tanto na investigação como na avaliação do seu funcionamento, nomeadamente os relacionados com a produção, com o financiamento, com a qualidade, com a eficiência e com a avaliação do seu desempenho. O estado da arte da avaliação do desempenho das organizações de saúde parece seguir a trilogia definida por Donabedian (1985) — Estrutura, Processo e Resultados. Existem diversas perspectivas para a avaliação do desempenho na óptica dos Resultados — efectividade, eficiência ou desempenho financeiro. No entanto, qualquer que seja a utilizada, o ajustamento pelo risco é necessário para se avaliar a actividade das organizações de saúde, como forma de medir as características dos doentes que podem influenciar os resultados de saúde. Como possíveis indicadores de resultados, existem a mortalidade (resultados finais), as complicações e as readmissões (resultados intermédios). Com excepção dos estudos realizados por Thomas (1996) e Thomas e Hofer (1998 e 1999), praticamente ninguém contesta a relação entre estes indicadores e a efectividade dos cuidados. Chamando, no entanto, a atenção para a necessidade de se definirem modelos de ajustamento pelo risco e ainda para algumas dificuldades conceptuais e operacionais para se atingir este objectivo. Em relação à eficiência técnica dos hospitais, os indicadores tradicionalmente mais utilizados para a sua avaliação são os custos médios e a demora média. Também neste domínio, a grande maioria dos estudos aponta para que a gravidade aumenta o poder justificativo do consumo de recursos e que o ajustamento pelo risco é útil para avaliar a eficiência dos hospitais. Em relação aos sistemas usados para medir a severidade e, consequentemente, ajustar pelo risco, o seu desenvolvimento apresenta, na generalidade, dois tipos de preocupações: a definição dos suportes de recolha da informação e a definição dos momentos de medição. Em última instância, o dilema que se coloca reside na definição de prioridades e daquilo que se pretende sacrificar. Quando se entende que os aspectos financeiros são determinantes, então será natural que se privilegie o recurso quase exclusivo a elementos dos resumos de alta como suporte de recolha da informação. Quando se defende que a validade de construção e de conteúdo é um aspecto a preservar, então o recurso aos elementos dos processos clínicos é inevitável. A definição dos momentos de medição dos dados tem repercussões em dois níveis de análise: na neutralidade económica do sistema e na prospectividade do sistema. O impacto destas questões na avaliação da efectividade e da eficiência dos hospitais não é uma questão pacífica, visto que existem autores que defendem a utilização de modelos baseados nos resumos de alta, enquanto outros defendem a supremacia dos modelos baseados nos dados dos processos clínicos, para finalmente outros argumentarem que a utilização de uns ou outros é indiferente, pelo que o processo de escolha deve obedecer a critérios mais pragmáticos, como a sua exequibilidade e os respectivos custos de implementação e de exploração. Em relação às possibilidades que neste momento se colocam em Portugal para a utilização e aplicação de sistemas de ajustamento pelo risco, verifica-se que é praticamente impossível a curto prazo aplicar modelos com base em dados clínicos. Esta opção não deve impedir que a médio prazo se altere o sistema de informação dos hospitais, de forma a considerar a eventualidade de se utilizarem estes modelos. Existem diversos problemas quando se pretendem aplicar sistemas de ajustamento de risco a populações diferentes ou a subgrupos distintos das populações donde o sistema foi originalmente construído, existindo a necessidade de verificar o ajustamento do modelo à população em questão, em função da sua calibração e discriminação.

Le théorème de lebesgue sur la dérivabilité des fonctions à variation bornée

Dans ce mémoire, nous traiterons du théorème de Lebesgue, un des plus frappants et des plus importants de l'analyse mathématique ; à savoir qu'une fonction à variation bornée est dérivable presque partout. Le but de ce travail est de fournir, à part la démonstration souvent proposée dans les cours de la théorie de la mesure, d'autres démonstrations élaborées avec des outils mathématiques plus simples. Ma contribution a consisté essentiellement à détailler et à compléter ces démonstrations, puis à inclure la plupart des figures pour une meilleure lisibilité. Nous allons maintenant, pour ce théorème qui se présente sous d'autres variantes, en proposer l'historique et trois démonstrations différentes.

