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Risks
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Systemic Risk in Finance and Insurance
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Systemic Risk in Finance and Insurance

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 25704

Special Issue Editor

Dr. Traian A Pirvu

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada
Interests: optimal investment and pricing in incomplete markets; equilibrium pricing of non-tradable risks; optimal portfolio selection with regulatory constraints; time consistent portfolio management; prospect theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Financial regulations usually deal with limiting the risk of institutions, focusing mostly on idiosyncratic components while underestimating the systemic risk, which, in turn, may lead to financial crises. During a financial crisis, there are societal costs due to bailouts of failing banks, and economies tend to undercapitalize leading to financial contagion through banking-correlated networks. Thus, it appears only natural to come up with realistic measures for systemic risk to reduce the costs of financial crises or to prevent them in the first place. One such a measure of systemic risk is the systemic expected shortfall (SES) proposed by Acharya, Pedersen, Philippon, and Richardson (2017). SES is the expected amount by which a bank is undercapitalized in a global financial crisis scenario. Scenario risk measurements, developed by Larsen, Pirvu, Shreve, and Tutuncu (2005), may be also employed in quantifying systemic risk. The risk return optimization, which banks and insurance companies undertake, may be then considered within a paradigm that sets limits to their SES or other systemic risk measures.   

Prof. Dr. Traian A Pirvu
Guest Editor

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Keywords

  • Measures of systemic risk
  • Systemic expected shortfall
  • Market scenarios analysis of financial crisis
  • Risk return optimization via systemic risk

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Published Papers (6 papers)

