Discrete time models of the term structure of interest rates and interest rate contingent claims

In this study, discrete time one-factor models of the term structure of interest rates and their application to the pricing of interest rate contingent claims are examined theoretically and empirically. The first chapter provides a discussion of the issues involved in the pricing of interest rate contingent claims and a description of the Ho and Lee (1986), Maloney and Byrne (1989), and Black, Derman, and Toy (1990) discrete time models. In the second chapter, a general discrete time model of the term structure from which the Ho and Lee, Maloney and Byrne, and Black, Derman, and Toy models can all be obtained is presented. The general model also provides for the specification of an additional model, the ExtendedMB model. The third chapter illustrates the application of the discrete time models to the pricing of a variety of interest rate contingent claims. In the final chapter, the performance of the Ho and Lee, Black, Derman, and Toy, and ExtendedMB models in the pricing of Eurodollar futures options is investigated empirically. The results indicate that the Black, Derman, and Toy and ExtendedMB models outperform the Ho and Lee model. Little difference in the performance of the Black, Derman, and Toy and ExtendedMB models is detected. ^

R-script modified VS-Lite model

Drought is a key factor affecting forest ecosystem processes at different spatio-temporal scales. For accurately modeling tree functioning ? and thus for producing reliable simulations of forest dynamics ? the consideration of the variability in the timing and extent of drought effects on tree growth is essential, particularly in strongly seasonal climates such as in the Mediterranean area. Yet, most dynamic vegetation models (DVMs) do not include this intra-annual variability of drought effects on tree growth. We present a novel approach for linking tree-ring data to drought simulations in DVMs. A modified forward model of tree-ring width (VS-Lite) was used to estimate seasonal- and site-specific growth responses to drought of Scots pine (Pinus sylvestris L.), which were subsequently implemented in the DVM ForClim. Ring-width data from sixteen sites along a moisture gradient from Central Spain to the Swiss Alps, including the dry inner Alpine valleys, were used to calibrate the forward ring-width model, and inventory data from managed Scots pine stands were used to evaluate ForClim performance. The modified VS-Lite accurately estimated the year-to-year variability in ring-width indices and produced realistic intra-annual growth responses to soil drought, showing a stronger relationship between growth and drought in spring than in the other seasons and thus capturing the strategy of Scots pine to cope with drought. The ForClim version including seasonal variability in growth responses to drought showed improved predictions of stand basal area and stem number, indicating the need to consider intra-annual differences in climate-growth relationships in DVMs when simulating forest dynamics. Forward modeling of ring-width growth may be a powerful tool to calibrate growth functions in DVMs that aim to simulate forest properties in across multiple environments at large spatial scales.

Big bang bifurcations in von Bertalanffy’s dynamics with strong and weak Allee effects

The main purpose of this work was to study population dynamic discrete models in which the growth of the population is described by generalized von Bertalanffy's functions, with an adjustment or correction factor of polynomial type. The consideration of this correction factor is made with the aim to introduce the Allee effect. To the class of generalized von Bertalanffy's functions is identified and characterized subclasses of strong and weak Allee's functions and functions with no Allee effect. This classification is founded on the concepts of strong and weak Allee's effects to population growth rates associated. A complete description of the dynamic behavior is given, where we provide necessary conditions for the occurrence of unconditional and essential extinction types. The bifurcation structures of the parameter plane are analyzed regarding the evolution of the Allee limit with the aim to understand how the transition from strong Allee effect to no Allee effect, passing through the weak Allee effect, is realized. To generalized von Bertalanffy's functions with strong and weak Allee effects is identified an Allee's effect region, to which is associated the concepts of chaotic semistability curve and Allee's bifurcation point. We verified that under some sufficient conditions, generalized von Bertalanffy's functions have a particular bifurcation structure: the big bang bifurcations of the so-called box-within-a-box type. To this family of maps, the Allee bifurcation points and the big bang bifurcation points are characterized by the symmetric of Allee's limit and by a null intrinsic growth rate. The present paper is also a significant contribution in the framework of the big bang bifurcation analysis for continuous 1D maps and unveil their relationship with the explosion birth and the extinction phenomena.

Dynamic-Data Driven Real-Time Identification for Electric Power Systems

Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

Credit risk & forward price models

Doutoramento em Gestão

Trends in NE Atlantic landings (southern Portugal): identifying the relative importance of fisheries and environmental variables

Time series of commercial landings from the Algarve (southern Portugal) from 1982 to 1999 were analyzed using min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA). These techniques were used to identify trends and explore the relationships between the response variables (annual landings of 12 species) and explanatory variables [sea surface temperature, rainfall, an upwelling index, Guadiana river (south-east Portugal) flow, the North Atlantic oscillation, the number of licensed fishing vessels and the number of commercial fishermen]. Landings were more highly correlated with non-lagged environmental variables and in particular with Guadiana river flow. Both techniques gave coherent results, with the most important trend being a steady decline over time. A DFA model with two explanatory variables (Guadiana river flow and number of fishermen) and three common trends (smoothing functions over time) gave good fits to 10 of the 12 species. Results of other models indicated that river flow is the more important explanatory variable in this model. Changes in the mean flow and discharge regime of the Guadiana river resulting from the construction of the Alqueva dam, completed in 2002, are therefore likely to have a significant and deleterious impact on Algarve fisheries landings.

