We study systemic risk in a network model of the interbank market where the asset returns of the banks in the network are correlated. In this way we can study the interaction of two important channels for systemic risk (correlation of asset returns and contagion due direct financial linkages). We carry out a simulation study that determins the probability of a systemic crisis in the banking network as a function of both the asset correlation, and the connectivity and structure of the financial network. An important observation is the fact that the relation between asset correlation and the probalility of a systemic crisis is hump-sharped; in particular, lowering the correlation between the assets returns of different banks does not always imply a lower probability of a systemic crisis.

The recent financial crisis has brought to the fore the need to better understand systemic risk, that is, the risk of collapse of a large part of the financial system and its potential effects on the real economy. In this thesis, we argue that a proper assessment of systemic risk must include an analysis of the network of interdependencies that exists between the different financial institutions. In fact, today's level of financial interconnectedness between and among markets has proven to have ambiguous effects. On the one hand, a highly connected system allows to diversify risk at the micro level. On the other hand, too much interdependencies provide various paths for contagion to take place and propagate at the macro level. In what follows, we analyze financial markets as networks of interactions and dependencies between financial agents. Through this lens, we investigate three major aspects: (i) how the structure of financial networks can amplify or mitigate the propagation of financial distress, (ii) what are the implications for macro-prudential regulation and (iii) which patterns of interactions characterize real financial networks.We start out by delivering a stability analysis of a network model of interbank contagion that accounts for panics and bank runs. We identify the effects of market architecture, banks' capital ratios, market liquidity and shocks. Our results show that no single network architecture is always superior to others. In particular, highly concentrated networks can both be the most robust and the most fragile depending on other market characteristics, mainly, liquidity.We then move on to tackle issues related to the building of regulatory frameworks that adequately account for the effects of financial interdependencies. We propose a new methodology to compute individual and systemic probabilities of default and show that certain network characteristics give rise to uncertainty. More precisely, we find that network cycles are responsible for the emergence of multiple equilibria even in the presence of complete knowledge. In turn, multiple equilibria give rise to uncertainty for the regulator in the determination of default probabilities. We also quantify the effects of network structures, leverage, volatility and correlations.Having introduced a way to overcome multiplicity, we deliver a method that quantifies the price of complexity in financial markets based on the above mentioned model. This method consists of determining the scope of possible levels of systemic risk that can be obtained when some parameters are subject to small deviations from their true value. The results show a price to the interconnected nature of credit markets even when the equilibrium is unique: small errors can lead to large mistakes in measuring the likelihood of systemic default. Extending the model to account for derivative contracts, we show that error effects increase dramatically as more types of contracts are present in the system. While there is an intuition for such phenomenon, our framework formalizes the idea and quantifies its determinants.In the last part of this thesis, we contribute to the quantitative analysis of real financial networks. We start with a temporal network analysis of one of the major national interbank markets, that is, the German interbank market. We report on the structural evolution of two of the most important over-the-counter markets for liquidity: the interbank market for credit and for derivatives. We find that the majority of interactions is concentrated onto a set of few market participants. There also exists an important correlation between the borrowing and lending activities for each bank in terms of numbers of counterparties. In contrast with other works, we find little impact of the 2008 crisis on the structure of the credit market. The derivative market however exhibits a peak of concentration in the run up to the crisis. Globally, both markets exhibit large levels of stability for most of the network metrics and high correlation amongst them.Finally, we analyze how banks interact with the real economy by investigating the network of loans from banks to industries in Japan. We find evidence of a particular structure of interactions resulting from the coexistence of specific strategies both on the lending side and the borrowing side: generalist agents and specialist agents. Generalist banks have a diversified portfolio (i.e. they provide liquidity to almost all industries) while specialist banks focus their activity on a narrow set of industries. Similarly, generalists industries obtain credit from all banks while specialist industries have a restricted number of creditors. Moreover, the arrangement of interactions is such that specialists tend to only interact with generalists from the other side. Our model allows to structurally characterize highly persistent, and economically meaningful, sets of generalists and specialists. We further provide an analysis of the factors that predict whether a given bank or industry is a generalist. We show that size is an important determinant, both for banks and industries, but we also highlight additional relevant factors. Finally, we find that generalist banks tend to be less vulnerable. Hence, how banks position themselves in the network has important implications for their risk profile. Overall the results presented in this thesis highlight the complex role played by financial interlinkages. Therefore, they demonstrate the need to embed the network dimension in the regulatory framework to properly assess the stability profile of financial systems. Such findings are relevant for both theoretical modeling and empirical investigations. We believe that they also shed light on crucial aspects of systemic risk relevant for policy making and regulation of today's complex financial systems. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

