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La literatura empírica ha encontrado evidencia de una tendencia hacia el envejecimiento de la población en América Latina. Este documento analiza el impacto de los cambios demográficos sobre la pobreza utilizando las proyecciones demográficas de la Organización de las Naciones Unidas junto con distintos escenarios en la estructura educativa. La metodología utilizada en este trabajo es la de microsimulaciones econométricas. Su principal innovación consiste en proponer el método de máxima verosimilitud empírica como estrategia de simulación de ponderadores. Bajo todos los supuestos del modelo de simulación, los resultados sugieren que si la dinámica poblacional se mantiene los niveles de pobreza se verán reducidos. Sin embargo el efecto cuantitativo es muy débil, dejando un amplio margen para la planificación de políticas económicas orientadas a la reducción de la pobreza.

This dissertation focuses on (river) forecasting, but also includes a study on stormwater treatment. Using forecasts for decision-making is complicated by their inherent uncertainty. An interview-based study qualitatively and a survey empirically investigate forecast use in emergency management. Emergency managers perceive uncertainty as a given rather than as a problem. To cope with the uncertainty, decision-makers gather as much information as possible; forecasts are only one piece of information among many. For decision-making, emergency managers say that they rely more on radar than on river forecasting. However, forecasts play an important role in communication with the public, because they are the official interpretation of the situation. Emergency managers can add a lot of value to those forecasts by combining them with local knowledge, but might not do so because of accountability concerns. Forecasts must have value to emergency managers, because those with more work experience rely more on them than those without. Another study further develops the application of quantile regression to generate probabilistic river forecasts. Compared to existing research, this study includes a larger number of river gages; includes more independent variables; and studies longer lead times. Additionally, it is the first to apply this method to the U.S. American context. It was found that the model has to be customized for each river gage for extremely high event thresholds. For other thresholds and across lead times, a one-size-fits-all model suffices. The model performance is robust to the size of the training dataset, but depends on the year, the river gage, lead time and event threshold that are being forecast. An additional study considers the robustness of stormwater management to the amount of runoff. Impervious surfaces, such as roads and parking lots, can increase the amount of runoff and lead to more pollution reaching streams, rivers, and lakes. Best Management Practices (BMPs) reduce the peak discharge into the storm sewer system and remove pollutants such as sediments, phosphorus and nitrogen from the stormwater runoff. Empirically, it is found that BMP effectiveness decreases sooner, steeper and deeper with increasing sizes of storm events than assumed in current computer models.

In this thesis, we introduce a concept of directional quantile envelopes, the intersection of the halfspaces determined by directional quantiles, and show that they allow for explicit probabilistic interpretation, compared to other multivariate quantile concepts. Directional quantile envelopes provide a way to perform multivariate quantile regression: to ``regress contours'' on covariates. We also develop theory and algorithms for an important application of multivariate quantile regression in biometry: bivariate growth charts. We prove that directional quantiles are continuous and derive their closed-form expression for elliptically symmetric distributions. We provide probabilistic interpretations of directional quantile envelopes and establish that directional quantile envelopes are essentially halfspace depth contours. We show that distributions with smooth directional quantile envelopes are uniquely determined by their envelopes. We describe an estimation scheme of directional quantile envelopes and prove its affine equivariance. We establish the consistency of the estimates of directional quantile envelopes and describe their accuracy. The results are applied to estimation of bivariate extreme quantiles. One of the main contributions of this thesis is the construction of bivariate growth charts, an important application of multivariate quantile regression. We discuss the computation of our multivariate quantile regression by developing a fast elimination algorithm. The algorithm constructs the set of active halfspaces to form a directional quantile envelope. Applying this algorithm to a large number of quantile halfspaces, we can construct an arbitrary exact approximation of the direction quantile envelope. In the remainder of the thesis, we exhibit the connection between depth contours and directional regression quantiles (Laine, 2001), stated without proof in Koenker (2005). Our proof uses the duality theory of primal-dual linear programming. Aiming at interpreting halfspace depth contours, we explore their properties for empirical distributions, absolutely continuous distributions and certain general distributions. Finally, we propose a generalized quantile concept, depth quantile, inspired by halfspace depth (Tukey, 1975) and regression depth (Rousseeuw and Hubert, 1999). We study its properties in various data-analytic situations: multivariate and univariate locations, regression with and without intercept. In the end, we show an example that while the quantile regression of Koenker and Bassett (1978) fails, our concept provides sensible answers. / Statistics

