Fitting the yield curve

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

O espaço fórum como apoio na formação da rede intersetorial regional em saúde mental: desafios e potencialidades

Pós-graduação em Psicologia - FCLAS

Redes neurais artificiais na previsão da inflação: aplicação como ferramenta de apoio à análise de decisões financeiras em organizações de pequeno porte

As estimações das taxas de inflação são de fundamental importância para os gestores, pois as decisões de investimento estão intimamente ligadas a elas. Contudo, o comportamento inflacionário tende a ser não linear e até mesmo caótico, tornando difícil a sua correta estimação. Essa característica do fenômeno pode tornar imprecisos os modelos mais simples de previsão, acessíveis às pequenas organizações, uma vez que muitos deles necessitam de grandes manipulações de dados e/ou softwares especializados. O presente artigo tem por objetivo avaliar, por meio de análise formal estatística, a eficácia das redes neurais artificiais (RNA) na previsão da inflação, dentro da realidade de organizações de pequeno porte. As RNA são ferramentas adequadas para mensurar os fenômenos inflacionários, por se tratar de aproximações de funções polinomiais, capazes de lidar com fenômenos não lineares. Para esse processo, foram selecionados três modelos básicos de redes neurais artificiais Multi Layer Perceptron, passíveis de implementação a partir de planilhas eletrônicas de código aberto. Os três modelos foram testados a partir de um conjunto de variáveis independentes sugeridas por Bresser-Pereira e Nakano (1984), com defasagem de um, seis e doze meses. Para tal, foram utilizados testes de Wilcoxon, coeficiente de determinação R² e o percentual de erro médio dos modelos. O conjunto de dados foi dividido em dois, sendo um grupo usado para treinamento das redes neurais artificiais, enquanto outro grupo era utilizado para verificar a capacidade de predição dos modelos e sua capacidade de generalização. Com isso, o trabalho concluiu que determinados modelos de redes neurais artificiais têm uma razoável capacidade de predição da inflação no curto prazo e se constituem em uma alternativa razoável para esse tipo de mensuração.

Software and Space: Investigating How a Cosmology Research Group Enacts Infrastructure by Producing Software

Thesis (Ph.D.)--University of Washington, 2016-08

Empirical analysis of the lending decisions of Chinese formal financial institutions in rural areas

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

The polymorhism of crime scene investigation: an exploratory analysis of the influence of crime and forensic intelligence on decisions made by crime scene examiners

A growing body of scientific literature recurrently indicates that crime and forensic intelligence influence how crime scene investigators make decisions in their practices. This study scrutinises further this intelligence-led crime scene examination view. It analyses results obtained from two questionnaires. Data have been collected from nine chiefs of Intelligence Units (IUs) and 73 Crime Scene Examiners (CSEs) working in forensic science units (FSUs) in the French speaking part of Switzerland (six cantonal police agencies). Four salient elements emerged: (1) the actual existence of communication channels between IUs and FSUs across the police agencies under consideration; (2) most CSEs take into account crime intelligence disseminated; (3) a differentiated, but significant use by CSEs in their daily practice of this kind of intelligence; (4) a probable deep influence of this kind of intelligence on the most concerned CSEs, specially in the selection of the type of material/trace to detect, collect, analyse and exploit. These results contribute to decipher the subtle dialectic articulating crime intelligence and crime scene investigation, and to express further the polymorph role of CSEs, beyond their most recognised input to the justice system. Indeed, they appear to be central, but implicit, stakeholders in intelligence-led style of policing.

When decisions of others matter to me: an electrophysiological analysis.

