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.

The banking sector plays an important part of the modern society and a collapse of the financial system would have severe consequences for the society. In order to protect the system from a systemic collapse, regulations have been put in place to ensure a more stable financial system. Because of the financial instabilities experienced in recent years, the Basel Committee has released an improved framework in order to deal with the systemic risk which contributed to the crisis. Parts of the new Basel III Accord will be implemented in 2013, and this is why we have chosen to study how Swedish banks perceive the impact of the Basel III Accord and its effect on systemic risk. Our intention is to study the perception of the impact of the Basel III framework on the Swedish bank sector through a study of the four largest banks in Sweden. We examine how these four banks expect the Basel III Accord to affect systemic risk and consequently improve the protection of these banks, and also the Swedish banking industry and more generally the Swedish economy. The research paradigm of this study is constructivism, which is in line with our research question and purpose, since we have studied and analyzed the perceptions of the Swedish banking sector. In order to answer our research question and purpose we have used an inductive research approach, as well as a qualitative research strategy. The data was collected through 10 semi-structured interviews with people from the four largest banks in Sweden. The theoretical frame of reference is divided into four parts. The first part consists of a discussion on the Swedish banking sector, as well as a presentation of the four largest banks. In the second part of the chapter we review the current research regarding systemic risk. We then present the most important aspects and elements of the forthcoming Basel III Accord and at last we assemble the three areas together in a final discussion. The findings in the study disclose new knowledge. The knowledge consist of the Swedish banks’, through the 10 interviewees, perception of the impact of the Basel III Accord and its effect on systemic risk. The Swedish banks hold a positive perception of: higher capital requirements set out in Basel III, the counter cyclical buffer, the basic concept of implementing liquidity standards, the Basel III will (1) to some degree reduce systemic risk, (2) improve the protection of the Swedish banks, (3) decrease the probability of financial instabilities, and (4) enhance the Swedish banks ability to meet a new financial crisis. The Swedish banks hold a neutral perception of: the risk coverage and the LCR. The Swedish banks hold a negative perception of: the higher capital requirements implemented in Sweden, the frameworks’ competitive disadvantage, the capital conservation buffer, the NSFR, the leverage ratio, that the Basel III will (1) increase costs that will affect customers, shareholders and/or employees negatively, (2) impair growth, and (3) not be able to prevent a new kind of financial crisis.

In this paper, we study the implications of diversification in the asset portfolios of banks for financial stability and systemic risk. Adding to the existing literature, we analyse this issue in a network model of the interbank market. We carry out a simulation study that determines the probability of a systemic crisis in the banking network as a function of both the level of diversification, and the connectivity and structure of the financial network. In contrast to earlier studies we find that diversification at the level of individual banks may be beneficial for financial stability even if it does lead to a higher asset return correlation across banks.

The first chapter analyzes the impact of macroprudential policies on bank systemic risk worldwide. Using data from 63 countries over 2001-2017, I find strong evidence that macroprudential policies are effective in reducing systemic risk at the country level. The effectiveness of macroprudential policies differs across countries in the sample. Macroprudential policies are more effective in reducing systemic risk in countries with more advanced economic development, with a higher degree of concentration in the banking sector, and with less stringent micro-prudential regulations. Bank-level evidence suggests that bank size matters. The impact of macroprudential policies on constraining bank systemic risk is more pronounced for large banks. Results are robust to the use of instrumental variables to address potential concerns, and to the inclusion of additional controls to account for the impact of alternate tools that might be used to foster financial stability. These results have policy implications for effective conduct of macroprudential policies. The second chapter examines the impact of macroprudential policies on private credit growth worldwide. Using data from 43 countries over 2001-2017, I confirm previous findings that borrower-targeted macroprudential policies (Loan-to-Value ratio and Debt-to-Income ratio) significantly reduce total private credit growth. Moreover, the impact of macroprudential policies on private credit differs across countries in the sample. Macroprudential policies negatively affect credit growth only in countries with less advanced economic development, with a lower degree of creditor protection, and without the existence of information sharing institutions. Results are robust to additional controls to account for the impact of alternate bank regulations and policies that might be used to constrain unsustainable credit growth. The third chapter examines the impact of loan loss provisions regulations on bank income smoothing. Using a sample of 2,380 banks from 107 countries over the period 1995-2016, I document evidence that stricter loan classification regulation reduces bank income smoothing through loan loss provisions, especially for big banks. However, I do not find such impact of loan provisioning regulation. I also find evidence that stricter loan classification regulation is effective at reducing bank income smoothing because it encourages banks to recognize loan loss in a more timely manner.

