In the present work we study families of skew-probability distributions. We will gradually build concept of families of more and more general distributions. For us the most important ones are skew normal distribution, elliptical distri- bution and skew elliptical distribution. On the each of them we will present basic properties and visualize particular examples. At the end we will generate realizations of variates and propose how to estimate the original distribution.

Escolheu-se o método GMM a fim de testar os modelos CAPM não-condicionais (Sharpe-Litner e zero-beta) no mercado de capitais brasileiro, pois as séries dos log-retornos diários de ações analisadas não se mostraram normais e IID. Este trabalho é pioneiro em testar a validade do modelo CAPM zero-beta via GMM no mercado brasileiro. Constatamos que o modelo CAPM de SL, tanto em termos da SELIC como do CDI, não pode ser rejeitado ao nível de 5% para o período de 2/1/00 até 31/12/04. Já para os períodos de 2/1/95 até 31/12/99 e de 2/1/95 até 31/12/04, tal modelo foi rejeitado ao nível de 5%. Dessa forma, para o modelo CAPM de SL, tanto em termos da SELIC como do CDI, o índice BOVESPA se comportou como um portfólio eficiente somente no período de 2/1/00 até 31/12/04. Já para o modelo CAPM zero-beta, verifica-se a sua não rejeição ao nível de 5% nos três períodos analisados acima. / The GMM method have been chosen in order to test non-conditional CAPM (Sharpe-Lintner and zero-beta) model in Brazilian security market, because the daily log-returns series of the analyzed shares did not showed itselves as normal and IID. This dissertation will be pioneer in testing the validity of the CAPM zero-beta model by GMM. We have realized that the SL CAPM model, either in terms of SELIC rate as of CDI rate (risk-free assets), can not be rejected at 5% level for the period from 2/1/00 until 31/12/04. For the periods from 2/1/95 until 31/12/99 and from 2/1/95 until 31/12/04, the given model was rejected at the 5% level. This way, for the SL CAPM model, either in terms of SELIC rate as of CDI rate, the BOVESPA index has behaved as an efficient portfolio only on the period from 2/1/00 until 31/12/04. For the zero-beta CAPM model, it can be verified that we cannot reject it at the 5% level in none of the three periods analyzed above.

Escolheu-se o método GMM a fim de testar os modelos CAPM não-condicionais (Sharpe-Litner e zero-beta) no mercado de capitais brasileiro, pois as séries dos log-retornos diários de ações analisadas não se mostraram normais e IID. Este trabalho é pioneiro em testar a validade do modelo CAPM zero-beta via GMM no mercado brasileiro. Constatamos que o modelo CAPM de SL, tanto em termos da SELIC como do CDI, não pode ser rejeitado ao nível de 5% para o período de 2/1/00 até 31/12/04. Já para os períodos de 2/1/95 até 31/12/99 e de 2/1/95 até 31/12/04, tal modelo foi rejeitado ao nível de 5%. Dessa forma, para o modelo CAPM de SL, tanto em termos da SELIC como do CDI, o índice BOVESPA se comportou como um portfólio eficiente somente no período de 2/1/00 até 31/12/04. Já para o modelo CAPM zero-beta, verifica-se a sua não rejeição ao nível de 5% nos três períodos analisados acima. / The GMM method have been chosen in order to test non-conditional CAPM (Sharpe-Lintner and zero-beta) model in Brazilian security market, because the daily log-returns series of the analyzed shares did not showed itselves as normal and IID. This dissertation will be pioneer in testing the validity of the CAPM zero-beta model by GMM. We have realized that the SL CAPM model, either in terms of SELIC rate as of CDI rate (risk-free assets), can not be rejected at 5% level for the period from 2/1/00 until 31/12/04. For the periods from 2/1/95 until 31/12/99 and from 2/1/95 until 31/12/04, the given model was rejected at the 5% level. This way, for the SL CAPM model, either in terms of SELIC rate as of CDI rate, the BOVESPA index has behaved as an efficient portfolio only on the period from 2/1/00 until 31/12/04. For the zero-beta CAPM model, it can be verified that we cannot reject it at the 5% level in none of the three periods analyzed above.

