1000 resultados para financial constraint


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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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

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Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.

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The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

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This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

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This paper analyses, through a dynamic panel data model, the impact of the Financial and the European Debt crisis on the equity returns of the banking system. The model is also extended to specifically investigate the impact on countries who received rescue packages. The sample under analysis considers eleven countries from January 2006 to June 2013. The main conclusion is that there was in fact a structural change in banks’ excess returns due to the outbreak of the European Debt Crisis, when stock markets were still recovering from the Financial Crisis of 2008.

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The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

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The purpose of the project is to measure the impact of fiscal policy on the Portuguese GDP and how it may vary according to the state of the financial market. A Threshold VAR model is presented in which the two regimes are found using a financial stress index that divides the economy into a situation of financial stress and financial stability.

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In this paper we analyze the role of deposit insurance in providing the market with liquidity in times of financial turmoil. To do so, we look at the variation in insured and uninsured deposits between 2005Q3 and 2011Q3, controlling for liquidity, solvency and capital adequacy indicators, and find evidence that deposit insurance does provide some confidence in keeping funds in banks in times of turmoil. Additionally we follow an event study methodology to assess the impact of deposit insurance oriented policies on bank holding companies stock market returns, and find a TBTF effect.

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The 2008 global financial crisis caused the collapse of business key sectors, declines in consumer wealth and a fall in economic activity resulting in a global recession. In some European countries, the 2008 crisis contributed to a sovereign-debt crisis which had a strong impact in Southern European countries. The construction sector was particularly affected, with budget cuts disturbing public investment and no financing available for private constructors. This report intends to explain how Mota-Engil, faced this situation of low growth, and which strategies were adopted by the management to overcome the difficult economic conjecture, mainly in its domestic market: Portugal. The report is organized as a case-study. The first part, the case narrative, is subdivided into 6 parts, and the second part is the teaching note. The teaching note is constituted by the four questions and their respective responses.

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This thesis focus on the measurement and accounting of contributions received by nonprofit organizations, as they are a significant component of revenues nowadays. A survey was developed and forward to 38 different NPOs, with the goal of understanding their motivations and what advantages and disadvantages they believe would result if they start to measure and account for all kinds of contributions. They presented many advantages from this practice; however, some are not doing it due to the difficulties in valuing contributions with no market value which would require a higher workload, waste of resources and time to be taken from other important activities.

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Corporate social responsibility (CSR) literature has largely neglected consumers’ perceptions in the debate regarding the role of CSR in the aftermath of the financial crisis. In that context, this study aims to test the possibility that consumers’ perceptions of CSR level, firm reputation and brand trust, might depend on the type of industry sector of a firm, the level of fit of an initiative or both. By conducting a survey on Portuguese consumers and running a two-way analysis of variance, it suggests that solely the type of industry sector has an effect on consumer perception and that consumers are less tolerable of controversial industries.