The 2008 financial crisis revealed systemic weaknesses in the global financial architecture, gave rise to the most severe economic collapse since the Great Depression and engendered a fundamental shift in the prevailing consensus on financial governance. It reminded us of the fragility of the international financial system and the politically unacceptable costs to society when it fails. This dissertation adds to the literature on the governance of private and public sector financial institutions. It presents a conceptual framework of linkage between the governance of financial institutions, systemic risk and financial crises. It is based on a review of the empirical and theoretical literature on the influence of financial regulation and governance on the stability of the international financial system. The dissertation examines the application of financial governance in three different contexts: (i) the introduction of a common regulatory framework for the European securities industry, known as MIFID; (ii) the introduction of a risk governance framework at a US federal agency, the US Export-Import Bank, and (iii) the introduction of performance metrics among Export Credit Agencies that operate within a common governance framework known as the Arrangement on Officially Supported Export Credits. In addition, the dissertation provides specific policy recommendations designed to enhance the portfolio risk management practices of the US Export Import Bank. By extension, these recommendations are relevant to a wider audience of federal agencies with similar portfolio credit risks and may help inform the design of a robust risk management framework that is critical to the government's ability to manage its burgeoning credit portfolio. / Ph. D.

Systemic risk is the risk that an economic shock may result in the breakdown of the fundamental functions of the financial system. It can involve multiple vectors of infection such as chains of losses or consecutive failures of financial institutions that may ultimately cause the failure of the financial system to provide liquidity, stable prices, and to perform economic activities. This thesis develops methods to quantify systemic risk, its effect on the financial system and perhaps more importantly, to determine its cause. In the first chapter, we provide an overview and a literature review of the topics covered in this thesis. First, we present a literature review on network-based models of systemic risk. Finally we end the first chapter with a review on market impact models. In the second chapter, we consider one unregulated financial institution with constant absolute risk aversion investment risk preferences that optimizes its strategies in a multi asset market impact model with temporary and permanent impact. We prove the existence and derive explicitly the optimal trading strategies. Furthermore, we conduct numerical exploration on the sensitivity of the optimal trading curve. This chapter sets the foundation for further research into multi-agent models and systemic risk models with optimal behaviours. In the third chapter, we extend the market impact models to the multi-agent setting. The agents follow a game theoretic strategy that is constrained by the regulations imposed. Furthermore, the agents must liquidate themselves if they become insolvent or unable to meet the regulations imposed on them. This paper provides a bridge between market impact models and network models of systemic risk. In chapter four, we introduce a financial network model that combines the default and liquidity stress mechanisms into a ``double cascade mapping''. Unlike simpler models, this model can quantify how illiquidity or default of one bank influences the overall level of liquidity stress and default in the system. We derive large-network asymptotic cascade mapping formulas that can be used for efficient network computations of the double cascade. Finally we use systemic risk measures to compare the results of including with and without an asset firesale mechanism. / Thesis / Doctor of Philosophy (PhD)

Diploma thesis deals with the issue of systemic risk and its impact on the financial system. In terms of the explanation of the individual regularities analyses principles of systemic risk and its impact on the financial sector. The first part of this work is dedicated to a complex analysis of the systemic risk sources and a description of different measurement methods among others also dedicated to detection of systemically important institutions. The analytical part demonstrates an application of one of the model for systemic risk measurement on the real data from the United States of America between years 1990 and 2011 and the analysis of the newly adopted Dodd-Frank Act regulation. The main merit of this work is to describe and evaluate the complex perspective of the systemic risk, which is a prerequisite for its successful application and management.