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Research

18 pages, 427 KiB  
Article
Portfolio Optimization under Correlation Constraint
by Aditya Maheshwari and Traian A. Pirvu
Risks 2020, 8(1), 15; https://doi.org/10.3390/risks8010015 - 6 Feb 2020
Cited by 1 | Viewed by 3045
Abstract
We consider the problem of portfolio optimization with a correlation constraint. The framework is the multi-period stochastic financial market setting with one tradable stock, stochastic income, and a non-tradable index. The correlation constraint is imposed on the portfolio and the non-tradable index at [...] Read more.
We consider the problem of portfolio optimization with a correlation constraint. The framework is the multi-period stochastic financial market setting with one tradable stock, stochastic income, and a non-tradable index. The correlation constraint is imposed on the portfolio and the non-tradable index at some benchmark time horizon. The goal is to maximize a portofolio’s expected exponential utility subject to the correlation constraint. Two types of optimal portfolio strategies are considered: the subgame perfect and the precommitment ones. We find analytical expressions for the constrained subgame perfect (CSGP) and the constrained precommitment (CPC) portfolio strategies. Both these portfolio strategies yield significantly lower risk when compared to the unconstrained setting, at the cost of a small utility loss. The performance of the CSGP and CPC portfolio strategies is similar. Full article
(This article belongs to the Special Issue Systemic Risk in Finance and Insurance)
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25 pages, 1758 KiB  
Article
The Time-Spatial Dimension of Eurozone Banking Systemic Risk
by Matteo Foglia and Eliana Angelini
Risks 2019, 7(3), 75; https://doi.org/10.3390/risks7030075 - 6 Jul 2019
Cited by 10 | Viewed by 5243
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Systemic Risk in Finance and Insurance)
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17 pages, 1502 KiB  
Article
Memory, Risk Aversion, and Nonlife Insurance Consumption: Evidence from Emerging and Developing Markets
by Ashu Tiwari and Archana Patro
Risks 2018, 6(4), 145; https://doi.org/10.3390/risks6040145 - 14 Dec 2018
Cited by 8 | Viewed by 3738
Abstract
Policymakers in developing and emerging countries are facing higher risk that is related to natural disasters in comparison to developed ones because of persistent problem of supply-side bottleneck for disaster insurance. Additionally, lower insurance consumption, higher disaster risk, and high income elasticity of [...] Read more.
Policymakers in developing and emerging countries are facing higher risk that is related to natural disasters in comparison to developed ones because of persistent problem of supply-side bottleneck for disaster insurance. Additionally, lower insurance consumption, higher disaster risk, and high income elasticity of insurance demand have worsened the loss consequences of natural disaster in these markets. In this context, current study for the first time argues that the supply side bottleneck problem has its origin in peculiar pattern of disaster consumption owing to memory cues. The study finds that relatively higher frequency of natural disasters acts as a negative memory cue and positively impacts insurance consumption. On the other hand, a relatively lower frequency of natural disasters adversely impacts insurance consumption in the background of variation in risk aversion behavior. For this purpose, current study has based its work on Mullainathan (2002), which builds its argument around memory cues. Full article
(This article belongs to the Special Issue Systemic Risk in Finance and Insurance)
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26 pages, 1858 KiB  
Article
Modeling Financial System with Interbank Flows, Borrowing, and Investing
by Aditya Maheshwari and Andrey Sarantsev
Risks 2018, 6(4), 131; https://doi.org/10.3390/risks6040131 - 15 Nov 2018
Cited by 4 | Viewed by 3754
Abstract
In our model, private actors with interbank cash flows similar to, but more general than that by Carmona et al. (2013) borrow from the non-banking financial sector at a certain interest rate, controlled by the central bank, and invest in risky assets. Each [...] Read more.
In our model, private actors with interbank cash flows similar to, but more general than that by Carmona et al. (2013) borrow from the non-banking financial sector at a certain interest rate, controlled by the central bank, and invest in risky assets. Each private actor aims to maximize its expected terminal logarithmic wealth. The central bank, in turn, aims to control the overall economy by means of an exponential utility function. We solve all stochastic optimal control problems explicitly. We are able to recreate occasions such as liquidity trap. We study distribution of the number of defaults (net worth of a private actor going below a certain threshold). Full article
(This article belongs to the Special Issue Systemic Risk in Finance and Insurance)
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19 pages, 823 KiB  
Article
CoRisk: Credit Risk Contagion with Correlation Network Models
by Paolo Giudici and Laura Parisi
Risks 2018, 6(3), 95; https://doi.org/10.3390/risks6030095 - 12 Sep 2018
Cited by 23 | Viewed by 5348
Abstract
We propose a novel credit risk measurement model for Corporate Default Swap (CDS) spreads that combines vector autoregressive regression with correlation networks. We focus on the sovereign CDS spreads of a collection of countries that can be regarded as idiosyncratic measures of credit [...] Read more.
We propose a novel credit risk measurement model for Corporate Default Swap (CDS) spreads that combines vector autoregressive regression with correlation networks. We focus on the sovereign CDS spreads of a collection of countries that can be regarded as idiosyncratic measures of credit risk. We model CDS spreads by means of a structural vector autoregressive model, composed by a time dependent country specific component, and by a contemporaneous component that describes contagion effects among countries. To disentangle the two components, we employ correlation networks, derived from the correlation matrix between the reduced form residuals. The proposed model is applied to ten countries that are representative of the recent financial crisis: top borrowing/lending countries, and peripheral European countries. The empirical findings show that the contagion variable derived in this study can be considered as a network centrality measure. From an applied viewpoint, the results indicate that, in the last 10 years, contagion has induced a “clustering effect” between core and peripheral countries, with the two groups further diverging through, and because of, contagion propagation, thus creating a sort of diabolic loop extremely difficult to be reversed. Finally, the outcomes of the analysis confirm that core countries are importers of risk, as contagion increases their CDS spread, whereas peripheral countries are exporters of risk. Greece is an unfortunate exception, as its spreads seem to increase for both idiosyncratic factors and contagion effects. Full article
(This article belongs to the Special Issue Systemic Risk in Finance and Insurance)
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17 pages, 417 KiB  
Article
Mean Field Game with Delay: A Toy Model
by Jean-Pierre Fouque and Zhaoyu Zhang
Risks 2018, 6(3), 90; https://doi.org/10.3390/risks6030090 - 1 Sep 2018
Cited by 5 | Viewed by 3298
Abstract
We study a toy model of linear-quadratic mean field game with delay. We “lift” the delayed dynamic into an infinite dimensional space, and recast the mean field game system which is made of a forward Kolmogorov equation and a backward Hamilton-Jacobi-Bellman equation. We [...] Read more.
We study a toy model of linear-quadratic mean field game with delay. We “lift” the delayed dynamic into an infinite dimensional space, and recast the mean field game system which is made of a forward Kolmogorov equation and a backward Hamilton-Jacobi-Bellman equation. We identify the corresponding master equation. A solution to this master equation is computed, and we show that it provides an approximation to a Nash equilibrium of the finite player game. Full article
(This article belongs to the Special Issue Systemic Risk in Finance and Insurance)
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