The present work aims at discussing the main theoretical aspects related to the occurrence of long memory processes and its respective application in economics and finance. In order to discuss the main theoretical aspects of its occurrence, it is worth starting from the complex systems approach and emergent phenomena, keeping in mind that many of these are computationally irreducible. In other words, the current state of the system depends on all previous states, in such a way that any change in the initial configuration must cause a significant difference in all posterior states. That is, there is a persistence of information over time - this is a concept directly related to long memory processes. Hence, based on complex systems simulations, three factors (possibly there are many others) were related to the rise of long memory processes: agents\' heterogeneity, occurrence of large deviations from the steady states (in conjunction with the motion laws of each system) and spatial complexity (which must influence on information propagation and on the dynamics of agents competition). In relation to the applied knowledge, first it is recognized that the explanatory factors for the rise of long memory processes are common to the structures/characteristics of real markets and it is possible to identify potential stylized facts when filtering the long memory components from time series - a considerable part of information present in time series is a consequence of the autocorrelation structure, which is directly related to the specificities of each market. Given that, in this thesis was developed a new risk contagion technique that does not need any further intervention. This technique is basically given by the calculation of rolling correlations between long memory filtered series of the conditional variances for different economies, such that these filtered series contain the stylized facts (risk peaks), free from possible overreactions caused by market idiosyncrasies. Then, based on the identification of risk contagion episodes related to the 2007/2008 Subprime Crisis in the U.S. and its respective contagion to the Brazilian economy, it was filtered out from the conditional variance of the Brazilian assets (which are an uncertainty measure) aiming at eliminating the contagion episodes and, consequently, it was made a counterfactual projection of what would have happened to the Brazilian economy if the risk contagion episodes had not occurred. Moreover, in conjunction with the evolutionary trend of the Brazilian economy prior to the crisis, it is possible to conclude that 70% of the economic crisis posterior to the 2008 events was caused by macroeconomic policies and only 30% is due to the effects of risk contagion episodes from the U.S. / O presente trabalho tem como objetivo discutir os principais aspectos teóricos ligados à ocorrência dos processos de memória longa e sua respectiva aplicação em economia e finanças. Para discutir os principais aspectos teóricos da sua ocorrência, recorre-se primeiramente à abordagem de sistemas complexos e fenômenos emergentes, tendo em vista que muitos destes são irredutíveis computacionalmente, ou seja, o estado atual do sistema depende de todos os estados anteriores, tal que, qualquer mudança nos instantes iniciais deve causar significativa diferença nos estados posteriores. Em outras palavras, há uma persistência da informação - conceito este intimamente ligado à memória longa. Portanto, com base em simulações de sistemas complexos computacionais, três fatores (podendo haver outros mais) foram relacionados ao surgimento de processos de memória longa: heterogeneidade dos agentes, ocorrência de grandes desvios do equilíbrio do sistema (em consonância com as respectivas leis do movimento de cada sistema estudado) e a complexidade espacial (que deve influenciar na propagação da informação e na dinâmica competitiva dos agentes). Em relação à aplicação do conhecimento, primeiro é reconhecido que os fatores explicativos para o surgimento de processos de memória longa são inerentes a estruturas/características de mercados reais e que é possível identificar potenciais fatos estilizados, ao filtrar as componentes de memória longa de séries temporais - grande parte da informação presente nas séries é função da estrutura de autocorrelação que advém das especificidades de cada mercado. Com base nisso, nesta tese foi desenvolvida uma nova técnica de estimação de contágio de risco, que não necessita intervenções adicionais, tendo em vista a identificação prévia de potenciais fatos estilizados em diferentes economias, utilizando as séries filtradas de variância condicional, tal que a partir destas séries filtradas é calculada uma correlação com horizonte móvel de observações entre choques (picos de risco) de curto prazo livres de possíveis reações causadas por idiossincrasias de cada mercado. Posteriormente, com base na identificação dos episódios ligados à Crise do Subprime de 2007/2008 nos Estados Unidos e seu respectivo contágio para a economia brasileira, filtrou-se a variância condicional dos ativos brasileiros (que é uma medida de incerteza), objetivando-se eliminar os eventos de contágio e, consequentemente, foi feita uma projeção contrafactual da evolução da economia, caso os episódios da crise não tivessem ocorrido. Com base nestes dados e com uma análise da tendência evolutiva da economia brasileira no período anterior à crise, constatou-se que 70% da crise econômica vivenciada no Brasil no período pós-2008 é decorrente de falhas na condução da política macroeconômica e somente 30% decorre dos efeitos do cenário externo na economia.

