82 resultados para Power Trading Methodology


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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas Ambientais

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

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Epistemology in philosophy of mind is a difficult endeavor. Those who believe that our phenomenal life is different from other domains suggest that self-knowledge about phenomenal properties is certain and therefore privileged. Usually, this so called privileged access is explained by the idea that we have direct access to our phenomenal life. This means, in contrast to perceptual knowledge, self-knowledge is non-inferential. It is widely believed that, this kind of directness involves two different senses: an epistemic sense and a metaphysical sense. Proponents of this view often claim that this is due to the fact that we are acquainted with our current experiences. The acquaintance thesis, therefore, is the backbone in justifying privileged access. Unfortunately the whole approach has a profound flaw. For the thesis to work, acquaintance has to be a genuine explanation. Since it is usually assumed that any knowledge relation between judgments and the corresponding objects are merely causal and contingent (e.g. in perception), the proponent of the privileged access view needs to show that acquaintance can do the job. In this thesis, however, I claim that the latter cannot be done. Based on considerations introduced by Levine, I conclude that this approach involves either the introduction of ontologically independent properties or a rather obscure knowledge relation. A proper explanation, however, cannot employ either of the two options. The acquaintance thesis is, therefore, bound to fail. Since the privileged access intuition seems to be vital to epistemology within the philosophy of mind, I will explore alternative justifications. After discussing a number of options, I will focus on the so called revelation thesis. This approach states that by simply having an experience with phenomenal properties, one is in the position to know the essence of those phenomenal properties. I will argue that, after finding a solution for the controversial essence claim, this thesis is a successful replacement explanation which maintains all the virtues of the acquaintance account without necessarily introducing ontologically independent properties or an obscure knowledge relation. The overall solution consists in qualifying the essence claim in the relevant sense, leaving us with an appropriate ontology for phenomenal properties. On the one hand, this avoids employing mysterious independent properties, since this ontological view is physicalist in nature. On the other hand, this approach has the right kind of structure to explain privileged self-knowledge of our phenomenal life. My final conclusion consists in the claim that the privileged access intuition is in fact veridical. It cannot, however, be justified by the popular acquaintance approach, but rather, is explainable by the controversial revelation thesis.

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Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.

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This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

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This paper designs a pairs trading model with the intent to identify existing profitable market opportunities to invest, i.e. traditionally strong correlated stocks that have diverged from its historical norm. It comprises a broad literature review on this strategy whose relevant findings (strategy improvements) are contemplated in the model. The authors combine the statistical results of the model with a backtesting analysis in order to provide guidance on the best investment opportunities.

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Wind turbines and solar panels are becoming second nature in Portugal, as its occurrence in the country becomes ubiquitous. Somehow, one could argue that renewable energy in Portugal is in the process of ‘naturalisation’ as part of a new – mechanised, but environmentally benign – landscape. Portuguese Institute for the Conservation of Nature and Biodiversity (ICNB) has shown an ambiguous stance on this issue, defending global concerns towards renewable energy, while at the same time attempting to engage locals in the preservation of extensive ‘classified areas’. In the course of this research, we tried to focus on these incongruities and to analyse how they are impacting local communities during the process of wind power installation.

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Major in Competition and Regulation

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A potentially renewable and sustainable source of energy is the chemical energy associated with solvation of salts. Mixing of two aqueous streams with different saline concentrations is spontaneous and releases energy. The global theoretically obtainable power from salinity gradient energy due to World’s rivers discharge into the oceans has been estimated to be within the range of 1.4-2.6 TW. Reverse electrodialysis (RED) is one of the emerging, membrane-based, technologies for harvesting the salinity gradient energy. A common RED stack is composed by alternately-arranged cation- and anion-exchange membranes, stacked between two electrodes. The compartments between the membranes are alternately fed with concentrated (e.g., sea water) and dilute (e.g., river water) saline solutions. Migration of the respective counter-ions through the membranes leads to ionic current between the electrodes, where an appropriate redox pair converts the chemical salinity gradient energy into electrical energy. Given the importance of the need for new sources of energy for power generation, the present study aims at better understanding and solving current challenges, associated with the RED stack design, fluid dynamics, ionic mass transfer and long-term RED stack performance with natural saline solutions as feedwaters. Chronopotentiometry was used to determinate diffusion boundary layer (DBL) thickness from diffusion relaxation data and the flow entrance effects on mass transfer were found to avail a power generation increase in RED stacks. Increasing the linear flow velocity also leads to a decrease of DBL thickness but on the cost of a higher pressure drop. Pressure drop inside RED stacks was successfully simulated by the developed mathematical model, in which contribution of several pressure drops, that until now have not been considered, was included. The effect of each pressure drop on the RED stack performance was identified and rationalized and guidelines for planning and/or optimization of RED stacks were derived. The design of new profiled membranes, with a chevron corrugation structure, was proposed using computational fluid dynamics (CFD) modeling. The performance of the suggested corrugation geometry was compared with the already existing ones, as well as with the use of conductive and non-conductive spacers. According to the estimations, use of chevron structures grants the highest net power density values, at the best compromise between the mass transfer coefficient and the pressure drop values. Finally, long-term experiments with natural waters were performed, during which fouling was experienced. For the first time, 2D fluorescence spectroscopy was used to monitor RED stack performance, with a dedicated focus on following fouling on ion-exchange membrane surfaces. To extract relevant information from fluorescence spectra, parallel factor analysis (PARAFAC) was performed. Moreover, the information obtained was then used to predict net power density, stack electric resistance and pressure drop by multivariate statistical models based on projection to latent structures (PLS) modeling. The use in such models of 2D fluorescence data, containing hidden, but extractable by PARAFAC, information about fouling on membrane surfaces, considerably improved the models fitting to the experimental data.

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This paper aims to investigate if the market capital charge of the trading book increased in Basel III compared to Basel II. I showed that the capital charge rises by 232% and 182% under the standardized and internal model, respectively. The varying liquidity horizons, the calibration to a stress period, the introduction of credit spread risk, the restrictions on correlations across risk categories and the incremental default charge boost Basel III requirements. Nevertheless, the impact of Expected shortfall at 97.5% is low and long term shocks decrease the charge. The standardized approach presents advantages and disadvantages relative to internal models.

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This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

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A Work Project, presented as part of the requirements for the Award of a Master’s Double Degree in Finance and Financial Economics from NOVA – School of Business and Economics and Maastricht University

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This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.