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本文以臺灣八大類股指數結合分量迴歸模型進行價量關係研究。有別於過去文獻多使用大盤指數進行分析，本文將以產業類股指數作為研究目標。實證結果顯示 : 「價量背離」與「價量齊揚」的效果同時存在於臺灣股市各個類股的價量關係中，且後者的效果普遍高於前者；而在八個產業類股中，尤以金融業在兩側分量的效果大於其他產業。另外，在相同的交易機制下，並非所有產業的價量關係皆會受到漲跌幅限制的影響而改變。本文更進一步選用法人持股佔該類股市值比作為資訊不對稱之代理變數，結果發現資訊不對稱程度較高的產業，在價量齊揚時，法人持股比的係數為負，代表在市場出現正報酬時，會有抑制股價上揚的效果；反之，在負報酬時，會加深股價下挫的力道。 / This research examines the relation between stock return and trading volume of Taiwan’s eight industries using quantile regression model. Our empirical results show that, for most industry indices, both large positive returns and large negative returns are usually accompanied by a large trading volume, with the effect of large positive returns being stronger. Among all industries, the financial industry has the most significant effect in either situation. But for some industries, the price-volume relations change when returns approach the price limits. In addition, we also emphasize the impact of information asymmetry, using ownership share of institutional investors as the proxy variable. The results show that, in the situation of positive returns with large trading volume, the institutional trading variable will restrain stock price from continually rising. In contrast, in the situation of negative returns with large trading volume, the institutional effect will make the stock price overreact.

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The general focus of this thesis is on how the family, work and the welfare system are intertwined. A major determinant is the way responsibilities are shared by the state, the market and civil society in different welfare state regimes. An introductory chapter will therefore be dedicated to the development of the social dimension in the process of European integration. A first chapter will then go deeper into the comparative analysis of welfare state regimes, to comment on the provision of welfare in societies with a different mix of state, market and societal welfare roles and to assess the adequacy of existing typologies as reflections of today’s changed socio-economic, political and gender reality. Although they stand strong on their own, these first two chapters also contribute to contextualising the research subject of the remainder of the thesis: the study and comparison of the differential situation of women and men and of mothers and non-mothers on the labour markets of the EU-15 countries as well as of the role of public policies with respect to the employment penalties faced by women, particularly in the presence of young children. In our analysis, employment penalties are understood in three ways: (i) the difference in full-time equivalent employment rates between mothers and non-mothers, (ii) the wage penalty associated with motherhood, and (iii) the wage gap between part-time and full-time workers, considering men and women separately. Besides from a gender point of view, employment outcomes and public policies are thus assessed comparatively for mothers and non-mothers. Because women choose to take part in paid employment, fertility rates will depend on their possibilities to combine employment and motherhood. As a result, motherhood-induced employment penalties and the role of public policies to tackle them should be given priority attention, not just by scholars, but also by politicians and policy-makers.

Title: Modelling dependence between hydrological and meteorological variables measured on several stations Author: Bc. Marie Turčičová Department: Department of Probability and Mathematical Statistics Supervisor: Prof. RNDr. Daniela Jarušková CSc., Czech Technical University in Prague, Faculty of Civil Engineering, Department of Mathematics Abstract: The aim of the thesis is to explore the dependence of daily discharge averages of the Opava river on high daily precipitation values in its basin. Three methods are presented that can be used for analyzing the dependence between high values of random variables. Their application on the studied data is also given. First it is the tail-dependence coefficient that measures the dependence between high values of two continuous random variables. The model for the high quantiles of the discharge at a given precipitation value was first determined non-parametrically by quantile regression and then parametrically through the peaks-over-threshold (POT) method. Keywords: extremal dependence, tail-dependence coefficient, quantile regression, peaks over threshold method

This thesis investigates forecasting performance of Quantile Regression Neural Networks in forecasting multiperiod quantiles of realized volatility and quantiles of returns. It relies on model-free measures of realized variance and its components (realized variance, median realized variance, integrated variance, jump variation and positive and negative semivariances). The data used are S&P 500 futures and WTI Crude Oil futures contracts. Resulting models of returns and volatility have good absolute performance and relative performance in comparison to the linear quantile regression models. In the case of in- sample the models estimated by Quantile Regression Neural Networks provide better estimates than linear quantile regression models and in the case of out-of-sample they are equally good.