A multi-model approach to evaluate the role of environmental variability and fishing pressure in sardine fisheries

Understanding the fluctuations in population abundance is a central question in fisheries. Sardine fisheries is of great importance to Portugal and is data-rich and of primary concern to fisheries managers. In Portugal, sub-stocks of Sardina pilchardus (sardine) are found in different regions: the Northwest (IXaCN), Southwest (IXaCS) and the South coast (IXaS-Algarve). Each of these sardine sub-stocks is affected differently by a unique set of climate and ocean conditions, mainly during larval development and recruitment, which will consequently affect sardine fisheries in the short term. Taking this hypothesis into consideration we examined the effects of hydrographic (river discharge), sea surface temperature, wind driven phenomena, upwelling, climatic (North Atlantic Oscillation) and fisheries variables (fishing effort) on S. pilchardus catch rates (landings per unit effort, LPUE, as a proxy for sardine biomass). A 20-year time series (1989-2009) was used, for the different subdivisions of the Portuguese coast (sardine sub-stocks). For the purpose of this analysis a multi-model approach was used, applying different time series models for data fitting (Dynamic Factor Analysis, Generalised Least Squares), forecasting (Autoregressive Integrated Moving Average), as well as Surplus Production stock assessment models. The different models were evaluated, compared and the most important variables explaining changes in LPUE were identified. The type of relationship between catch rates of sardine and environmental variables varied across regional scales due to region-specific recruitment responses. Seasonality plays an important role in sardine variability within the three study regions. In IXaCN autumn (season with minimum spawning activity, larvae and egg concentrations) SST, northerly wind and wind magnitude were negatively related with LPUE. In IXaCS none of the explanatory variables tested was clearly related with LPUE. In IXaS-Algarve (South Portugal) both spring (period when large abundances of larvae are found) northerly wind and wind magnitude were negatively related with LPUE, revealing that environmental effects match with the regional peak in spawning time. Overall, results suggest that management of small, short-lived pelagic species, such as sardine quotas/sustainable yields, should be adapted to a regional scale because of regional environmental variability.

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

Goals and reputations amongst young children - The validation of the importance of goals and reputation enhancement scales

The aim of the present research was to provide school psychologists with valid instruments with which to assess the goals and reputations of young children. This was achieved by ascertaining whether the factor structures and the second-order factor models of the high school versions of the Importance of Goals (Carroll, et al., 1997) and Reputation Enhancement Scales (Carroll, et al., 1999) could be replicated with a primary school sample. Eight hundred and eighty-six 10 to 12 year old children were administered modified versions of the two scales, which were combined and renamed the Children's Activity Questionnaire. For the two scales, the factor structure proved replicable and reliable with the primary school sample. A comparison between the factor loadings of the primary school and the high school samples using the coefficient of congruence procedure demonstrated similarity indicating that the scales are replicable and able to be used with a younger primary school sample. Structural equation modelling indicated that the second-order factor structure of the Importance of Goals Scale was acceptable but this was not the case for the second-order factor structure of the Reputation Enhancement Scale.

An assumption-driven case-specific model editor

A case sensitive intelligent model editor has been developed for constructing consistent lumped dynamic process models and for simplifying them using modelling assumptions. The approach is based on a systematic assumption-driven modelling procedure and on the syntax and semantics of process,models and the simplifying assumptions.

Systematic and liquidity risk in sub-prime mortgage-backed assets

The mis-evaluation of risk in securitized financial products is central to understanding the global financial crisis. This paper characterizes the evolution of risk factors affecting collateralized debt obligations (CDOs) based on subprime mortgages. A key feature of subprime mortgage-backed indices is that they are distinct in their vintage of issuance. Using a latent factor framework that incorporates this vintage effect, we show the increasing importance of common factors on more senior tranches during the crisis. An innovation of the paper is that we use the unbalanced panel structure of the data to identify the vintage, credit, common and idiosyncratic effects from a state-space specification.

Persistência no desempenho dos fundos de investimento em ações

Mestrado em Contabilidade e Análise Financeira

On the cloud deployment of a session abstraction for service/data aggregation

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A narrativa da liderança escolar: os alunos como agentes de revelação

Publicado em "Educação, territórios e desenvolvimento humano: atas do I Seminário Internacional, Vol. I – conferências e intervenções". ISBN 978-989-96186-9-5

Sensitivity of the Amazon biome to high resolution climate change projections

ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.