Correlación entre niveles séricos de PCR ultrasensible y riesgo cardiovascular en una cohorte de mujeres adultas

La PCR es el marcador de inflamación vascular más estudiado y validado hasta la fecha. Los niveles de PCR ultrasensible pueden predecir el riesgo de enfermedad cardiovascular. En el programa “salud integral para la mujer” de la fundación cardio-infantil se realizan estratificaciones de riesgo cardiovascular a mujeres adultas. Se midieron los niveles de PCR en este grupo de pacientes entre Octubre del 2007 y Mayo del 2009 y se evaluó la correlación entre la estratificación del riesgo cardiovascular por escala de Framingham y niveles de PCR en esta población. Objetivo: establecer el grado de correlación entre los niveles de PCR ultrasensible y el grado de riesgo cardiovascular y otros factores de riesgo cardiovascular. Resultados: Edad promedio 48 años (18 a 98 años). 62 pacientes hipertensas (40,7%). 19 pacientes con cifras alteradas de glicemia en ayunas (12%). Hay un 83% de la población estudiada con dislipidemia (127 pacientes). 78 pacientes con sobrepeso u obesidad. El 87% de la población tiene al menos un factor de riesgo presente. Discusión y resultados: En la población estudiada existe una alta prevalencia de factores de riesgo cardiovasculares, dentro de los cuales predomina los trastornos del metabolismo de los lípidos. Sin embargo no hay correlación entre los niveles de PCR ultrasensible y el riesgo cardiovascular según la escala de Framingham. En la literatura médica publicada sobre PCR ultrasensible y su relación con el riesgo cardiovascular los resultados son muy divergentes con los encontrados en este estudio.

Clustering and visualization of failure modes using an evolving tree

Despite the popularity of Failure Mode and Effect Analysis (FMEA) in a wide range of industries, two well-known shortcomings are the complexity of the FMEA worksheet and its intricacy of use. To the best of our knowledge, the use of computation techniques for solving the aforementioned shortcomings is limited. As such, the idea of clustering and visualization pertaining to the failure modes in FMEA is proposed in this paper. A neural network visualization model with an incremental learning feature, i.e., the evolving tree (ETree), is adopted to allow the failure modes in FMEA to be clustered and visualized as a tree structure. In addition, the ideas of risk interval and risk ordering for different groups of failure modes are proposed to allow the failure modes to be ordered, analyzed, and evaluated in groups. The main advantages of the proposed method lie in its ability to transform failure modes in a complex FMEA worksheet to a tree structure for better visualization, while maintaining the risk evaluation and ordering features. It can be applied to the conventional FMEA methodology without requiring additional information or data. A real world case study in the edible bird nest industry in Sarawak (Borneo Island) is used to evaluate the usefulness of the proposed method. The experiments show that the failure modes in FMEA can be effectively visualized through the tree structure. A discussion with FMEA users engaged in the case study indicates that such visualization is helpful in comprehending and analyzing the respective failure modes, as compared with those in an FMEA table. The resulting tree structure, together with risk interval and risk ordering, provides a quick and easily understandable framework to elucidate important information from complex FMEA forms; therefore facilitating the decision-making tasks by FMEA users. The significance of this study is twofold, viz., the use of a computational visualization approach to tackling two well-known shortcomings of FMEA; and the use of ETree as an effective neural network learning paradigm to facilitate FMEA implementations. These findings aim to spearhead the potential adoption of FMEA as a useful and usable risk evaluation and management tool by the wider community.

