Constructing good deals in discrete time arbitrage-free dynamic pricing models

Recent literature has proved that many classical pricing models (Black and Scholes, Heston, etc.) and risk measures (V aR, CV aR, etc.) may lead to “pathological meaningless situations”, since traders can build sequences of portfolios whose risk leveltends to −infinity and whose expected return tends to +infinity, i.e., (risk = −infinity, return = +infinity). Such a sequence of strategies may be called “good deal”. This paper focuses on the risk measures V aR and CV aR and analyzes this caveat in a discrete time complete pricing model. Under quite general conditions the explicit expression of a good deal is given, and its sensitivity with respect to some possible measurement errors is provided too. We point out that a critical property is the absence of short sales. In such a case we first construct a “shadow riskless asset” (SRA) without short sales and then the good deal is given by borrowing more and more money so as to invest in the SRA. It is also shown that the SRA is interested by itself, even if there are short selling restrictions.

A comparative study of alternative approaches for common factors identification

Preliminary version

Influência da actividade do tronco inferior na sequência de activação muscular proximal durante o passo (fase de apoio) - em crianças com quadro motor diplegia

A marcha assegura uma progressão do corpo, compatível com o equilíbrio dinâmico e adaptada a potenciais factores destabilizadores, de um ponto de vista antecipatório, através de sinergias coordenadas entre os MSs, o tronco e os MIs. O tronco inferior tem um papel preponderante na marcha, sobretudo na estabilização necessária durante a fase de apoio. Esta actividade implica mobilidade pélvica e alongamento activo dos abdominais para conseguir a relação comprimento-tensão muscular óptima entre quadricípite e isquiotibiais, permitindo uma correcta sequência, timing e amplitude de activação. Nas crianças com alterações neuromotoras existem alterações no controlo do movimento e na estrutura do próprio movimento, alterando todo este processo. Como tal, este estudo tem como principal objectivo determinar a influência da actividade do tronco inferior na activação muscular proximal durante a fase de apoio da marcha, em crianças com quadro motor de diplegia, caracterizada por uma dificuldade na relação entre os membros e entre estes e o tronco. Para responder a este objectivo realizou-se um estudo de série de casos, com 2 crianças com quadro motor de diplegia. Efectuou-se EMG dos músculos abdominais, quadricípite e isquiotibiais e análise de imagem (para amplitude da CF) durante a marcha, em ambos os membros e em dois momentos de avaliação, separados por 2 meses, nos quais se realizou um protocolo de intervenção terapêutica adequado a cada caso. Os resultados indicam que a variação de amplitude da CF desde a fase de ataque ao solo à fase média de apoio é aproximadamente igual em M0e M1; concretamente, a amplitude inicial é inferior à de referência (pouca flexão) (melhor em M0) e a amplitude final é superior à de referência (pouca extensão) (melhor em M1). Estes resultados são idênticos em ambos os casos. Na EMG verificou-se uma actividade mais global e sincronizada de todos os músculos, mantendo-se aproximadamente a mesma percentagem de activação em M1, sobretudo no caso 1. No caso 2 verificou-se uma maior eficiência na variação da percentagem de activação dos abdominais, em M1, e dos isquiotibiais, à direita. Em conclusão, pode dizer-se que, em crianças com alterações neuromotoras (quadro motor de diplegia), uma actividade mais eficiente e sincronizada no tempo do tronco inferior, nomeadamente dos abdominais, contribui para uma maior capacidade de extensão da CF, durante a fase de apoio.

