Query: non-financial systemic risk

title: Do China's Non Financial Firms Affect Systemic Risk?
abstract: This article investigates the contribution of non financial firms to systemic risk in the entire financial system and the corresponding firm specific determinants. Thus, we develop a new measure of systemic risk with a test of our hypothesis that separates systemic risk from systematic risk. We also consider the firm level determinants of contributions to systemic risk using a fixed effects model and a logit model. Using data on companies in the CSI 300 index from 2008 to 2016, we find that our extreme value theory (EVT) copula method is a good fit for testing the joint probability distribution of extreme returns as well as diverse dependence patterns with asymmetry and non linearity characteristics. The empirical results provide evidence against the marginal expected shortfall (MES) method without a mechanism to test the statistical significance of determination. Several non financial firms, though not all financial institutions, can generate significant spillover effects on the financial system. Our regression results suggest that, among firms with a significantly positive contribution to systemic risk, smaller firms have greater spillover effects on the financial system in China. Moreover, economy wide systemic risk information and dynamic identification on systemically important firms deserve more attention in terms of macro prudential regulation.

title: Assessment of Russian non financial companies' systemic risk in financial stability monitoring
abstract: Subject. The article addresses the issues of financial stability monitoring as part of macroprudental supervision and regulation. The study concerns non financial companies as a source of systemic risk for the national financial system. There are a lot of discussions about monitoring of systemically important borrowers under the auspices of the Russian Regulator.  Research is aimed at developing a methodology for assessing the systemic risk of Russian non financial companies.  We propose a set of indicators to assess the systemic risk derived from non financial companies in Russia. The sample of indicators corresponds with the leading international practice and available data. The dynamic analysis of the sampled indicators should be conducted. We should focus on separate indicators and for a comprehensive view using a new composite indicator of systemic risk.  We devised a methodology for assessing the systemic risk of Russian non financial companies. The relevance of the methodology was proved with empirical data. The sample includes 3,766 companies per year. The proposed indicators were proved to reflect an adequate change in the tested period (the year before, during and after financial instability)  Our methodology contributes to the current scientific discussion on new directions for assessing the financial stability. The results can be applied to the analytical practice, including the macroprudential supervision and regulation.

title: Systemic Risk in the Insurance Banking Brokerage and Non Financial Sectors Time Lags and Persistence
abstract: Common systemic risk measures focus on the instantaneous occurrence of triggering and systemic events. However, systemic events may occur with a time lag to the triggering event. To study this contagion period and the resulting persistence of institutions' systemic risk, we develop and employ the Conditional Shortfall Probability (CoSP) which is the likelihood that a systemic market event occurs with a specific time lag to the triggering event. Based on CoSP we propose two aggregate systemic risk measures, namely the Aggregate Excess CoSP and the CoSP weighted time lag that reflect the systemic persistence and contagion period of an institution's triggering event. Our empirical results show a significant systemic time lag for various institutions. The size of this time lag and the related systemic risk (measured by CoSP) depend on the respective institution and market. In general, we find that brokers exhibit the most persistent systemic impact on all considered markets, whereas non financial companies have the smallest systemic persistence. Insurance companies are exposed to the largest systemic persistence among financial institutions, particularly if systemic risk is triggered by non financial companies. In contrast, the systemic persistence of insurance companies is similar to that of banks but substantially smaller than the systemic persistence of brokers.

title: Do firm level factors play forward looking role for financial systemic risk: Evidence from China
abstract: This paper examines the firm level driving factors of the systemic risk in the Chinese banking system. To more accurately estimate the systemic risk, we take asymmetric and fat tailed financial returns into consideration. Our empirical results reveal that the Chinese banks' systemic risk contribution reached the highest level during the stock market crash in 2015. The panel regression results imply that banks' size, leverage, loans, non performing loans and demand deposits positively drive their systemic risk contribution, and ROA, loan loss provisions and time deposits shows a negative relationship. Moreover, individual bank's VaR increase its systemic risk contribution, which means that the riskier individual bank contributes more to the systemic risk. The forward looking role of the firm level factors can potentially be used for macro prudential regulation.