Uma resenha sobre modelos de apreçamento de derivativos

Apresento aqui uma abordagem que unifica a literatura sobre os vários modelos de apreçamento de derivativos que consiste em obter por argumentos intuitivos de não arbitragem uma Equação Diferencial Parcial(EDP) e através do método de Feynman-Kac uma solução que é representada por uma esperança condicional de um processo markoviano do preço do derivativo descontado pela taxa livre de risco. Por este resultado, temos que a esperança deve ser tomada com relação a processos que crescem à taxa livre de risco e por este motivo dizemos que a esperança é tomada em um mundo neutro ao risco(ou medida neutra ao risco). Apresento ainda como realizar uma mudança de medida pertinente que conecta o mundo real ao mundo neutro ao risco e que o elemento chave para essa mudança de medida é o preço de mercado dos fatores de risco. No caso de mercado completo o preço de mercado do fator de risco é único e no caso de mercados incompletos existe uma variedade de preços aceitáveis para os fatores de risco pelo argumento de não arbitragem. Neste último caso, os preços de mercado são geralmente escolhidos de forma a calibrar o modelo com os dados de mercado.

Ensaios em Finanças

Esta tese é composta de três artigos sobre finanças. O primeiro tem o título "Nonparametric Option Pricing with Generalized Entropic Estimators " e estuda um método de apreçamento de derivativos em mercados incompletos. Este método está relacionado com membros da família de funções de Cressie-Read em que cada membro fornece uma medida neutra ao risco. Vários testes são feitos. Os resultados destes testes sugerem um modo de definir um intervalo robusto para preços de opções. Os outros dois artigos são sobre anúncios agendados em diferentes situações. O segundo se chama "Watching the News: Optimal Stopping Time and Scheduled Announcements" e estuda problemas de tempo de parada ótimo na presença de saltos numa data fixa em modelos de difusão com salto. Fornece resultados sobre a otimalidade do tempo de parada um pouco antes do anúncio. O artigo aplica os resultados ao tempo de exercício de Opções Americanas e ao tempo ótimo de venda de um ativo. Finalmente o terceiro artigo estuda um problema de carteira ótima na presença de custo fixo quando os preços podem saltar numa data fixa. Seu título é "Dynamic Portfolio Selection with Transactions Costs and Scheduled Announcement" e o resultado mais interessante é que o comportamento do investidor é consistente com estudos empíricos sobre volume de transações em momentos próximos de anúncios.

Carbon Leakage: Options for the EU. CEPS Special Report, March 2014

This CEPS Special Report builds on the first deliverable of the project entitled “Carbon leakage: Options for the EU”. It identifies carbon costs, and the ability to pass through carbon costs, as the main risk factors that could lead from asymmetrical carbon policies to carbon leakage. It also outlines and evaluates, based on criteria discussed in the paper, options for detecting and mitigating the risk of carbon leakage in three jurisdictions, with special attention to the EU ETS (Emissions Trading Scheme). Based on the analysis of approaches currently used in a number of existing carbon pricing systems, it identifies the balance between the number of sectors identified as being at risk, and the amount of compensation provided as a risk mitigation measure, as the critical element in providing an optimum approach to address carbon leakage risks. It also identifies a risk-based approach to identifying sectors at risk as allowing for a better reflection of reality in a counterfactual argument. Finally, the paper concludes that while, with some exceptions, there has been limited carbon leakage until now, the past may not be a good reflection of the future and that measures need to be put in place for the post-2020 period. While examining a number of approaches, it identifies free allocation as the most likely way forward for mitigating the risk of carbon leakage. While other approaches may provide interesting options, they also present challenges for implementation, from a market functioning, to international trade and relations, points of view. A number of challenges will need to be addressed in the post-2020 period, with many of them part of the EU ETS structural reform package. Some of these challenges include, among others, the need to recognise, and provide for individual sectoral characteristics, as well as for changes in production patterns, due to economic cycles, and other factors. Finally, the paper emphasises the need for an open dialogue regarding the post-2020 provisions for carbon leakage as no overall Energy and Climate Package is likely to be agreed on until this matter is addressed.