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.

Since the onset of the global financial crisis, there have been calls to regulate those parts of the financial system that were previously either unregulated or lightly regulated. These proposals are being put forward as part of an international drive to bring parts of the financial sector within the ambit of regulation, with the overarching aim of protecting investors from bearing the brunt of regulatory failures, as was experienced in the 2007/2008 global financial crisis. The purpose of this study was to explore the impact of proposed regulation on the South African Hedge Fund industry.The focus of this research study was limited specifically to regulation in the Hedge Fund industry, although there are also proposals to strengthen regulations in other parts of the financial system. Qualitative research was conducted through a combination of face-to-face and telephonic interviews with stakeholders in the Hedge Fund industry.The research found that the proposed regulation would result in growth in the hedge fund industry by virtue of giving more credibility to the industry, thereby increasing the consumer base. The research also revealed that regulation would negatively impact the functioning of hedge funds and the quality of regulation in the industry was found to be good. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted

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This dissertation consists of two topics. Chapter 1 The Microstructure of the Reinsurance Network among US Property-Casualty Insurers and Its Effect on Insurers' Performance models the connectivity within the US property-casualty (P/C) reinsurance market as a network. It provides the first detailed empirical analysis of the microstructure of the reinsurance network including both affiliated and unaffiliated insurers. I find that reinsurance networks are highly sparse and yet largely connected, and exhibit hierarchical core-periphery structure. Moreover, an insurer's network position, measured by its network centrality, has economically significant implications for its loss experience and performance. Particularly, I find that there is an inverse U-shaped relationship between an insurer's network position and its combined ratio, and a U-shaped relationship between an insurer's network position and its performance measured by risk adjusted return on assets and risk adjusted return on equity. I also analyze the resilience of the reinsurance network against possible contagion risk by simulating economic impacts resulting from failures of one or more strategically networked reinsurers. The simulation results suggest that US Property-Casualty insurance industry is resilient to the failure of one or more top reinsurers. Chapter 2 Tail Risk Spillover and Its Contribution to Systemic Risk: A Network Analysis for Global Reinsurers analyzes the dynamic short-run tail risk dependence among global reinsurers and studies its contributions to global reinsurers' systemic risk, where a reinsurer's tail risk is measured by the Value-at-Risk. The tail risk dependence or tail risk spillover among global reinsurers is modeled as networks based on Granger Causality test. The results show that the tail risk interconnectedness among global reinsurers is subject to the impacts of both the insurance industry-wide shock and economy-wide shocks, where the former seems to have a larger effect than the latter. Moreover, I find that a reinsurer's role in the tail risk network as measured by degree/eigenvector centrality contributes significantly to its systemic risk, i.e., a more central tail risk network position will cause a higher level of systemic risk. I also find that there is a threshold effect of tail risk connectedness to systemic risk. That is, when the tail risk connectedness, as measured by daily network density, is below its median state, an increase in a reinsurer's tail risk network centrality will result in a decrease in its systemic risk possibly through risk diversification. In contrast, when the tail risk connectedness is above such threshold, an increase in the reinsurer's tail risk network centrality will lead to an increase in its systemic risk. / Business Administration/Risk Management and Insurance