Dispositional optimism is unidimensional or bidimensional? The Portuguese Revised Life Orientation Test

The aim of the study is to adapt and then discuss the appropriateness of the Life Orientation Test as a one or two dimension scale. The research includes two studies; one is composed of a sequential sample of 280 people with multiple sclerosis, 71% female, and another includes a convenience sample of 615 individuals from the community, 51.1% female. Because the construct is built upon a theoretical assumption that has one dimension, we examine the hypothesis of one or two factor solutions through confirmatory factor analysis, and the two-dimension solution premise demonstrates better adjustment for both samples. The other psychometric properties explored show appropriate results for the Portuguese sample, and similar to the original ones; the Test therefore seems appropriate for use in cross cultural studies. Based on our results, we discuss whether the questionnaire is a one or two dimension instrument, concluding that it appears appropriate to accept the recommendations of the original authors to use it as a one-dimensional tool and, when necessary, to use both dimensions. - RESUMO: El objetivo del estudio es adaptar y discutir la adecuación de la prueba de Orientación de la Vida en una o dos escalas de dimensión. La investigación engloba dos estudios, uno constituido por una muestra secuencial de 280 personas con esclerosis múltiple, 71% mujeres y otro con una muestra de conveniencia de la comunidad de 615 individuos, 51,1% del sexo femenino. Como el constructo se asienta sobre la presunción teórica de que tiene una dimensión, inspeccionamos la hipótesis de una o dos soluciones de factor a través del análisis factorial confirmatorio y la hipótesis de dos dimensiones manifiesta un mejor ajuste para ambas muestras. Las otras propiedades psicométricas exploradas muestran los resultados apropiados para la muestra portuguesa, y semejantes a los originales. Parece apropiado para los estudios culturales transversales. Basándonos en nuestros resultados, discutimos si el cuestionario es un instrumento de una o dos dimensiones, concluyéndose que parece conveniente seguir las recomendaciones de los autores originales, para utilizarlo como un instrumento unidimensional y, si fuera necesario necesario, utilizar cada una de las dimensiones.

Performance of an immunochromatography test for vivax malaria in the Amazon region, Brazil

The study was carried out to evaluate the diagnostic performance of the ICT malaria Pf/PvTM test for vivax malaria diagnosis in Belém, Amazon region, Brazil. The results of blood malaria parasites examination using an immunochromatography test were compared with thick blood film (TBF) examination. It was also evaluated the performance of this test storaged at three different temperatures (25°C, 30°C, and 37°C) for 24 hours before use. Overall sensitivity of ICT Pf/PvTM was 61.8% with a specificity of 100%, positive and negative predictive value of 100% and 71.8%, respectively and accuracy of 80.6%. The test sensitivity was independent of the parasite density. This test needs to be further reviewed in order to have better performance for P. vivax malaria diagnosis.

Design of a new test chamber for evaluation of the toxicity of rubber infill

A test chamber was projected and built (according to ISO 16000-9 Standard) to simulate atmospheric conditions experienced by rubber infill (when applied in synthetic turf pitches) and measure accurately the airborne emissions of pollutants such as dusts and volatile organic compounds (VOC), as well as pollutants present in leachates. It should be pointed out that standard ISO 16000-9 is only concerned with the determination of the emission of VOC from building products and furnishing (not specific of synthetic turf materials), whereas other standards are concerned with the emission of leachates only. This procedure is to be considered as a technical option to the lysimeter "global turf system evaluation" when the rubber infill alone is to be evaluated. The advantage of the proposed option considering this "test chamber" is its simplicity and economy. This test chamber is actually installed and being used for tests in LAIST.

Ankle dynamic in stroke patients: agonist vs. antagonist muscle relations

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

MASDSheGATS – Scheduling System for Dynamic Manufacturing Environments

This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

A study on dynamic state information (DSI) around users for safe urban life

To select each node by devices and by contexts in urban computing, users have to put their plan information and their requests into a computing environment (ex. PDA, Smart Devices, Laptops, etc.) in advance and they will try to keep the optimized states between users and the computing environment. However, because of bad contexts, users may get the wrong decision, so, one of the users’ demands may be requesting the good server which has higher security. To take this issue, we define the structure of Dynamic State Information (DSI) which takes a process about security including the relevant factors in sending/receiving contexts, which select the best during user movement with server quality and security states from DSI. Finally, whenever some information changes, users and devices get the notices including security factors, then an automatic reaction can be possible; therefore all users can safely use all devices in urban computing.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.