Thesis focuses on actual trends in regulation of financial markets and institutions, reflecting the financial crisis of 2007 -- 2009. Taking into consideration the range of these issues the thesis specifically deals with the insurance industry and impact of increasing regulation on the insurance companies. Further, thesis concentrates on intensification of financial markets regulation, consolidation of regulatory competence and its transfer on supranational authorities, including on the issue of changes in the approach to the systemic risks regulation. These matters are being analyzed mainly from the perspective of their impact on the insurance industry. Thesis tries to evaluate the adequacy of these trends in respect to insurance market. Also the thesis deals with optimization of the current system of insurance regulation in the Czech Republic by implementation of self-regulation components into it. Finally it deals with evaluation of the regulatory system in total from the clients' perspective.

Dans sa première partie, cette thèse étudie l’utilisation optimale des produits dérivés par les intermédiaires financiers dans leur gestion du risque, en prêtant spécifiquement attention au marché des dérivés de taux d’intérêt. En modélisant la structure de capital optimale d’une banque, le premier chapitre montre comment l’usage optimal des dérivés affecte certaines décisions souvent étudiées en finance d’entreprise : l’offre de crédit, la transformation de maturité, la politique de dividendes ou les probabilités de défaut. La seconde partie de la thèse étudie au contraire le marché des dérivés comme un système à part entière. Le second chapitre utilise une base de données nouvelle et unique d’expositions bilatérales sur des contrats CDS afin d’offrir une description détaillée de la structure du réseau des expositions. Le troisième chapitre a pour objet la régulation des marchés de produits dérivés. Il étudie la compensation centrale des produits dérivés standardisés, et la demande de collatéral induite par cette réforme à l’échelle mondiale, sous une variété d’hypothèses concernant la microstructure du marché. / In its first part, this thesis studies the optimal use of derivatives contracts for risk management by financial intermediaries, focusing especially on interest rate derivative contracts. It models the optimal capital structure policy of a bank and shows how the optimal use of derivatives affects a number of oft-studied decisions in corporate finance: bank lending, maturity mismatching, payout policy or default probabilities. The second part of the thesis, in contrast, studies derivatives market as a system on its own. The second chapter uses a new and unique dataset of bilateral exposures to CDS contracts in order to provide a detailed description of the network structure of exposures. The third chapter focuses on the regulation of derivatives markets. It studies central clearing of standardized derivatives contracts and the collateral demand induced by the reform at a global scale, under a variety of hypotheses regarding the market microstructure.

Cette thèse vise à analyser le risque systémique sur les marchés futures de matières premières. En effet, plusieurs travaux de recherche mettent en évidence l'importance de ces futures dans la détermination du prix physique des matières premières. Leur incorporation dans la finance traditionnelle en tant qu'actif diversifiant a entraîné une évolution de leurs prix similaire à celles de différents actifs financiers depuis environ 2004. La question ayant motivé cette thèse a donc été de quantifier ce risque systémique (puisqu'affectant les matières premières, directement impliquées dans l'économie réelle), d'en voir précisément les moyens de transmission (quels marchés affectent quels autres marchés) et enfin de permettre d'en évaluer les conséquences, par exemple à partir de scénarii (stress tests). Elle permet donc de développer des outils de surveillance des marchés et pourrait donc contribuer à la régulation de ces marchés. / This thesis aims at studying systemic risk in commodity futures markets. A whole strand of the literature is dedicated to the "financialization of commodity markets", but also to the influence of the existence of futures markets on the spot price of their underlying asset. Indeed, since these commodity futures have been largely used by in asset management as diversifying assets, their financialization has raised concerns, especially seeing the evolution of their price, which seems to be similar to that of financial assets. My interest here is thus to quantify this systemic risk, provide a toolbox to assess the consequences of various scenarios (stress tests), but also to assess which markets should be monitored more closely (because they could threaten the real economy or the whole system).

In chapter one, by exploiting the staggered interstate banking deregulation as exogenous shocks to bank geographic expansion, we examine the causal effect of geographic diversification on systemic risk using the gravity-deregulation approach developed in Goetz, Laeven, and Levine (2013, 2016). We find that bank geographic diversification leads to higher systemic risk measured by the change in conditional value at risk (ΔCoVaR) and financial integration (Logistic(R2)). Furthermore, we document asset similarity and bank inter-connectedness as two channels to explain the documented results. The impact of geographic diversification on systemic risk is more pronounced in BHCs located in states comoving less with the U.S. aggregate economy. In chapter two, by integrating the staggered interstate bank deregulation into a gravity model, we construct a time-varying bank-specific instrument for geographic diversification, and investigate how geographic expansion affects borrowing firms’ innovation. Our approach disentangles the effects of bank deregulation on geographic expansion from competition and isolates its direct impact on innovation via the lending channel. Bank geographic diversification boosts borrowing firms’ innovation input and output, enables firms to expand innovation scope beyond core business, and enhances the economic value of innovation. We find that relaxing debt covenants and alleviating borrowers’ financial constraints are two channels through which bank geographic diversification spurs innovation. In chapter three, we construct a novel bank-specific and time-varying measure of deregulation-induced bank competition following Jiang, Levine, and Lin (2016) and Goetz (2017), and investigate the causal effect of bank competition on borrowing firm’s accounting conservatism. We find that bank competition leads to an increase in firm accounting conservatism. Moreover, we find that bank competition intensifies lenders’ monitoring in that banks impose more strict and intensive covenants on bank loans, and bank monitoring reduces the probability of default of borrowing firms, and thereby result in more conservative reporting of borrowing firms. Our findings are robust to alternative accounting conservatism measure C-Score and potential multicollinearity issue.