Dans le cadre de cette thèse, nous nous intéressons à plusieurs problématiques liées au traitement de données 3D. La première concerne la détection et le suivi de personnes dans des séquences d'images de profondeur. Nous proposons une amélioration d'une méthode existante basée sur une étape de segmentation, puis de suivi des personnes. La deuxième problématique abordée est la détection et la modélisation de têtes dans un nuage de points 3D. Pour cela, nous adoptons une approche probabiliste basée sur un nouveau modèle de mélange sphérique. La dernière application traitée est liée à la restauration d'images de profondeur présentant des données manquantes. Nous proposons pour cela d'utiliser une méthode d'approximation de surface par Dm-splines d'interpolation avec changements d'échelle pour approximer et restaurer les données. Les résultats présentés illustrent l'efficacité des algorithmes développés. / In this dissertation, we are interested in several issues related to 3D data processing. The first one concerns people detection and tracking in depth map sequences. We propose an improvement of an existing method based on a segmentation stage followed by a tracking module. The second issue is head detection and modelling in 3D point clouds. In order to do this, we adopt a probabilistic approach based on a new spherical mixture model. The last considered application deals with the restoration of deteriorated depth maps. To solve this problem, we propose to use a surface approximation method based on interpolation Dm-splines with scale transforms to approximate and restore the image. Presented results illustrate the efficiency of the developed algorithms.

Diaconis and Ylvisaker (1979) give necessary conditions for conjugate priors for distributions from the natural exponential family to be proper as well as to have the property of linear posterior expectation of the mean parameter of the family. Their conditions for propriety and linear posterior expectation are also sufficient if the natural parameter space is equal to the set of all d-dimensional real numbers. In this paper their results are extended to characterize when conjugate priors are proper if the natural parameter space is bounded. For the special case where the natural exponential family is through a spherical probability distribution n,we show that the proper conjugate priors can be characterized by the behavior of the moment generating function of n at the boundary of the natural parameter space, or the second-order tail behavior of n. In addition, we show that if these families are non-regular, then linear posterior expectation never holds. The results for this special case are also extended to natural exponential families through elliptical probability distributions.

Title: Semi-infinite programming: theory and portfolio efficiency application Author: Bc. Lukáš Klouda Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Ing. Miloš Kopa, PhD. Supervisor's e-mail address: kopa@karlin.mff.cuni.cz Abstract: The thesis deals with application of semi-infinite programming to a portfolio efficiency testing. The summary of semi-infinite programming, first and second order optimality conditions and duality in linear semi-infinite programming is presented. The optimization problem for a portfolio efficiency testing with respect to the second order stochastic dominance under assumption of discrete, normal, Students and general elliptical distribution is formulated. Conditional value at risk(CVaR) is used as the risk measure, because of its consistency with the second order stochastic dominance relation. Efficiency of index PX with respect to the second order stochastic dominance is tested. The tests are performed using the program GAMS.

Este trabalho objetiva apresentar um estudo detalhado e sistemático de algumas condições de regularidade para inferências baseadas em máxima verossimilhança no modelo de regressão elíptico multivariado com parametrização geral proposto em Lemonte e Patriota (2011). O modelo em estudo tem vários modelos importantes como casos particulares, entre eles temos os modelos lineares e não lineares homocedásticos e heterocedásticos, modelos mistos, modelos heterocedásticos com erros nas variáveis e na equação, modelos multiníveis, entre outros. As condições de regularidade estudadas estão associadas à identificabilidade do modelo, à existência, à unicidade, à consistência e à normalidade assintótica dos estimadores de máxima verossimilhança (EMV) e à distribuição assintótica das estatísticas de testes. Para isso, são enunciadas as condições suficientes e formalizados os teoremas que garantem a existência, unicidade, consistência e normalidade assintótica dos EMV e a distribuição assintótica das estatísticas de teste usuais. Além disso, os resultados de cada teorema são comentados e as demonstrações são apresentadas com detalhes. Inicialmente, considerou-se o modelo sob a suposição de normalidade dos erros, para, na sequência, ser possível generalizar os resultados para o caso elíptico. A fim de exemplificar os resultados obtidos, foram verificadas, analiticamente, a validade de algumas condições e os resultados de alguns teoremas em casos particulares do modelo geral. Ademais, foi desenvolvido um estudo de simulação em que uma das condições é violada adotando o modelo heterocedástico com erros nas variáveis e na equação. Por meio de simulações de Monte Carlo foram avaliados os impactos sobre a consistência e normalidade assintótica dos EMV. / This work aims to present a detailed and systematic study of some regularity conditions for inferences based on maximum likelihood in the multivariate elliptic regression model with general parameterization proposed in Lemonte and Patriota (2011). The model under study has several important models as particular cases, among them we have the linear and non-linear homocedastic and heterocedastic models, mixed models, heterocedastic models with errors in the variables and in the equation, multilevel models, among others. The regularity conditions studied are associated with the identifiability of the model, existence, uniqueness, consistency and asymptotic normality of the maximum likelihood estimators (MLE) and the asymptotic distribution of some test statistics. Sufficient conditions are stated to guarantee the existence, unicity, consistency and asymptotic normality of the MLE and the asymptotic distribution of the usual test statistics. In addition, the results of each theorem are commented and the proof are presented in detail. Initially, the model was considered under the assumption of normality of the errors, and then the results were generalized for the elliptical case. In order to exemplify the attained results, some particular cases of the general model are analyzed analytically, the validity of some conditions and the results of some theorems are verified. In addition, a simulation study is developed with one of the conditions violated under the heterocedastic model with errors in the variables and in the equation. By means of Monte Carlo simulations, the impacts of this violation on the consistency and the asymptotic normality of the MLE are evaluated.

