scholarly journals An Equilibrium-Based Measure of Systemic Risk

2021 ◽  
Vol 14 (9) ◽  
pp. 414
Author(s):  
Katerina Ivanov ◽  
James Schulte ◽  
Weidong Tian ◽  
Kevin Tseng
Keyword(s):  
Empirical Study ◽  
Systemic Risk ◽  
Equilibrium Model ◽  
Risk Measure ◽  
Too Big To Fail

This paper develops and implements an equilibrium model of systemic risk. The model derives a systemic risk measure, loss beta, in characterizing all too-big-to-fail banks using a capital insurance equilibrium. By constructing each bank’s loss portfolio with a recent accounting approach, we perform a comprehensive empirical study of this loss beta measure and document all TBTF banks from 2002 to 2019. Our empirical findings suggest a significant number of too-big-to-fail banks in 2018–2019.

scholarly journals Identify too big to fail banks and capital insurance: An equilibrium approach

2017 ◽  
Vol 7 (4) ◽  
pp. 62-87
Author(s):  
Katerina Ivanov
Keyword(s):  
Systemic Risk ◽  
Rational Expectation ◽  
Innovation Policy ◽  
Risk Measure ◽  
Too Big To Fail ◽  
Market Participants ◽  
Policy Tool ◽  
Equilibrium Approach ◽  
Rational Expectation Equilibrium ◽  
High Level

The objective of this paper is develop a rational expectation equilibrium model of capital insurance to identify too big to fail banks. The main results of this model include (1) too big to fail banks can be identified explicitly by a systemic risk measure, loss betas, of all banks in the entire financial sector; (2) the too big to fail feature can be largely justified by a high level of loss beta; (3) the capital insurance proposal benefits market participants and reduces the systemic risk; (4) the implicit guarantee subsidy can be estimated endogenously; and lastly, (5) the capital insurance proposal can be used to resolve the moral hazard issue. We implement this model and document that the too big to fail issue has been considerably reduced in the pro-crisis period. As a result, the capital insurance proposal could be a useful macro-regulation innovation policy tool.

scholarly journals Statistical Inference for the Beta Coefficient

Risks ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 56 ◽  
Author(s):  
Taras Bodnar ◽  
Arjun K. Gupta ◽  
Valdemar Vitlinskyi ◽  
Taras Zabolotskyy
Keyword(s):  
Confidence Interval ◽  
Empirical Study ◽  
Crucial Role ◽  
Risk Measure ◽  
Statistical Test ◽  
Asymptotic Distributions ◽  
Finite Sample ◽  
Benchmark Portfolio ◽  
Beta Coefficient ◽  
Theoretical Results

The beta coefficient plays a crucial role in finance as a risk measure of a portfolio in comparison to the benchmark portfolio. In the paper, we investigate statistical properties of the sample estimator for the beta coefficient. Assuming that both the holding portfolio and the benchmark portfolio consist of the same assets whose returns are multivariate normally distributed, we provide the finite sample and the asymptotic distributions of the sample estimator for the beta coefficient. These findings are used to derive a statistical test for the beta coefficient and to construct a confidence interval for the beta coefficient. Moreover, we show that the sample estimator is an unbiased estimator for the beta coefficient. The theoretical results are implemented in an empirical study.

scholarly journals The Time-Spatial Dimension of Eurozone Banking Systemic Risk

Risks ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 75 ◽  
Author(s):  
Matteo Foglia ◽  
Eliana Angelini
Keyword(s):  
Spatial Econometrics ◽  
Systemic Risk ◽  
Spatial Dependence ◽  
Financial Stability ◽  
Risk Measure ◽  
Spatial Dimension ◽  
Time Dimension ◽  
Cross Sectional ◽  
Time Space ◽  
Contagion Risk

In this paper, we measure the systemic risk with a novel methodology, based on a “spatial-temporal” approach. We propose a new bank systemic risk measure to consider the two components of systemic risk: cross-sectional and time dimension. The aim is to highlight the “time-space dynamics” of contagion, i.e., if the CDS spread of bank i depends on the CDS spread of other banks. To do this, we use an advanced spatial econometrics design with a time-varying spatial dependence that can be interpreted as an index of the degree of cross-sectional spillovers. The findings highlight that the Eurozone banks have strong spatial dependence in the evolution of CDS spread, namely the contagion effect is present and persistent. Moreover, we analyse the role of the European Central Bank in managing contagion risk. We find that monetary policy has been effective in reducing systemic risk. However, the results show that systemic risk does not imply a policy intervention, highlighting how financial stability policy is not yet an objective.

Origins of too-big-to-fail policy in the United States

2020 ◽  
Vol 27 (1) ◽  
pp. 1-15
Author(s):  
George C. Nurisso ◽  
Edward Simpson Prescott
Keyword(s):  
United States ◽  
Federal Reserve ◽  
Systemic Risk ◽  
Deposit Insurance ◽  
The United States ◽  
Too Big To Fail ◽  
Interstate Banking ◽  
Legal Constraints ◽  
Federal Deposit Insurance ◽  
Over Time

This article traces the origin of too-big-to-fail policy in modern US banking to the bailout of the $1.2b Bank of the Commonwealth in 1972. It describes this bailout and those of subsequent banks through that of Continental Illinois in 1984. During this period, market concentration due to interstate banking restrictions is a factor in most of the bailouts and systemic risk concerns were raised to justify the bailouts of surprisingly small banks. Finally, most of the bailouts in this period relied on the Federal Deposit Insurance Corporation's use of the Essentiality Doctrine and Federal Reserve lending. A discussion of this doctrine is used to illustrate how legal constraints on regulators may become less constraining over time.

SYSTEMIC RISK: THE EFFECT OF MARKET CONFIDENCE

2020 ◽  
Vol 23 (07) ◽  
pp. 2050043
Author(s):  
MAXIM BICHUCH ◽  
KE CHEN
Keyword(s):  
Nash Equilibrium ◽  
Simple Model ◽  
Empirical Study ◽  
Systemic Risk ◽  
Existence And Uniqueness ◽  
Maximum Amount ◽  
The Other ◽  
Nash Equilibrium Point ◽  
Optimal Mix ◽  
Uniqueness Of Nash Equilibrium

In a crisis, when faced with insolvency, banks can sell stock in a dilutive offering in the stock market and borrow money in order to raise funds. We propose a simple model to find the maximum amount of new funds the banks can raise in these ways. To do this, we incorporate market confidence of the bank together with market confidence of all the other banks in the system into the overnight borrowing rate. Additionally, for a given cash shortfall, we find the optimal mix of borrowing and stock selling strategy. We show the existence and uniqueness of Nash equilibrium point for all these problems. Finally, using this model we investigate if banks have become safer since the crisis. We calibrate this model with market data and conduct an empirical study to assess safety of the financial system before, during after the last financial crisis.

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