Management of systemic risk in financial markets is traditionally associated with setting (higher) capital requirements for market participants. There are indications that while equity ratios have been increased massively since the financial crisis, systemic risk levels might not have lowered, but even increased (see ECB data 1 ; SRISK time series 2 ). It has been shown that systemic risk is to a large extent related to the underlying network topology of financial exposures. A natural question arising is how much systemic risk can be eliminated by optimally rearranging these networks and without increasing capital requirements. Overlapping portfolios with minimized systemic risk which provide the same market functionality as empir- ical ones have been studied by Pichler et al. (2018). Here we propose a similar method for direct exposure networks, and apply it to cross-sectional interbank loan networks, consisting of 10 quarterly observations of the Austrian interbank market. We show that the suggested framework rearranges the network topol- ogy, such that systemic risk is reduced by a factor of approximately 3.5, and leaves the relevant economic features of the optimized network and its agents unchanged. The presented optimization procedure is not intended to actually re-configure interbank markets, but to demonstrate the huge potential for systemic risk management through rearranging exposure networks, in contrast to increasing capital requirements that were shown to have only marginal effects on systemic risk (Poledna et al., 2017). Ways to actually incentivize a self-organized formation toward optimal network configurations were introduced in Thurner and Poledna (2013) and Poledna and Thurner (2016). For regulatory policies concerning financial market stability the knowledge of minimal systemic risk for a given economic environment can serve as a benchmark for monitoring actual systemic risk in markets.

The thesis presents a network model, where financial institutions form linkages at various investment horizons through their interdependence measured by volatility connectedness. Applying the novel framework of frequency connectedness mea- sures Baruník & Křehlík (2018), based on spectral representation of variance de- composition, we show fundamental properties of connectedness that originate in heterogeneous frequency responses to shocks. The newly proposed network mod- els characterize financial connections and systemic risk at the short-, medium- and long-term frequency. The empirical focus of this thesis is on the interde- pendence structure of US financial system, specifically, major U.S. banks in the period 2000 - 2016. In the light of frequency volatility connectedness measures, we argue that stocks with high levels of long-term connectedness represent greater systemic risk, because they are subject to persistent shocks transmitted for longer periods. When we assess institutions' risk premiums in asset pricing model, the model confirms the significance of volatility connectedness factor for asset prices. JEL Classification C18, C58, C58, G10, G15, Keywords connectedness, frequency, spectral analysis, sys- temic risk, financial network Author's e-mail 93539385@fsv.cuni.cz Supervisor's e-mail...

This dissertation is composed of three chapters, each an application of Bayesian statistical models to particular research questions. In Chapter 1, we evaluate systemic risk exposure of financial institutions. Building upon traditional regime switching approaches, we propose a network model for volatility contagion to assess linkages between institutions in the financial system. Focusing empirical analysis on the financial sector, we find that network connectivity has dynamic properties, with linkages between institutions increasing immediately before the recent crisis. Out-of-sample forecasts demonstrate the ability of the model to predict losses during distress periods. We find that institutional exposure to crisis events depends upon the structure of linkages, not strictly the number of linkages. In Chapter 2, we develop procedures for benchmarking small area estimates. In sample surveys, precision can be increased by introducing small area models which "borrow strength" by incorporating auxiliary covariate information. One consequence of using small area models is that small area estimates at lower geographical levels typically will not aggregate to the estimate at the corresponding higher geographical levels. Benchmarking is the statistical procedure for reconciling these differences. Two new approaches to Bayesian benchmarking are introduced, one procedure based on Minimum Discrimination Information, and another for Bayesian self-consistent conditional benchmarking. Notably the proposed procedures construct adjusted posterior distributions whose moments all satisfy benchmarking constraints. In the context of the Fay-Herriot model, simulations are conducted to assess benchmarking performance. In Chapter 3, we exploit the Pair Copula Construction (PCC) to develop a flexible multivariate model for time-varying dependence. The PCC is an extremely flexible model for capturing complex, but static, multivariate dependency. We use a Bayesian framework to extend the PCC to account for time dynamic dependence structures. In particular, we model the time series of a transformation of parameters of the PCC as an autoregressive model, conducting inference using a Markov Chain Monte Carlo algorithm. We use financial data to illustrate empirical evidence for the existence of time dynamic dependence structures, show improved out-of-sample forecasts for our time dynamic PCC, and assess performance of dynamic PCC models for forecasting Value-at-Risk. / Statistics