Crop insurance is recognized as one of the most efficient mechanisms of income protection in agriculture, transferring risk from agriculture to other agents and economic sectors. Insurance tends to stimulate the increase of cultivated area and the use of technology, especially as it acts as an additional guarantee for access to credit. In Brazil, however, the massification of rural insurance is limited due to the restricted budget to fund government subsidization. Also, the lack of predictability and guarantee of resources prevents the long-term planning of investments by the private sector, imposes costs on the beneficiaries and generates dissatisfaction of the target public. This thesis aims to contribute to the expansion of crop insurance in Brazil through the research of index insurance, which has lower administrative and claim adjustment costs when compared to traditional insurance. The absence of in situ claim adjustment and moral hazard monitoring reduces the administrative costs of this type of insurance, permitting a subsidy free crop insurance. In the first of two articles, we explore the availability and quality of public databases for soybean yields and daily rainfall in the state of Paraná in Brazil in order to verify the feasibility of an index insurance product. We use multiple imputation by chained equations (MICE) to fill missing values in the rainfall dataset and study the existence of spatial and temporal patterns in the data by means of hierarchical clustering. Our results indicate that Paraná fulfills data requirements for a scalable weather index insurance with MICE and hierarchical clustering being effective tools in the pre-processing of data. The second article studies the efficiency of a novel regression approach, the geographically weighted quantile LASSO (GWQLASSO) in the modelling of yield-index relationship for weather index insurance products. GWQLASSO allows regression coefficients to vary spatially, while using the information from neighboring locations to derive robust estimates. The LASSO component of the model facilitates the selection of relevant explanatory variables. A weather index insurance (WII) product is developed based on 1-month SPI derived from a daily precipitation dataset for 41 weather stations in the State of Paraná (Brazil) for the period of 1979 through 2015. Soybean yield data are also used for the 41 municipalities from 1980 through 2015. The effectiveness of the GWQLASSO product is evaluated against a classic quantile regression approach and a traditional yield insurance product using the Spectral Risk Measure (SRM) and the Mean Semi-deviation. While GWQLASSO proved as effective as quantile regression it outperformed the yield insurance product, thus proving an alternative to the crop insurance market in Brazil and other locations with limited data. / O seguro agrícola é reconhecido como um dos mecanismos mais eficientes de proteção de renda na agricultura, transferindo o risco da fazenda para outros agentes e setores econômicos. O seguro tende a estimular o aumento da área cultivada e o uso de tecnologia, principalmente por atuar como garantia adicional de acesso ao crédito. No Brasil, no entanto, a massificação do seguro rural é limitada devido ao orçamento restrito para financiar o programa de subvenção governamental. Além disso, a falta de previsibilidade e garantia de recursos impede o planejamento de investimentos de longo prazo pelo setor privado, impõe custos aos beneficiários e gera insatisfação do público alvo. Esta tese visa contribuir para a expansão do seguro agrícola no Brasil por meio da pesquisa de seguro de índice climático, que possui menores custos administrativos e regulatórios quando comparado ao seguro tradicional. A ausência de validação de sinistro in loco e monitoramento de risco moral reduz os custos administrativos desse tipo de seguro, permitindo um seguro agrícola sem subsídio. No primeiro de dois artigos, exploramos a disponibilidade e a qualidade de bancos de dados públicos para produtividade de soja e precipitação diária no estado do Paraná, no Brasil, a fim de verificar a viabilidade de um produto de seguro de índice climático. Usamos a imputação múltipla por equações encadeadas (MICE) para preencher valores ausentes no conjunto de dados de precipitação e estudar a existência de padrões espaciais e temporais nos dados por meio de agrupamento hierárquico. Nossos resultados indicam que o Paraná preenche os requisitos de dados para um seguro de índice climático escalável com o uso do método MICE, e o agrupamento hierárquico é uma ferramenta eficaz no pré-processamento de dados. O segundo artigo estuda a eficiência de uma nova abordagem de regressão, a regressão quantílica LASSO ponderada geograficamente (GWQLASSO) na modelagem da relação entre o índice climático e a produtividade de soja. O GWQLASSO permite que os coeficientes de regressão variem espacialmente, enquanto utiliza a informação proveniente dos locais vizinhos de modo a obter estimativas robustas. O componente LASSO do modelo facilita a seleção de variáveis explicativas relevantes. Um produto de seguro de índice climático (WII) é desenvolvido com base em um índice de precipitação normalizado (intervalo de 1 mês) derivado de um conjunto de dados diários de precipitação para 41 estações meteorológicas (uma por município) no Estado do Paraná no período de 1979 a 2015. Os dados de rendimento da soja também são obtidos para estes 41 municípios de 1980 a 2015. A eficácia do produto GWQLASSO é avaliada em comparação com uma abordagem de regressão quantílica clássica e um produto tradicional de seguro de rendimento utilizando-se a medida de risco espectral (SRM) e o semi-desvio médio. Embora o GWQLASSO tenha se mostrado tão eficaz quanto a regressão quantílica, ele superou o produto de seguro de rendimento, provando assim ser uma alternativa ao mercado de seguro agrícola no Brasil e em outros locais com dados limitados.