Background: Actions of others may have immediate consequences for oneself. We probed the neural responses associated with the observation of another person"s action using event-related potentials in a modified gambling task. In this task a"performer" bet either a higher or lower number and could win or lose this amount. Three different groups of"observers" were also studied. The first (neutral) group simply observed the performer"s action, which had no consequences for the observers. In the second (parallel) group, wins/losses of the performer were paralleled by similar wins and losses by the observer. In the third (reverse) group, wins of the performer led to a loss of the observer and vice versa. Results: ERPs of the performers showed a mediofrontal feedback related negativity (FRN) to losses. The neutral and parallel observer groups did similarly show an FRN response to the performer"s losses with a topography indistinguishable from that seen in the performers. In the reverse group, however, the FRN occurred for wins of the performer which translated to losses for the observer. Conclusions: Taking into account previous experiments, we suggest that the FRN response in observers is driven by two evaluative processes (a) related to the benefit/loss for oneself and (b) related to the benefit/loss of another person

An analysis of household farm investment decisions under varying land tenure arrangements in Ghana

Land tenure insecurity is widely perceived as a disincentive for long-term land improvement investment hence the objective of this paper is to evaluate how tenure (in)security associated with different land use arrangements in Ghana influenced households’ plot level investment decisions and choices. The paper uses data from the Farmer-Based Organisations (FBO) survey. The FBO survey collected information from 2,928 households across three ecological zones of Ghana using multistaged cluster sampling. Probit and Tobit models tested the effects of land tenancy and ownership arrangements on households’ investment behaviour while controlling other factors. It was found that marginal farm size was inversely related to tenure insecurity while tenure insecurity correlate positively with value of farm land and not farm size. Individual ownership and documentation of land significantly reduced the probability of households losing uncultivated lands. Individual land ownership increased both the probability of investing and level of investments made in land improvement and irrigation probably due to increasing importance households place on land ownership. Two possible explanations for this finding are: First, that land markets and land relations have changed significantly over the last two decades with increasing money transaction and fixed agreements propelled by population growth and increasing value of land. Secondly, inclusion of irrigation investment as a long term investment in land raises the value of household investment and the time period required to reap the returns on the investments. Households take land ownership and duration of tenancy into consideration if the resource implications of land investments are relatively huge and the time dimension for harvesting returns to investments is relatively long.

Judgments, forecasts and decisions: an analysis of fund managers over time

Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

Brazilian Students and Working Capital: An Analysis of Their Decisions When Using Virtual Market Business Games

This study aims to demonstrate that data from business games can be an important resource for improving efficiency and effectiveness of learning. The proposal presented here was developed from preliminary studies of data from Virtual Market games that pointed the possibility of identifying gaps in learning by analyzing the decisions of students. This proposal helps students to refine their learning processes and equips tutors with strategies for teaching and student assessment. The proposal also complements the group discussion and/or debriefing, which are widely used to enhance learning mediated by games. However, from a management perspective the model has the potential to be erroneous and miss opportunities, which cannot be detected because of the dependence on the characteristics of the individual, such as ability to communicate and work together. To illustrate the proposed technique, data sets from two business games were analyzed with the focus on managing working capital and it was found that students had difficulties managing this task. Similar trends were observed in all categories of students in the study-undergraduate, postgraduate and specialization. This discovery led us to the analysis of data for decisions made in the performance of the games, and it was determined that indicators could be developed that were capable of indentifying inconsistencies in the decisions. It was decided to apply some basic concepts of the finance management, such as management of the operational and non-operational expenditures, as well as production management concepts, such as the use of the production capacity. By analyzing the data from the Virtual Market games using the indicator concept, it was possible to detect the lack of domain knowledge of the students. Therefore, these indicators can be used to analyze the decisions of the players and guide them during the game, increasing their effectiveness and efficiency. As these indicators were developed from specific content, they can also be used to develop teaching materials to support learning. Viewed in this light, the proposal adds new possibilities for using business games in learning. In addition to the intrinsic learning that is achieved through playing the games, they also assist in driving the learning process. This study considers the applications and the methodology used.

Method for evaluating the significance of macro-economic variables in the analysis of technology incorporation decisions

Includes bibliography

Sharing decisions in breast cancer care: Development of the Decision Analysis System for Oncology (DAS-O) to identify shared decision making during treatment consultations

Shared Decision Making (SDM) is widely accepted as the preferred method for reaching treatment decisions in the oncology setting including those about clinical trial participation: however, there is some disagreement between researchers over the components of SDM. Specific standardized coding systems are needed to help overcome this difficulty.