This master's thesis studies portfolio optimization using linear programming algorithms. The contribution of this thesis is an extension of the convex framework for portfolio optimization with Conditional Value-at-Risk, introduced by Rockafeller and Uryasev. The extended framework considers risk measures in this thesis belonging to the intersecting classes of coherent risk measures and distortion risk measures, which are known as coherent distortion risk measures. The considered risk measures belonging to this class are the Conditional Value-at-Risk, the Wang Transform, the Block Maxima and the Dual Block Maxima measures. The extended portfolio optimization framework is applied to a reference portfolio consisting of stocks, options and a bond index. All assets are from the Swedish market. The returns of the assets in the reference portfolio are modelled with elliptical distribution and normal copulas with asymmetric marginal return distributions. The portfolio optimization framework is a simulation-based framework that measures the risk using the simulated scenarios from the assumed portfolio distribution model. To model the return data with asymmetric distributions, the tails of the marginal distributions are fitted with generalized Pareto distributions, and the dependence structure between the assets are captured using a normal copula. The result obtained from the optimizations is compared to different distributional return assumptions of the portfolio and the four risk measures. A Markowitz solution to the problem is computed using the mean average deviation as the risk measure. The solution is the benchmark solution which optimal solutions using the coherent distortion risk measures are compared to. The coherent distortion risk measures have the tractable property of being able to assign user-defined weights to different parts of the loss distribution and hence value increasing loss severities as greater risks. The user-defined loss weighting property and the asymmetric return distribution models are used to find optimal portfolios that account for extreme losses. An important finding of this project is that optimal solutions for asset returns simulated from asymmetric distributions are associated with greater risks, which is a consequence of more accurate modelling of distribution tails. Furthermore, weighting larger losses with increasingly larger weights show that the portfolio risk is greater, and a safer position is taken. / Denna masteruppsats behandlar portföljoptimering med linjära programmeringsalgoritmer. Bidraget av uppsatsen är en utvidgning av det konvexa ramverket för portföljoptimering med Conditional Value-at-Risk, som introducerades av Rockafeller och Uryasev. Det utvidgade ramverket behandlar riskmått som tillhör en sammansättning av den koherenta riskmåttklassen och distortions riksmåttklassen. Denna klass benämns som koherenta distortionsriskmått. De riskmått som tillhör denna klass och behandlas i uppsatsen och är Conditional Value-at-Risk, Wang Transformen, Block Maxima och Dual Block Maxima måtten. Det utvidgade portföljoptimeringsramverket appliceras på en referensportfölj bestående av aktier, optioner och ett obligationsindex från den Svenska aktiemarknaden. Tillgångarnas avkastningar, i referens portföljen, modelleras med både elliptiska fördelningar och normal-copula med asymmetriska marginalfördelningar. Portföljoptimeringsramverket är ett simuleringsbaserat ramverk som mäter risk baserat på scenarion simulerade från fördelningsmodellen som antagits för portföljen. För att modellera tillgångarnas avkastningar med asymmetriska fördelningar modelleras marginalfördelningarnas svansar med generaliserade Paretofördelningar och en normal-copula modellerar det ömsesidiga beroendet mellan tillgångarna. Resultatet av portföljoptimeringarna jämförs sinsemellan för de olika portföljernas avkastningsantaganden och de fyra riskmåtten. Problemet löses även med Markowitz optimering där "mean average deviation" används som riskmått. Denna lösning kommer vara den "benchmarklösning" som kommer jämföras mot de optimala lösningarna vilka beräknas i optimeringen med de koherenta distortionsriskmåtten. Den speciella egenskapen hos de koherenta distortionsriskmåtten som gör det möjligt att ange användarspecificerade vikter vid olika delar av förlustfördelningen och kan därför värdera mer extrema förluster som större risker. Den användardefinerade viktningsegenskapen hos riskmåtten studeras i kombination med den asymmetriska fördelningsmodellen för att utforska portföljer som tar extrema förluster i beaktande. En viktig upptäckt är att optimala lösningar till avkastningar som är modellerade med asymmetriska fördelningar är associerade med ökad risk, vilket är en konsekvens av mer exakt modellering av tillgångarnas fördelningssvansar. En annan upptäckt är, om större vikter läggs på högre förluster så ökar portföljrisken och en säkrare portföljstrategi antas.