Title: Statistical inference based on saddlepoint approximations Author: Radka Sabolová Abstract: The saddlepoint techniques for M-estimators have proved to be very accurate and robust even for small sample sizes. Based on these results, saddle- point approximations of density of regression quantile and saddlepoint tests on the value of regression quantile were derived, both in parametric and nonpara- metric setup. Among these, a test on the value of regression quantile based on the asymptotic distribution of averaged regression quantiles was also proposed and all these tests were compared in a numerical study to the classical tests. Finally, special case of Kullback-Leibler divergence in exponential family was studied and saddlepoint approximations of the density of maximum likelihood estimator and sufficient statistic were also derived using this divergence. 1

This thesis is an attempt to bridge some research gaps in the area of behavioural finance and investment through adopting the three essays scheme of PhD dissertations. There is a widespread belief that the traditional finance theory failed to provide a sufficient and plausible explanation for (1) what motivates individual investors to trade, (2) the pattern of their trading and the formation of their portfolios, (3) the determinants of cross section of expected returns other than risk. Behavioural Finance, however, offers more realistic assumptions based on two building blocks; behavioural biases of irrational investors and the limits of arbitrage that prevent the arbitrageurs from correcting mispricing and pushing prices back to fundamental values. This dissertation is structured as follows: In the first essay, the disposition effect is defined as the propensity of investors to realize gains too early while being loath to realize losses. Capital gains overhang is a measure of unrealized capital gains and losses that is associated with the disposition effect and the trading activities of behaviourally biased investors. We discover that firm characteristics can play a role in explaining variations in the capital gains overhang that is consistent with the activities of behaviourally biased and disposition investors. Specifically, we find that capital gains overhang is increasing in firm attributes that attract behaviourally biased investors, namely, earnings per share, leverage, growth and size. Capital gains overhang is also declining in market liquidity, possibly because liquidity allows behaviourally biased investors to excessively trade shares and beta and corporate earnings, probably because when high risk and inefficient firms experience losses, disposition investors experience capital losses that they are reluctant to realize. In the second essay, quantile regressions are employed to analyse the relationship between the unrealized capital gains overhang and expected returns. The ability of the disposition effect to generate momentum is also considered for the extreme expected return regions (0.05th) and (0.95th) quantiles. To do so, 450,617 observations belonging to 5176 US firms are employed, covering a time span from January 1998 to June 2015. Following the methodology of Grinblatt and Han (2005), the findings show significant differences across various quantiles in terms of signs and magnitudes. These findings indicate a nonlinear relationship between capital gains overhang and expected returns since the impact of capital gains overhang as a proxy for disposition effect on expected returns vary across the expected return distribution. More precisely, the coefficients of capital gains overhang are significantly positive and decline as the expected returns quantiles increase from the lowest to the median expected return quantiles. However, they become significantly negative and rise with the increase in expected returns quantiles above median expected returns quantiles. The findings also suggest that the disposition effect is not a good noisy proxy for momentum at the lowest expected return quantile (0.05th). However, interestingly it seems to generate contrarian in returns at the highest expected returns quantile (0.95th). In the third essays, we try to discover systematic disagreements in momentum, asymmetric volatility and the idiosyncratic risk momentum return relationship between high-tech stocks and low-tech stocks. We develop several hypotheses that suggest greater momentum profits, fainter asymmetric volatility and weaker idiosyncratic risk-momentum return relation in the high-tech stocks relative to the low tech stocks. To this end, we divide 5795 stocks that are listed in the Russell 3000 index from January 1995 to December 2015 into two samples SIC code and analysed them using the Fama French with GJR-GARCH-M term. The results show that the high-tech stocks provide greater momentum profits especially for portfolios that have holding and ranking periods of less than 12 months. In most cases momentum returns in the high-tech stocks explain a symmetric response to good and bad news while the momentum returns in the low-tech stocks show an asymmetric response. Finally, the idiosyncratic risk-momentum return relation is insignificant for high-tech stocks while it is significant and negative for low-tech stocks. That is, as idiosyncratic risk increases, momentum decreases for low-tech stocks. These findings are robust to different momentum strategies and to different breakpoints.