Les écarts communément observés entre les prévisions de consommations énergétiques et les performances réelles des bâtiments limitent le développement des projets de construction et de réhabilitation. La garantie de performance énergétique (GPE) a pour vocation d’assurer des niveaux de consommations maximaux et donc de sécuriser les investissements. Sa mise en place fait cependant face à plusieurs problématiques, notamment techniques et méthodologiques. Ces travaux de thèse se sont intéressés au développement d’une méthodologie pour la GPE associant les outils de simulation énergétique dynamique (SED) à un protocole de mesure et vérification. Elle repose d’abord sur la modélisation physico-probabiliste du bâtiment. Les incertitudes sur les paramètres physiques et techniques, et les variabilités des sollicitations dynamiques sont modélisées et propagées dans la SED. Un modèle de génération de données météorologiques variables a été développé. L’étude statistique des résultats de simulation permet d’identifier des modèles liant les consommations d’intérêt à des facteurs d’ajustement, caractéristiques des conditions d’exploitation. Les méthodes de régression quantile permettent de déterminer le quantile conditionnel des distributions et caractérisent donc conjointement la dépendance aux facteurs d’ajustement et le niveau de risque de l’engagement. La robustesse statistique de ces méthodes et le choix des meilleurs facteurs d’ajustement ont été étudiés, tout comme l’influence des incertitudes sur la mesure des grandeurs d’ajustement en exploitation. Leur impact est intégré numériquement en amont de la méthodologie. Cette dernière est finalement mise en œuvre sur deux cas d’étude : la rénovation de logements, et la construction de bureaux. / Discrepancies between ex-ante energy performance assessment and actual consumption of buildings hinder the development of construction and renovation projects. Energy performance contracting (EPC) ensures a maximal level of energy consumption and secures investment. Implementation of EPC is limited by technical and methodological problems.This thesis focused on the development of an EPC methodology that allies building energy simulation (BES), and measurement and verification (M&V) process anticipation. The building parameters’ uncertainties and dynamic loads variability are considered using a Monte-Carlo analysis. A model generating synthetic weather data was developed. Statistical studies of simulation results allow a guaranteed consumption limit to be evaluated according to a given risk. Quantile regression methods jointly capture the risk level and the relationship between the guaranteed energy consumption and external adjustment factors. The statistical robustness of these methods was studied as well as the choice of the best adjustment factors to consider. The latter will be measured during building operation. The impact of measurement uncertainties is statistically integrated in the methodology. The influence of M&V process accuracy is also examined. The complete EPC methodology is finally applied on two different projects: the refurbishment of a residential building and the construction of a high energy performance office building.

Esse trabalho apresenta um estudo da causalidade de Granger em Risco bivariado aplicado a séries temporais financeiras. Os eventos de risco, no caso de séries financeiras, estão relacionados com a avaliação do Valor em Risco das posições em ativos. Para isso, os modelos CaViaR, que fazem parte do grupo de modelos de Regressão Quantílica, foram utilizado para identificação desses eventos. Foram expostos os conceitos principais envolvidos da modelagem, assim como as definições necessárias para entendê-las. Através da análise da causalide de Granger em risco entre duas séries, podemos investigar se uma delas é capaz de prever a ocorrência de um valor extremo da outra. Foi realizada a análise de causalidade de Granger usual somente para como comparativo. / Quantile Regression, Value at Risk, CAViaR Model, Granger Causality, Granger Causality in Risk

[pt] O presente artigo tem como objetivo estudar a relação entre os retornos de índice de mercado de ações e taxas de câmbio de seis países da América Latina. De acordo com a abordagem do portfólio, ambas as variáveis devem ser negativamente correlacionadas. Tendo em vista que a regressão linear capta a relação linear média, não apresentando resultados satisfatórios, uma regressão quantílica foi usada para verificar essa relação em diferentes condições de mercado. Os resultados evidenciam um padrão no mercado latino americano, na qual a relação negativa entre as variáveis estudadas é mais pronunciada em momentos de forte desvalorização cambial. / [en] The present paper aims to study the relationship between stock price index returns and exchange rate of six Latin America countries. Acoording to the portfolio balance effect, both variables are supposed to be negatively correlated. Since the linear regression results are not satisfactory, a quantile regression is made to verify these relationship under different market conditions. The results show a pattern in these Latin American markets, where the negative relation between the studied variables is more pronunced when the exchange rate is very high.