Systemic Risk and Reinsurance

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

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 44727

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Department of Finance, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA
Interests: asset pricing; risk management; Knightian uncertainty; derivative and insurance market
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Dear Colleagues,

It is widely recognized that since the 2008–2009 financial crisis there exist essential flaws in the supervisory system and that further regulatory measures must put in place in the financial sector. Many proposals under consideration, or already embraced by regulatory authorities, focus on the “systemically important financial institutions” or banks “too big/connected to fail”. However, insurers and banks played markedly different roles in the financial crisis. Therefore, it is important to study the systemic risk for the insurer, and the nature of systemic risk from the reinsurance perspective. It is also important to examine how insurance business models, such as capital insurance, provide an alternative approach to systemic risk.

You are cordially invited to submit your research or proposal to the Topical Collection “Systemic Risk and Reinsurance” in the academic journal Risks. We welcome all high-quality papers related to systemic risk and reinsurance, in particular on the following topics:

• theoretical or empirical analysis of insurance and financial stability
• regulatory capital for the insurance sector
• forward-looking capital regulation
• capital insurance
• comparison between tax and insurance for systemic risk
• the “too connected to fail” issue

Prof. Dr. Weidong Tian

Guest Editor

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Manuscripts for the topical collection can be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on this website. The topical collection considers regular research articles, short communications and review articles. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

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Published Papers (7 papers)