This paper studies the effect of information disclosure on banks' portfolio risk. We cast a simple banking system into a general equilibrium model with trading frictions. We find that the information disclosure lowers the expected risk-adjusted profits for a non-negligible fraction of banks. The magnitude of this effect depends on the structure of the banking system and, alarmingly, it is more pronounced for systemically important institutions. We connect these theoretical findings to the stress test procedure, where bank information is disclosed by the regulator. The 2011 and 2014 stress tests are used in an empirical study to further support our theoretical results.

Thesis advisor: Robert Murphy / Thesis advisor: Hiroshi Nakazato / The majority of scholarship surrounding the late 2000s financial crisis explores the enabling factors that contributed to the subprime bubble and caused it to burst. This study’s purpose is to evaluate systemic risk and the near collapse of the financial sector in 2008. Several factors, including derivatives innovation, the rise of a parallel banking industry, and the securitization boom, heightened systemic fragility. I add to financial contagion literature by constructing a stochastic game theory model of institutional decision-making under the auspices of a severe liquidity shortage. Moreover, I will employ this model to evaluate the government’s regulatory program during the crisis. I find that the government’s ad hoc interventions and non-interventions significantly contributed to the atmosphere of uncertainty and exacerbated the crisis’ ill effects. I go on to evaluate the Dodd-Frank Act in light of those conclusions and suggest an alternate method of financial reform. / Thesis (BA) — Boston College, 2011. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: International Studies Honors Program. / Discipline: International Studies.

Risk assessment on interbank networks has drawn attention from researchers since the 2007 Subprime mortgage crisis. The lack of data for interbank transactions, which are usually not disclosed unless required by regulatory bodies, is one of the most critical difficulties to this research. A remedy to this issue is the dense reconstruction of interbank networks by using balance sheet data. The Maximum-Entropy estimation has been adopted by literature, however, this method produces networks with unrealistic properties: too dense in terms of having too many links. One alternative is sparse reconstruction that proposed by literature recently. This thesis applies the Message-Passing algorithm, which is extensively applied in Thermodynamics or Computer Science, and is suggested by Mastromatteo et al. [2012] for application in network reconstruction. Dense networks and sparse networks are reconstructed from Statistics on Depository Institutions data provided by Federal Deposit Insurance Corporation, and are compared by performance in both network properties and contagion simulations. The popular contagion mechanisms proposed by Furfine [2003] and the model of liquidity dry-up contagion proposed by Malherbe [2014] are adopted and compared in contagion simulations. Results show that dense networks and sparse networks perform differently in network properties and in contagions triggered by single-bank failures, while for contagions triggered by multiple-bank failures, both types of networks perform similarly. Furfine’s mechanism fail to predict some bank failures via the credit risk contagion on liquidity side, while these failures can be simulated by the liquidity dry-up model via fire-sale and marking-to-market effect. Both mechanisms overestimate the losses before the crisis, yet this signals the instability of the banking system, while the liquidity dry-up model proposes an explanation for why the banking system did not fail before the crisis, regarding to whether the equilibrium of high liquidity will shift to the self-fulfilling liquidity dry-up equilibrium. Implications on regulation are given.

This paper explores the economic rationales underpinning potential hedge fund regulation, and reviews the arguments about why rules aimed to mitigate systemic risk may be economically efficient. The paper presents a limited definition of systemic risk, and proposes that an international macro-prudential supervisory body be set up for the Ontario, U.S. and U.K. markets to collect systemically important information about hedge funds and to recommend policy changes in light of this information. The paper also reviews the proposed regulatory reforms in the United States that will apply to hedge funds, and argues that while helpful, such regulations are sub-optimal because they do not consider certain important characteristics of systemic risk.

This paper explores the economic rationales underpinning potential hedge fund regulation, and reviews the arguments about why rules aimed to mitigate systemic risk may be economically efficient. The paper presents a limited definition of systemic risk, and proposes that an international macro-prudential supervisory body be set up for the Ontario, U.S. and U.K. markets to collect systemically important information about hedge funds and to recommend policy changes in light of this information. The paper also reviews the proposed regulatory reforms in the United States that will apply to hedge funds, and argues that while helpful, such regulations are sub-optimal because they do not consider certain important characteristics of systemic risk.