Considerando a importância dos fatores financeiros nas decisões de investimento e as restrições financeiras das firmas, os intermediários financeiros mostram-se como importantes provedores de fonte de recursos para a viabilização dos investimentos. Devido a esta ligação, um possível canal de transmissão no qual o setor financeiro afeta o crescimento e risco das empresas ocorre pela dependência de recursos financeiros externos, portanto, o risco e retorno das firmas devem ser afetados pelas dificuldades das entidades financeiras. Atentando a esta circunstância o objetivo deste estudo é de verificar na economia brasileira os efeitos do alastramento de risco do setor financeiro para a economia real nas decisões de investimentos das firmas, as quais perpassam por conjunturas de restrição financeira. Para atingir tal objetivo utiliza-se informações financeiras e retorno das ações das empresas de capital aberto no Brasil no período de 1997 a 2015. O alastramento do risco do retorno é estimado por um processo VAR-GARCH, e o contágio financeiro pelo indicador de co-excessos condicionais. Essas variáveis são inseridas em um modelo neoclássico acelerador de investimento modificado, para um grupo de firmas restritas e outro de não restritas, classificadas pelos índices KZ e WW. A estimação do modelo de investimento é realizada pelo GMM system e os resultados mostram que o nível do alastramento do risco do setor financeiro para as firmas impacta negativamente nas taxas de investimento das empresas restritas tanto pelo índice KZ, quanto pelo WW. O estudo amplia a literatura nacional utilizando um enfoque microeconômico do alastramento do risco e dos co-excessos condicionais e abordando a questão do alastramento do risco no modelo de investimento. / Considering the importance of financial factors and financial constraints in firm\'s investment decisions, financial sector show up as important source of funds providers to the viability of industry investments. Because of this connection, a possible transmission channel in which the financial intermediaries affect firm\'s growth and risk is from the dependence on external financial funds, so the risk and return of firms should be affected by the difficulties and vagaries of financial sector. In accordance to this circumstance this study aim\'s to verify the effects of the financial sector risk spillover and contagion to the real economy in constrained, and unconstrained, firms\' investment decisions. To achieve this goal, we use financial data and stock returns of publicly traded companies in Brazil from 1997 to 2015. The risk spillover is estimated by a VAR-GARCH process, and financial contagion by an index called conditional co-exceedance. These variables are included in a modified neoclassical accelerator model of investment, splitting the observations into groups of constrained and unconstrained firms, classified by KZ and WW indexes. The estimation of the investment model is performed by GMM system, and the results show that the level of financial sector risk spillover negatively impact investment rates of constrained companies, both by the KZ and WW segregations. This study contributes to the national literature using a microeconomic approach to the risk spillover and conditional co-exceedances addressing it to the investment model.

Considerando a importância dos fatores financeiros nas decisões de investimento e as restrições financeiras das firmas, os intermediários financeiros mostram-se como importantes provedores de fonte de recursos para a viabilização dos investimentos. Devido a esta ligação, um possível canal de transmissão no qual o setor financeiro afeta o crescimento e risco das empresas ocorre pela dependência de recursos financeiros externos, portanto, o risco e retorno das firmas devem ser afetados pelas dificuldades das entidades financeiras. Atentando a esta circunstância o objetivo deste estudo é de verificar na economia brasileira os efeitos do alastramento de risco do setor financeiro para a economia real nas decisões de investimentos das firmas, as quais perpassam por conjunturas de restrição financeira. Para atingir tal objetivo utiliza-se informações financeiras e retorno das ações das empresas de capital aberto no Brasil no período de 1997 a 2015. O alastramento do risco do retorno é estimado por um processo VAR-GARCH, e o contágio financeiro pelo indicador de co-excessos condicionais. Essas variáveis são inseridas em um modelo neoclássico acelerador de investimento modificado, para um grupo de firmas restritas e outro de não restritas, classificadas pelos índices KZ e WW. A estimação do modelo de investimento é realizada pelo GMM system e os resultados mostram que o nível do alastramento do risco do setor financeiro para as firmas impacta negativamente nas taxas de investimento das empresas restritas tanto pelo índice KZ, quanto pelo WW. O estudo amplia a literatura nacional utilizando um enfoque microeconômico do alastramento do risco e dos co-excessos condicionais e abordando a questão do alastramento do risco no modelo de investimento. / Considering the importance of financial factors and financial constraints in firm\'s investment decisions, financial sector show up as important source of funds providers to the viability of industry investments. Because of this connection, a possible transmission channel in which the financial intermediaries affect firm\'s growth and risk is from the dependence on external financial funds, so the risk and return of firms should be affected by the difficulties and vagaries of financial sector. In accordance to this circumstance this study aim\'s to verify the effects of the financial sector risk spillover and contagion to the real economy in constrained, and unconstrained, firms\' investment decisions. To achieve this goal, we use financial data and stock returns of publicly traded companies in Brazil from 1997 to 2015. The risk spillover is estimated by a VAR-GARCH process, and financial contagion by an index called conditional co-exceedance. These variables are included in a modified neoclassical accelerator model of investment, splitting the observations into groups of constrained and unconstrained firms, classified by KZ and WW indexes. The estimation of the investment model is performed by GMM system, and the results show that the level of financial sector risk spillover negatively impact investment rates of constrained companies, both by the KZ and WW segregations. This study contributes to the national literature using a microeconomic approach to the risk spillover and conditional co-exceedances addressing it to the investment model.