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Research

22 pages, 3532 KiB  
Article
A Tail Dependence-Based MST and Their Topological Indicators in Modeling Systemic Risk in the European Insurance Sector
by Anna Denkowska and Stanisław Wanat
Risks 2020, 8(2), 39; https://doi.org/10.3390/risks8020039 - 22 Apr 2020
Cited by 7 | Viewed by 3581
Abstract
In the present work, we analyze the dynamics of indirect connections between insurance companies that result from market price channels. In our analysis, we assume that the stock quotations of insurance companies reflect market sentiments, which constitute a very important systemic risk factor. [...] Read more.
In the present work, we analyze the dynamics of indirect connections between insurance companies that result from market price channels. In our analysis, we assume that the stock quotations of insurance companies reflect market sentiments, which constitute a very important systemic risk factor. Interlinkages between insurers and their dynamics have a direct impact on systemic risk contagion in the insurance sector. Herein, we propose a new hybrid approach to the analysis of interlinkages dynamics based on combining the copula-DCC-GARCH model and minimum spanning trees (MST). Using the copula-DCC-GARCH model, we determine the tail dependence coefficients. Then, for each analyzed period we construct MST based on these coefficients. The dynamics are analyzed by means of the time series of selected topological indicators of the MSTs in the years 2005–2019. The contribution to systemic risk of each institution is determined by analyzing the deltaCoVaR time series using the copula-DCC-GARCH model. Our empirical results show the usefulness of the proposed approach to the analysis of systemic risk (SR) in the insurance sector. The times series obtained from the proposed hybrid approach reflect the phenomena occurring in the market. We check whether the analyzed MST topological indicators can be considered as systemic risk predictors. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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727 KiB  
Article
Community Analysis of Global Financial Markets
by Irena Vodenska, Alexander P. Becker, Di Zhou, Dror Y. Kenett, H. Eugene Stanley and Shlomo Havlin
Risks 2016, 4(2), 13; https://doi.org/10.3390/risks4020013 - 13 May 2016
Cited by 21 | Viewed by 7104
Abstract
We analyze the daily returns of stock market indices and currencies of 56 countries over the period of 2002–2012. We build a network model consisting of two layers, one being the stock market indices and the other the foreign exchange markets. Synchronous and [...] Read more.
We analyze the daily returns of stock market indices and currencies of 56 countries over the period of 2002–2012. We build a network model consisting of two layers, one being the stock market indices and the other the foreign exchange markets. Synchronous and lagged correlations are used as measures of connectivity and causality among different parts of the global economic system for two different time intervals: non-crisis (2002–2006) and crisis (2007–2012) periods. We study community formations within the network to understand the influences and vulnerabilities of specific countries or groups of countries. We observe different behavior of the cross correlations and communities for crisis vs. non-crisis periods. For example, the overall correlation of stock markets increases during crisis while the overall correlation in the foreign exchange market and the correlation between stock and foreign exchange markets decrease, which leads to different community structures. We observe that the euro, while being central during the relatively calm period, loses its dominant role during crisis. Furthermore we discover that the troubled Eurozone countries, Portugal, Italy, Greece and Spain, form their own cluster during the crisis period. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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1065 KiB  
Article
The Impact of Reinsurance Strategies on Capital Requirements for Premium Risk in Insurance
by Gian Paolo Clemente, Nino Savelli and Diego Zappa
Risks 2015, 3(2), 164-182; https://doi.org/10.3390/risks3020164 - 3 Jun 2015
Cited by 4 | Viewed by 7905
Abstract
New risk-based solvency requirements for insurance companies across European markets have been introduced by Solvency II and will come in force from 1 January 2016. These requirements, derived by a Standard Formula or an Internal Model, will be by far more risk-sensitive than [...] Read more.
New risk-based solvency requirements for insurance companies across European markets have been introduced by Solvency II and will come in force from 1 January 2016. These requirements, derived by a Standard Formula or an Internal Model, will be by far more risk-sensitive than the required solvency margin provided by the current legislation. In this regard, a Partial Internal Model for Premium Risk is developed here for a multi-line Non-Life insurer. We follow a classical approach based on a Collective Risk Model properly extended in order to consider not only the volatility of aggregate claim amounts but also expense volatility. To measure the effect of risk mitigation, suitable reinsurance strategies are pursued. We analyze how naïve coverage as conventional Quota Share and Excess of Loss reinsurance may modify the exact moments of the distribution of technical results. Furthermore, we investigate how alternative choices of commission rates in proportional treaties may affect the variability of distribution. Numerical results are also figured out in the last part of the paper with evidence of different effects for small and large companies. The main reasons for these differences are pointed out. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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1116 KiB  
Article
Interconnectedness of Financial Conglomerates
by Gaël Hauton and Jean-Cyprien Héam
Risks 2015, 3(2), 139-163; https://doi.org/10.3390/risks3020139 - 21 May 2015
Cited by 2 | Viewed by 6839
Abstract
Being active in both the insurance sector and the banking sector, financial conglomerates intrinsically increase the interconnections between the banking sector and the insurance sector. We address two main concerns about financial conglomerates using a unique database on bilateral exposures between 21 French [...] Read more.
Being active in both the insurance sector and the banking sector, financial conglomerates intrinsically increase the interconnections between the banking sector and the insurance sector. We address two main concerns about financial conglomerates using a unique database on bilateral exposures between 21 French financial institutions. First, we investigate to what extent to which the insurers that are part of financial conglomerates differ from pure insurers. Second, we show that in the presence of sovereign risk, the components of a financial conglomerate are better off than if they were distinct entities. Our empirical findings bring a new perspective to the previous results of the literature based on using different types of data. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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423 KiB  
Article
Optimal Dynamic Portfolio with Mean-CVaR Criterion
by Jing Li and Mingxin Xu
Risks 2013, 1(3), 119-147; https://doi.org/10.3390/risks1030119 - 11 Nov 2013
Cited by 6 | Viewed by 5278
Abstract
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman–Pearson type binary solution. We add a constraint on expected return to investigate the mean-CVaR [...] Read more.
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman–Pearson type binary solution. We add a constraint on expected return to investigate the mean-CVaR portfolio selection problem in a dynamic setting: the investor is faced with a Markowitz type of risk reward problem at the final horizon, where variance as a measure of risk is replaced by CVaR. Based on the complete market assumption, we give an analytical solution in general. The novelty of our solution is that it is no longer the Neyman–Pearson type, in which the final optimal portfolio takes only two values. Instead, in the case in which the portfolio value is required to be bounded from above, the optimal solution takes three values; while in the case in which there is no upper bound, the optimal investment portfolio does not exist, though a three-level portfolio still provides a sub-optimal solution. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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390 KiB  
Article
A Welfare Analysis of Capital Insurance
by Ekaterina Panttser and Weidong Tian
Risks 2013, 1(2), 57-80; https://doi.org/10.3390/risks1020057 - 17 Sep 2013
Cited by 3 | Viewed by 6886
Abstract
This paper presents a welfare analysis of several capital insurance programs in a rational expectation equilibrium setting. We first explicitly characterize the equilibrium of each capital insurance program. Then, we demonstrate that a capital insurance program based on aggregate loss is better than [...] Read more.
This paper presents a welfare analysis of several capital insurance programs in a rational expectation equilibrium setting. We first explicitly characterize the equilibrium of each capital insurance program. Then, we demonstrate that a capital insurance program based on aggregate loss is better than classical insurance, when big financial institutions have similar expected loss exposures. By contrast, classical insurance is more desirable when the bank’s individual risk is consistent with the expected loss in a precise way. Our analysis shows that a capital insurance program is a useful tool to hedge systemic risk from the regulatory perspective. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
205 KiB  
Article
Optimal Reinsurance: A Risk Sharing Approach
by Alejandro Balbas, Beatriz Balbas and Raquel Balbas
Risks 2013, 1(2), 45-56; https://doi.org/10.3390/risks1020045 - 5 Aug 2013
Cited by 4 | Viewed by 5919
Abstract
This paper proposes risk sharing strategies, which allow insurers to cooperate and diversify non-systemic risk. We deal with both deviation measures and coherent risk measures and provide general mathematical methods applying to optimize them all. Numerical examples are given in order to illustrate [...] Read more.
This paper proposes risk sharing strategies, which allow insurers to cooperate and diversify non-systemic risk. We deal with both deviation measures and coherent risk measures and provide general mathematical methods applying to optimize them all. Numerical examples are given in order to illustrate how efficiently the non-systemic risk can be diversified and how effective the presented mathematical tools may be. It is also illustrated how the existence of huge disasters may lead to wrong solutions of our optimal risk sharing problem, in the sense that the involved risk measure could ignore the existence of a non-null probability of "global ruin" after the design of the optimal risk sharing strategy. To overcome this caveat, one can use more conservative risk measures. The stability in the large of the optimal sharing plan guarantees that "the global ruin caveat" may be also addressed and solved with the presented methods. Full article
(This article belongs to the Special Issue Systemic Risk and Reinsurance)
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