This thesis analyses financial contagion between a reference EU market - Germany and markets of five countries which are actively seeking to become a part of European Union - Montenegro, Serbia, Turkey, Bosnia and Macedonia in the period of March 2006 to March 2018. We apply quantile regression framework to analyse contagion which we base on the occurrence and degree of coexceedances between the reference and analysed market. The results indicate that contagion between stock markets exists, however in different degree for each of the analysed markets. In addition we apply the regression framework specifically for period of financial crisis of 2008 to demonstrate that contagion is stronger during turbulent market periods. JEL Classification G01, G14, G15 Keywords coexceedance, quantile regression, contagion, stock markets Author's e-mail 80605682@fsv.cuni.cz Supervisor's e-mail roman.horvath@fsv.cuni.cz

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Since the origins of modern finance theory, interdependence is an issue between assets as the search for diversification ends with a better portfolio. Many studies and many approaches have been given to answer to the questions of correlation, covariance and interdependence but the subprime crises and the almost meltdown of financial markets throughout the globe, proved that portfolios were not efficiently diversified. The concept of diversification and the risk measures did not prevent from hundreds of companies worldwide to go belly up. This work aims to give another approach to interdependence, the quantile regression, including a volatility measure of the American Market regressed with other international major players grouped by their geographic region. This work stars in 2000 and ends in 2012, collecting data through four major events: the Nasdaq burst, the 9/11, the Subprime and the European crises. Our findings are: countries geographically close to the US have display higher levels of interdependence; European countries are in majority also highly integrated with the US; and lastly but more importantly, integration is increasing. / Desde as origens das teorias em finanças se estuda a interdependência entre os ativos em busca dos benefícios de uma diversificação eficiente. Inúmeros estudos foram realizados e várias abordagens foram dadas ao problema da correlação, covariância e interdependência, mas a crise do Subprime e o consequente quase colapso dos mercados mundiais, provaram que os métodos utilizados até então não se mostraram eficientes, pois não foram capazes de evitar a evaporação de centenas de instituições financeiras, de diferentes mercados e extrema perda de valor de ativos dos mais diversificados portfólios e carteiras com diversos níveis de risco. Esse trabalho visa dar um novo enfoque ao estudo da interdependência, o da regressão quantílica com um componente de volatilidade do mercado americano regredido contra os retornos dos principais mercados mundiais, divididos por região geográfica, relacionados com o mercado americano através de seu principal índice, o S&P500, desde os anos de 2000 até 2012. Ao final, constata-se que os países geograficamente mais próximos dos Estados Unidos sofrem com maior integração, bem como a maioria e dos países do continente europeu, e principalmente que as integrações vem aumentando entre grande parte dos países estudados e o principal mercado mundial.

Cette thèse de doctorat est une première tentative d'examiner si les réglementations bancaires ont le même impact sur la stabilité et l'efficience des banques islamiques que sur celles des banques conventionnelles. Suite aux nouvelles recommandations de Bâle III, nous étudions l'impact des exigences minimales en matière de fonds propres, de liquidité et de levier financier sur la stabilité et l'efficience des banques islamiques comparativement aux banques conventionnelles. Une première étude exploratoire utilise l'analyse en composantes principales (ACP), les méthodes Logit et Probit et les régressions MCO pour montrer que les banques islamiques disposent d'un capital plus élevé, qu'elles sont plus liquides, plus profitables, mais moins stables que leurs homologues conventionnelles. Une deuxième étude empirique examine la stabilité des banques islamiques et utilise la régression quantile pour montrer que les banques islamiques sont moins stables que les banques classiques. L'étude prouve également que des exigences de fonds propres renforcées améliorent la stabilité des banques islamiques les plus petites et les plus liquides, tandis que le levier financier est négativement associé à la stabilité de ce type de banques. Des contraintes de liquidité plus fortes renforcent la stabilité des grandes banques islamiques alors que l'effet est inverse pour les petites banques. Enfin, nous examinons l'efficience des banques islamiques en utilisant la méthode d'enveloppement des données (DEA). Nous constatons que les banques islamiques sont plus efficientes que les banques conventionnelles. Nous trouvons aussi que des exigences de capital et de liquidité accrues pénalisent l'efficience des petites banques islamiques très liquides, alors que l'inverse est vrai pour le levier financier. Ces résultats montrent notamment qu'en matière de réglementation du capital pour les petites banques islamiques très liquides, un choix est à opérer entre une efficience accrue ou une stabilité renforcée. / This PhD dissertation is the first attempt to examine whether banking regulations have the same impact on the stability and the efficiency of Islamic than for conventional banks. We benefit of Basel III recommendations to investigate the impact of bank capital, liquidity and leverage requirements on the stability and the efficiency of Islamic banks compared to conventional banks. A first exploratory study uses Principal Component Analysis, Logit and Probit methods, and OLS regressions and shows that Islamic banks have higher capital, liquidity, and profitability, but that they are less stable than their conventional counterparts. A second empirical study examines the stability of Islamic banks using conditional quantile regressions and proves that Islamic banks are less stable than conventional banks. It also shows that higher capital and lower leverage improve the adjusted profits of small and highly liquid Islamic banks. Liquidity is positively associated with the stability of large Islamic banks while an opposite effect is detected when small Islamic banks are examined. Finally, we study the efficiency of Islamic banks using Data Envelopment Analysis (DEA) and find that Islamic banks are more efficient than conventional banks. We also find that higher capital and liquidity requirements penalize the efficiency of small and highly liquid Islamic banks, while the opposite is true for financial leverage. These results show that concerning capital requirements for small and highly liquid Islamic banks, a possible trade-off could be found between stability and efficiency.

Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2017-07-06T14:30:18Z No. of bitstreams: 1 arquivototal.pdf: 6614647 bytes, checksum: 21e96f422787eaffc9d7176f0a15e007 (MD5) / Made available in DSpace on 2017-07-06T14:30:18Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 6614647 bytes, checksum: 21e96f422787eaffc9d7176f0a15e007 (MD5) Previous issue date: 2017-02-20 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / In this dissertation the beta regression models with variable dispersion and quantile regression are discussed. Therefore, an introduction was made with the objective of motivating its discussion in epidemiological studies, emphasizing the problematization around obesity. The application of these methods considered a real data set, obtained from public information sources, referring to adult obesity in the nations in the year 2014. After the descriptive analysis of the data it was verified that 50% of the nations present values of the proportion of obese adults greater than 0.20. In addition, viewing the obesity map by nation showed that the highest concentration of countries with the lowest obesity values is found in the continents of Asia and Africa. On the other hand, the highest concentrations of obese are found in the continents of America and Europe. Also, from the graphical analysis of the box-plot a possible difference in the proportions of obese adults between the continents of America and Europe with those of Africa and Asia was observed. After adjusting the beta and quantile regression models it was verified that the covariates average alcohol consumption in liters per person, percentage of insufficient physical activity and percentage of the population living in urban areas have a positive effect on the response variable. That is, individually such covariables tend to increase obesity values in the countries when the other covariables remain constant. In addition, the life expectancy variable in years presented a positive effect and was significant only for the variable regression beta regression model. Finally, analyzing the measures of prediction errors, it was verified that the estimates from the beta regression are more accurate when the mean square error and the total percentage error were evaluated. Therefore, for questions of predicting values for adult obesity in the nations in 2014, the beta regression model with variable dispersion was more suitable for this purpose. / Nesta dissertação são abordados os modelos de regressão beta com dispersão variável e de regressão quantílica. Para tanto, foi feita uma introdução com objetivo de motivar sua discussão em estudos epidemiológicos, enfatizando a problematização em torno da obesidade. A aplicação destes métodos considerou um conjunto de dados reais, obtidos a partir de fontes de informação pública, referente a obesidade adulta nas nações no ano de 2014. Após a análise descritiva dos dados verificou-se que 50% das nações apresentam valores da proporção de adultos obesos maiores do que 0.20. Além disso, visualizando o mapa da obesidade por nação constatou-se que a maior concentração de países com menores valores de obesidade encontra-se nos continentes da Ásia e África. Por outro lado, as maiores concentrações de obesos encontram-se nos continentes da América e Europa. Ainda, a partir da análise gráfica do box-plot foi observado uma possível diferença nas proporções de adultos obesos entre os continentes da América e Europa com os da África e Ásia. Após ajustar os modelos de regressão beta e quantílica verificou-se que as covariáveis consumo médio de álcool em litros por pessoa, porcentagem de atividade física insuficiente e porcentagem da população que vivem em áreas urbanas apresentam efeito positivo sobre a variável resposta. Ou seja, individualmente tais covariáveis tendem a aumentar os valores de obesidade nos países quando as demais covariáveis permanecem constantes. Além disso, a variável expectativa de vida em anos apresentou efeito positivo e foi significativa apenas para o modelo de regressão beta com dispersão variável. Por fim, analisando as medidas de erros de previsão verificou-se que as estimativas oriundas da regressão beta são mais precisas quando avaliado o erro quadrático médio e o erro percentual total. Portanto, para questões de predizer valores referentes a obesidade adulta nas nações em 2014 o modelo de regressão beta com dispersão variável se mostrou mais adequado para tal propósito.