In the new context of major public emergencies, this paper will mainly study the measurement and influencing factors of systemic risks in Chinese financial institutions based on three dimensions: overall situation, industries, and institutions. First, it uses the DTW-MST network model to describe the dependence structure between financial institutions and between industries. It explores important institutional nodes of risk dependence from a network perspective. Then, it uses the time-varying Copula-CoVaR model to measure financial institutions' and industries' risk spillover effect on the whole financial system and analyze the characteristics and differences of risk spillover. Last, it uses the panel regression model to study the influencing factors of the risk spillover effect of financial institutions and explore the sources of systemic risks. The results show that: (1) Industrial Bank (CIB), Changjiang Securities (CJSC), and China Pacific Insurance (CPIC) are the central nodes of the banking, securities, and insurance industries, respectively. (2) The risk spillover effect is characterized by a significant asymmetry and thick tail, and negative news has a greater impact on the risk spillover effect. (3) The value at risk (VaR) and volatility of financial institutions have a significant positive correlation with the risk spillover effect, while the size of financial institutions has a significant negative correlation with the risk spillover effect. / Business Administration/Finance

This thesis aims to analyze some of the available methods that aid in risk estimation based on econometric models, as well as to propose some new ones. Some of the questions that are expected to be answered include which distribution to choose to obtain better risk estimates for series with abnormal behaviours, how to determine whether the distribution in parametric conditional models is a Student’s t, and how to assess whether an asset’s risk helps predict the risk of another asset. In Chapter 1, we estimate several cryptocurrencies’ Expected Shortfall using different error distributions and GARCH-type models for conditional variance. ur goal is to examine which distributions perform better and to check which component of the specification plays a more crucial role in estimating Expected Shortfall. The performance of the estimations is conducted using a backtesting technique with a rolling-window approach. Results show that, in the case of Bitcoin, it is important to use a distribution with at least two parameters that control its shape and an extension of the GARCH model, whether it be the NGARCH or the CGARCH model. On the other hand, other smaller cryptocurrencies yield good enough risk predictions with the Student’s t distribution and a GARCH model. The fact that the main measures of financial risk are focused on the tail of the distribution of returns highlights the importance of the choice of an appropriate distribution model. Chapter 2 develops a procedure for consistently testing the specification of a Student’s t distribution for the innovations of a dynamic model. This contributes to the existing literature by providing a test for Student’s t distributions in conditional mean and variance models with a parameter-free test statistic and, thus, a known asymptotic distribution, avoiding the use of more computationally costly resampling techniques such as bootstrapping. The specific expressions needed for the computation of the test statistic are obtained by adapting the generic test of Bai (2003), which is based on the Khmaladze (1988) transformation of the model residuals. Finally, in Chapter 3, the concept of Granger causality in Expected Shortfall (ES) is introduced, along with a testing procedure to detect this type of predictive relationship between return series. Granger causality in Expected Shortfall is here defined as the predictive ability of tail values of a series over future tail values of another series on average. This definition may help in analyzing whether past values of an asset in extreme risk affect future extreme risk values of another asset. The main contribution of this chapter is a test for detecting this type of causality, based on the test for Granger causality in VaR by Hong et al. (2009). An empirical application on financial institutions from different industries (banking, insurance, and diversified financials) is presented to analyze the risk spillovers in the US financial market. The contribution of this thesis to the field of financial econometrics focuses on the market risk of financial assets, both in its modeling through the metric known as Expected Shortfall suggested in the Basel III Accords and in its utility beyond capital requirements. The results highlight the importance of a good specification of the chosen distribution model for risk estimation - especially in high-risk assets such as cryptocurrencies - and a test is proposed to verify if the conditional distribution in parametric models used for risk predictions is or is not a Student’s t distribution. Finally, a Granger causality test in Expected Shortfall is proposed, which allows for studying risk propagation in tails of return distributions. The proposed test can be used to investigate interconnections within and between markets as a complement when evaluating systemic risk. Other potential applications include improving Expected Shortfall forecasts by including causing variables as regressors in estimations, studying the inclusion of certain asset pairs in the same portfolio based on how they interact in the riskiest situations, or constructing networks of extreme risk propagation. / Esta tesis doctoral ha sido financiada mediante una ayuda FPU por el Ministerio de Educación, Cultura y Deporte (FPU17/06227).