This dissertation contributes to the discussion on the existence and extent of systemic risk in the insurance sector and its regulation. It consists of four self-contained empirical studies. Chapter one contains the introduction and motivation. The second chapter addresses the question of what characteristics an insurer exhibits such that it contributes to potential financial sector instability. The study analyzes stock losses of U.S. insurers and the U.S. financial market during the financial crisis of 2008, and examines idiosyncratic characteristics proposed by regulators to identify systemically important insurers. It employs three well-known measures of systemic risk in cross-sectional and probit regressions. Chapter three examines the relation between asset price bubbles and systemic risk among a global sample of insurance companies over a period of almost thirty years. The fourth chapter focuses on how stock market investors evaluate the presence of systemic risk in the U.S. insurance sector, and whether they price in indicators of systemic risk in insurer stocks. This study employs five different asset pricing models over time periods before, during, and after the financial crisis of 2008. The fifth chapter analyzes the relation between insurers' capital and their profitability around the world over a nine-year period. Causality between the measures of capital and profitability is established using an instrumental variable approach.

In this thesis, we study how sovereign credit default swaps are able to measure systemic risk as well as how they can be used to construct optimal portfolios to minimize risk. We define the clustering coefficient as a proxy for systemic risk and design an optimization problem with the goal of minimizing the mean absolute deviation of the clustering coefficient on a group of nine European countries. Additionally, we define a metric we call the diversity score that measures the diversification of any given portfolio. We solve this problem for a baseline set of parameters, then spend the remainder of the thesis modifying these parameters to investigate how the optimal solution and diversity score are impacted.

The effective implementation of infrastructure asset management systems within organizations that own, operate, and manage infrastructure assets is critical to address the main challenges facing the infrastructure industry (e.g., infrastructure ageing and deterioration, maintenance backlogs, strict regulatory operating conditions, limited financial resources, and losing valuable experience through retirements). Infrastructure asset management systems contain connectivity between major operational components and such connectivity can lead to systemic risks (i.e., dependence-induced failures). This thesis analyzes the asset management system as a network of connected components (i.e., nodes and links) to identify critical components exposed to systemic risks induced by information asymmetry and information overload. This thesis applies descriptive and prescriptive analytics strategies to address information asymmetry and information overload and predictive analytics is employed to enhance the resilience. Specifically, descriptive analytics was employed to visualize the key performance indicators of infrastructure assets ensuring that all asset management stakeholders make decisions using consistent information sources and that they are not overwhelmed by having access to the entire database. Predictive analytics is employed to classify the resilience key performance indicator pertaining to the forced outage rapidity of power infrastructure components enabling power infrastructure owners to estimate the rapidity of an outage soon after its occurrence, and thus allocating the appropriate resources to return the infrastructure to operation. Using predictive analytics allows decision-makers to use consistent and clear information to inform their decision to respond to forced outage occurrences. Finally, prescriptive analytics is applied to optimize the asset management system network by increasing the connectivity of the network and in turn decreasing the exposure of the asset management system to systemic risk from information asymmetry and information overload. By analyzing an asset management system as a network and applying descriptive-, predictive-, and prescriptive analytics strategies, this dissertation illustrates how systemic risk exposure, due to information asymmetry and information overload could be mitigated and how power infrastructure resilience could be enhanced in response to forced outage occurrences. / Thesis / Doctor of Science (PhD) / Effective infrastructure asset management systems are critical for organizations that own, manage, and operate infrastructure assets. Infrastructure asset management systems contain main components (e.g., engineering, project management, resourcing strategy) that are dependent on information and data. Inherent within this system is the potential for failures to cascade throughout the entire system instigated by such dependence. Within asset management, such cascading failures, known as systemic risks, are typically caused by stakeholders not using the same information for decision making or being overwhelmed by too much information. This thesis employs analytics strategies including: i) descriptive analytics to present only relevant and meaningful information necessary for respective stakeholders, ii) predictive analytics to forecast the resilience key performance indicator, rapidity, enabling all stakeholders to make future decisions using consistent projections, and iii) prescriptive analytics to optimize the asset management system by introducing additional information connections between main components. Such analytics strategies are shown to mitigate the systemic risks within the asset management system and enhance the resilience of infrastructure in response to an unplanned disruption.

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This dissertation discovers an important development in the life reinsurance market and investigates two problems behind the rapid growth of shadow insurance -- the motivation of shadow insurance activities and the underlying risks. The first part investigates why U.S. life insurance groups use shadow insurance, i.e., reinsure their risks using affiliated, unauthorized, and unrated off-balance-sheet entities rather than traditional reinsurers, and how such activities are allocated to individual group members. We find that regulatory arbitrage through shadow insurance activities is motivated by a large deviation from an insurance group's optimal capital structure and is primarily exercised by larger groups with relatively lower capital adequacy. Rather than smoothing capitalization across firms using affiliated reinsurers' capacity, insurance groups allocate the amount of shadow insurance to only a few highly leveraged, less capitalized, and larger life insurers within the group. The se / Business Administration/Risk Management and Insurance