O objetivo deste trabalho é o desenvolvimento e proposição de modelos matemáticos que possam estimar, com a precisão necessária para efeitos de aplicação prática, o grau ou o nível de segurança de interseções, semaforizadas ou não, usando-se o conceito de oportunidades de conflito de tráfego. O conceito de oportunidade de conflito de tráfego tem sido proposto para obter medidas analíticas de segurança, sendo uma medida correlata de segurança que pode substituir com vantagem as medidas usuais como histórico de acidentes e conflitos de tráfego. Os modelos que usam o conceito de oportunidades de conflito de tráfego necessitam apenas de dados operacionais das interseções, o que torna este parâmetro uma medida potencialmente útil para aplicações práticas na determinação do nível de segurança de um determinado local ou fazer projeções sobre a efetividade de projetos de segurança. São apresentados e discutidos trabalhos de outros autores sobre o assunto, baseados nos quais foram desenvolvidas alternativas às propostas por eles formuladas. Foram analisados pontos não tratados como a aplicação do conceito de oportunidade de conflito de tráfego no período de entreverdes, bem como o estudo de pedestres nas diferentes situações de travessia (nos estudos revisados, somente foi encontrada a análise de travessia de pedestres diante do movimento de conversão à esquerda com fluxo oposto). Foi realizado um estudo piloto numa interseção real com o objetivo de testar metodologias de trabalho de campo, o que permitiu estruturar um trabalho de validação de campo por meio de diagnósticos qualitativos. / The purpose of this work is, through the use of mathematic models, to estimate the level of risk using the concept of traffic conflict opportunity at signalized and unsignalized intersections. The concept of traffic conflict opportunity has been proposed to measure the level of risk, and it is considered as an alternative measure of traffic safety, potentially more useful than the traditional safety measures like traffic accident data or traffic conflict technique. The traffic conflict opportunity models do not require complex field data, only the operational data of the intersection as traffic counts and control parameters are needed. This work presents and analyses other authors studies about this subject, based on which were proposed alternative methods for their formulations. Points such as the safety analysis of the intergreen period using traffic conflict opportunity, not found in those studies, were treated in this work, as well as the pedestrian crossing risk in various situations (in the revised studies, only the analysis of pedestrian crossing risk due to a left turn movement facing an opposing flow was found). In order to test methodologies and to collect field data, it was performed a pilot study at a real intersection. The pilot study allowed to define the goals and the means needed to carry out a field validation by qualitative diagnostic analysis.

In capital market research (CMR) studies of the value relevance of accounting numbers are founded upon the concept that, in equilibrium, the book values are equal to or have some long-term relationship with the market value and that market returns are related to book returns. This thesis seeks to resolve a gap in the CMR by examining 30 selected individual firms listed on the Australian stock market during the period 1950 to 2004, using equilibrium correction modelling techniques. Even these limited prior works used cross-sectional techniques rather than the long-run, time-series, analysis used in this study. Moreover, dynamic analysis in the CMR has tended to focus on indexes or portfolio data rather than using firm-specific case study data of the type modelled here. No prior research has taken this approach using Australian data. The results of this thesis indicated that an equilibrium correction relationship between market values and book values for firms listed on the Australian Stock Exchange (ASX) could be determined by using accounting and macroeconomic regressors. The findings of the thesis were consistent with the literature in terms of the variables suggested and important in the firm's valuation from the three main approaches, the analysts (industry) approach, the finance and accounting theory (textbook) approach and the CMR literature approach. The earnings, dividends and book value variables are significant in their relationships with the firm's market values. The models constructed were typically more informative and had an increased forecasting performance compared with the a priori models tested, based on theory and the literature.