Le phénomène de contagion, les hypothèses d'efficience et les transferts de volatilité sont parmi les théories économiques les plus importantes, car elles fournissent une vision globale sur la stabilité financière. Or, elles restent les moins comprises depuis les récentes crises récentes. Ainsi, cette thèse propose de fournir aux régulateurs économiques, aux investisseurs et aux acteurs du marché financier une vision actualisée du comportement dynamique des marchés mondiaux des Credit Default Swaps (CDS): efficacité informationnelle, interaction avec d'autres marchés financiers internationaux et exposition au risque systémique. La dynamique en constante mutation de ces marchés associée à l'évolution constante des politiques de réglementation a suscité un enthousiasme mondial pour l'étude comportementale des marchés des CDS, auquel nous contribuons à travers cinq essais interconnectés. Nous discutons, dans le premier essai, les faits stylisés des données des CDS souverains à travers l'estimation de 9 modèles de type GARCH. Ce chapitre compare les performances de plusieurs modèles prédictifs de volatilité linéaire et non linéaire et prenant en compte différentes caractéristiques financières des séries statistiques. L'application de ces modèles aux spreads de CDS de 38 pays révèle que le pouvoir prédictif de ces modèles dépend de leur capacité à capturer les faits stylisés des CDS souverains pendant l'estimation du processus de la variance. En effet, les modèles GARCH fractionnellement intégrés surpassent les modèles GARCH de base en termes de prévision, en raison de la flexibilité accordée au degré de persistance des chocs de variance. Ces résultats sont utilisés pour modéliser conjointement les rendements et la volatilité des spreads de CDS dans l'ensemble des prochains essais. Le deuxième essai examine également les caractéristiques financières des marchés internationaux des CDS souverains, en donnant de nouvelles preuves sur leurs degrés d'efficacité. En utilisant un nouveau cadre économétrique basé sur une estimation du modèle VECM-FIGARCH en trois étapes, nous montrons que les informations contenues dans les spreads de CDS et les rendements des obligations sous-jacentes ne sont pas toujours reflétées instantanément et correctement dans le niveau du risque souverain. Les résultats révèlent l'existence d'opportunités d'arbitrage avec un rejet partiel de l'hypothèse de marche au hasard dans plusieurs des 37 pays étudiés [etc...] / Contagion phenomenon, efficiency hypothesis and spillover effects are amongst the most important economic theories as they provide an overall vision of the financial stability, yet the least understood in the aftermath of the recent crises. This thesis proposes to provide policy makers, investors and broadly market participants with an updated outlook of the dynamic behavior of the global sovereign Credit Default Swaps (CDS) markets: informational efficiency, interaction with other international financial markets and systemic-risk exposure. The steadily changing dynamics of these markets combined with the constantly evolving regulatory policies have led to a shared worldwide enthusiasm regarding the behavioral study of CDS markets, in which we contribute through five interconnected essays. We first discuss, in the first essay, the statistical characteristics of the sovereign CDS data, through the estimation of 9 GARCH-class models. This chapter compares the predictability performances of several linear and non-linear volatility models taking into consideration different financial stylized facts. Application on CDS spreads of 38 countries reveals that the forecasting power of these models depends on their ability to capture sovereign CDS features while estimating the variance process. Yet, the fractionally-integrated models outperform the basic GARCH-class models due to the allowed flexibility regarding the persistence degree of the variance shocks. These results are used to jointly model returns and volatility of CDS spreads in the forthcoming essays.The second essay also investigates the financial characteristics of the international sovereign CDS markets, by giving new evidences on their efficiency degrees. Using a new framework based on a 3-step estimation of a VECM-FIGARCH model, we show that information contained in CDS spreads and bond yields are not always instantaneously and properly reflected in the current sovereign risk level. Results reveal the existence of arbitrage opportunities with a partial rejection of the randomness hypothesis in some of the 37 studied countries. While the previous essay used the conditional expectation of CDS spreads to study the market behavior, the next essays rather focus on the properties of the variance and covariance. The predictability of sovereign CDS volatility, based on the information contained in some country-specific and global macroeconomic factors, is investigated in the third chapter [etc...]