The present work aims at discussing the main theoretical aspects related to the occurrence of long memory processes and its respective application in economics and finance. In order to discuss the main theoretical aspects of its occurrence, it is worth starting from the complex systems approach and emergent phenomena, keeping in mind that many of these are computationally irreducible. In other words, the current state of the system depends on all previous states, in such a way that any change in the initial configuration must cause a significant difference in all posterior states. That is, there is a persistence of information over time - this is a concept directly related to long memory processes. Hence, based on complex systems simulations, three factors (possibly there are many others) were related to the rise of long memory processes: agents\' heterogeneity, occurrence of large deviations from the steady states (in conjunction with the motion laws of each system) and spatial complexity (which must influence on information propagation and on the dynamics of agents competition). In relation to the applied knowledge, first it is recognized that the explanatory factors for the rise of long memory processes are common to the structures/characteristics of real markets and it is possible to identify potential stylized facts when filtering the long memory components from time series - a considerable part of information present in time series is a consequence of the autocorrelation structure, which is directly related to the specificities of each market. Given that, in this thesis was developed a new risk contagion technique that does not need any further intervention. This technique is basically given by the calculation of rolling correlations between long memory filtered series of the conditional variances for different economies, such that these filtered series contain the stylized facts (risk peaks), free from possible overreactions caused by market idiosyncrasies. Then, based on the identification of risk contagion episodes related to the 2007/2008 Subprime Crisis in the U.S. and its respective contagion to the Brazilian economy, it was filtered out from the conditional variance of the Brazilian assets (which are an uncertainty measure) aiming at eliminating the contagion episodes and, consequently, it was made a counterfactual projection of what would have happened to the Brazilian economy if the risk contagion episodes had not occurred. Moreover, in conjunction with the evolutionary trend of the Brazilian economy prior to the crisis, it is possible to conclude that 70% of the economic crisis posterior to the 2008 events was caused by macroeconomic policies and only 30% is due to the effects of risk contagion episodes from the U.S. / O presente trabalho tem como objetivo discutir os principais aspectos teóricos ligados à ocorrência dos processos de memória longa e sua respectiva aplicação em economia e finanças. Para discutir os principais aspectos teóricos da sua ocorrência, recorre-se primeiramente à abordagem de sistemas complexos e fenômenos emergentes, tendo em vista que muitos destes são irredutíveis computacionalmente, ou seja, o estado atual do sistema depende de todos os estados anteriores, tal que, qualquer mudança nos instantes iniciais deve causar significativa diferença nos estados posteriores. Em outras palavras, há uma persistência da informação - conceito este intimamente ligado à memória longa. Portanto, com base em simulações de sistemas complexos computacionais, três fatores (podendo haver outros mais) foram relacionados ao surgimento de processos de memória longa: heterogeneidade dos agentes, ocorrência de grandes desvios do equilíbrio do sistema (em consonância com as respectivas leis do movimento de cada sistema estudado) e a complexidade espacial (que deve influenciar na propagação da informação e na dinâmica competitiva dos agentes). Em relação à aplicação do conhecimento, primeiro é reconhecido que os fatores explicativos para o surgimento de processos de memória longa são inerentes a estruturas/características de mercados reais e que é possível identificar potenciais fatos estilizados, ao filtrar as componentes de memória longa de séries temporais - grande parte da informação presente nas séries é função da estrutura de autocorrelação que advém das especificidades de cada mercado. Com base nisso, nesta tese foi desenvolvida uma nova técnica de estimação de contágio de risco, que não necessita intervenções adicionais, tendo em vista a identificação prévia de potenciais fatos estilizados em diferentes economias, utilizando as séries filtradas de variância condicional, tal que a partir destas séries filtradas é calculada uma correlação com horizonte móvel de observações entre choques (picos de risco) de curto prazo livres de possíveis reações causadas por idiossincrasias de cada mercado. Posteriormente, com base na identificação dos episódios ligados à Crise do Subprime de 2007/2008 nos Estados Unidos e seu respectivo contágio para a economia brasileira, filtrou-se a variância condicional dos ativos brasileiros (que é uma medida de incerteza), objetivando-se eliminar os eventos de contágio e, consequentemente, foi feita uma projeção contrafactual da evolução da economia, caso os episódios da crise não tivessem ocorrido. Com base nestes dados e com uma análise da tendência evolutiva da economia brasileira no período anterior à crise, constatou-se que 70% da crise econômica vivenciada no Brasil no período pós-2008 é decorrente de falhas na condução da política macroeconômica e somente 30% decorre dos efeitos do cenário externo na economia.