O objetivo deste trabalho é o desenvolvimento e proposição de modelos matemáticos que possam estimar, com a precisão necessária para efeitos de aplicação prática, o grau ou o nível de segurança de interseções, semaforizadas ou não, usando-se o conceito de oportunidades de conflito de tráfego. O conceito de oportunidade de conflito de tráfego tem sido proposto para obter medidas analíticas de segurança, sendo uma medida correlata de segurança que pode substituir com vantagem as medidas usuais como histórico de acidentes e conflitos de tráfego. Os modelos que usam o conceito de oportunidades de conflito de tráfego necessitam apenas de dados operacionais das interseções, o que torna este parâmetro uma medida potencialmente útil para aplicações práticas na determinação do nível de segurança de um determinado local ou fazer projeções sobre a efetividade de projetos de segurança. São apresentados e discutidos trabalhos de outros autores sobre o assunto, baseados nos quais foram desenvolvidas alternativas às propostas por eles formuladas. Foram analisados pontos não tratados como a aplicação do conceito de oportunidade de conflito de tráfego no período de entreverdes, bem como o estudo de pedestres nas diferentes situações de travessia (nos estudos revisados, somente foi encontrada a análise de travessia de pedestres diante do movimento de conversão à esquerda com fluxo oposto). Foi realizado um estudo piloto numa interseção real com o objetivo de testar metodologias de trabalho de campo, o que permitiu estruturar um trabalho de validação de campo por meio de diagnósticos qualitativos. / The purpose of this work is, through the use of mathematic models, to estimate the level of risk using the concept of traffic conflict opportunity at signalized and unsignalized intersections. The concept of traffic conflict opportunity has been proposed to measure the level of risk, and it is considered as an alternative measure of traffic safety, potentially more useful than the traditional safety measures like traffic accident data or traffic conflict technique. The traffic conflict opportunity models do not require complex field data, only the operational data of the intersection as traffic counts and control parameters are needed. This work presents and analyses other authors studies about this subject, based on which were proposed alternative methods for their formulations. Points such as the safety analysis of the intergreen period using traffic conflict opportunity, not found in those studies, were treated in this work, as well as the pedestrian crossing risk in various situations (in the revised studies, only the analysis of pedestrian crossing risk due to a left turn movement facing an opposing flow was found). In order to test methodologies and to collect field data, it was performed a pilot study at a real intersection. The pilot study allowed to define the goals and the means needed to carry out a field validation by qualitative diagnostic analysis.

In the first part of this thesis the prices of six non-ferrous metals (aluminum, copper, lead, nickel, tin, and zinc) are used to assess the forecasting performance of GARCH models. We find that the forecasting performances of GARCH, EGARCH, and TGARCH models are similar. However, we suggest the use of the GARCH model because it is more parsimonious and has a slightly better statistical performance than the other two. In the second part, the prices of six non-ferrous metals and the price of crude oil are used to examine the dynamic links between oil and metal returns by using the BEKK specification of the multivariate GARCH model and the Granger causality-in-variance tests. Results of our study agree with the previous studies in that the crude oil market volatility leads all non-ferrous metal markets. In order to move as far away from the effects of 9/11, daily data for the period December 12, 2003 &ndash / December 15, 2008 is used for the data analysis part of the thesis.

In this masterthesis I have rewied basic approaches to volatility estimating. These approaches are based on classical and Bayesian statistics. I have applied the volatility models for the purpose of volatility forecasting of a different foreign exchange (EURUSD, GBPUSD and CZKEUR) in the different period (from a second period to a day period). I formulate the models EWMA, GARCH, EGARCH, IGARCH, GJRGARCH, jump diffuison with constant volatility and jump diffusion model with stochastic volatility. I also proposed an MCMC algorithm in order to estimate the Bayesian models. All the models we estimated as univariate models. I compared the models according to Mincer Zarnowitz regression. The most successfull model is the jump diffusion model with a stochastic volatility. On the second place they were the GJR- GARCH model and the jump diffusion model with a constant volatility. But the jump diffusion model with a constat volatilit provided much more overvalued results.The rest of the models were even worse. From the rest the IGARCH model is the best but provided undervalued results. All these findings correspond with R squared coefficient.

Forecasts are important to decision-making and risk assessment in many domains. Since current database systems do not provide integrated support for forecasting, it is usually done outside the database system by specially trained experts using forecast models. However, integrating model-based forecasting as a first-class citizen inside a DBMS speeds up the forecasting process by avoiding exporting the data and by applying database-related optimizations like reusing created forecast models. It especially allows subsequent processing of forecast results inside the database. In this demo, we present our prototype F2DB based on PostgreSQL, which allows for transparent processing of forecast queries. Our system automatically takes care of model maintenance when the underlying dataset changes. In addition, we offer optimizations to save maintenance costs and increase accuracy by using derivation schemes for multidimensional data. Our approach reduces the required expert knowledge by enabling arbitrary users to apply forecasting in a declarative way.