title: Non Performing Loans and Systemic Risk in Financial Networks
abstract: In this paper we study the implications of non performing loans (NPLs) for financial stability using a network based approach. We start by combining loan level data from DealScan and firm level data from Orbis to reconstruct the empirical global financial network in the period 1991 2016 and identify a series of stylized facts. Based on these findings, we develop a model in which two types of agents, banks and firms, are linked in a network by their reciprocal claims and analyze how an increase in NPLs affects the stability of the system. We study the model analytically and with numerical simulations, deriving a synthetic measure of systemic risk and quantifying the threshold level of NPLs that triggers a systemic crisis. Our model shows that there exist a level of connectivity that maximizes the fragility of the financial system and that small changes in the initial NPLs shock can have very different consequences at the aggregate level.

title: Tail Risk Networks of Insurers Around the Globe: An Empirical Examination of Systemic Risk for G SIIs vs Non G SIIs
abstract: In this article, we investigate systemic risk of 157 insurers around the globe. We construct tail risk networks among these insurers using a single index model for quantile regressions with a variable selection technique. We develop a new network based systemic risk indices, taking into account expected tail losses of insurers, direct and indirect contagion effects, and the time varying strength of tail risk spillover. Our systemic risk indices successfully recognize global systemically important insurers (G SIIs) We find that on average G SIIs are more systemically relevant than non G SIIs, particularly during the recent U.S. financial crisis. We also find a small group of non G SIIs that are more important than G SIIs. Our results have significant implications for systemic risk regulation.

title: Banks' Noninterest Income and Systemic Risk
abstract: This paper examines the contribution of non interest income to systemic bank risk. Using the CoVaR measure of Adrian and Brunnermeier (2010) as our proxy for systemic risk, we find banks with a higher non interest income to interest income ratio have a higher contribution to systemic risk. This suggests that activities that are not traditionally associated with banks (such as deposit taking and lending) are associated with a larger contribution to systemic risk. When we decompose total non interest income into three components, we find trading income and investment banking and venture capital income to be significantly related to systemic risk. The economic impact on systemic risk of investment banking and venture capital income is higher than that of trading income. Finally we find the impact of non interest income on systemic risk to be prevalent in the 1990 and 2007 financial crises (which were bank based) and not in the case before the 2001 high tech bubble bust. These effects occur one year before each crisis and not during the recession, showing their countercyclical contribution to systemic risk build up.

title: From Lombard Street to Wall Street: Systemic Risk, Rescues, and Stability in Financial Networks
abstract: This paper proposes a novel regulatory framework for financial interconnectedness and introduces a new concept: "self contained networks" In networks where each bank is too costly for other banks to let fail, banks endogenously rescue each other. Such networks are self contained since they minimize external assistance (bailouts) required to maintain stability. In such networks, banks have intermediate levels of interbank liabilities and non clustered interbank exposures. The results reverse the general insights into contagion: In self contained networks, system wide contagion risk leads to greater stability. Moreover, "letting a systemically important bank fail" arises at equilibrium for large shocks, which explains (non )rescues in 2007 2008.

title: Networks and systemic risk in the financial system
abstract: The complex web of exposures and interlinkages across the financial system highlights the relevance of network analysis in understanding systemic risk and guiding the design of financial regulation. This paper discusses how network models and those based on epidemiological approaches in particular offer a compelling description of the structure of real world financial systems and shed light on different contagion mechanisms seen during the global financial crisis. We also review how these insights may inform macroprudential risk assessment and policy in the areas of stress testing the financial system and the regulation of systemically important institutions. The role of non bank financial intermediation and social networks in shaping financial system risk is also briefly considered.

title: Analyzing Credit Risk Transmission to the Non Financial Sector in Europe: A Network Approach
abstract: We use a factor model and elastic net shrinkage to model a high dimensional network of European CDS spreads. Our empirical approach allows us to assess the joint transmission of bank and sovereign risk to the non financial corporate sector. Our findings identify a sectoral clustering in the CDS network, where financial institutions are in the center and non financial entities as well as sovereigns are grouped around the financial center. The network has a geographical component reflected in different patterns of real sector risk transmission across countries. Our framework also provides dynamic estimates of risk transmission, a useful tool for systemic risk monitoring.