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- W2898889573 abstract "The financial crisis of 2008 highlighted the need for better regulation mechanismsfor the stabilization of financial systems. The innovations in financialproducts and the evolution of financial market technologies and operationsobserved in the last decades do not only offer new opportunities but also implysystemic risks. They contributed to the establishment of interconnectedfinancial systems in which the failure of certain single financial institutions(the so-called systematically important financial institutions: SIFI) can spreadthrough contagion effects, thus causing the failures of other financial institutionsand threatening the stability of a financial system.The regulatory authorities reacted to this problem by designing and implementingvarious new risk management concepts and tasks, such as 1) the estimationof the potential financial loss suffered by the financial system if a givenfinancial institution defaults, 2) the identification of SIFIs 3) the calculation ofindividual bank’s contribution to resolution funds and 4) the elaboration andthe performance of bail-in-operations. These tasks necessitate the developmentof financial risk measures that are based not only on individual losses in isolation,as are standard risk measures such as Value-at-Risk (VaR), but alsoconsider loss dependency. One of the main tools proposed for this purpose isthe CoVaR-method of Brunnermeier and Adrian [2011]. The CoVaR-methodis based on the statistic CoVaR, which is defined as the VaR of one financialsystem conditional on the state of a given financial institution.The main contribution of this thesis is the development of methods for thecomputation of CoVaR in a wide variety of stochastic settings. We derive,using copula theory, a general formula for CoVaR, which takes into accountall information on the involved distribution. This allows us to consider notonly the normal but also the extreme part of the assumed distributions as wellas different types of dependency structure. We make some illustrative applicationsand related analysis. Also, using the theory of elliptical distributionswe derive an expression of CoVaR that is more accessible to financial practitioners.Both approaches allow us to consider not only Gaussian- but alsonon-Gaussian distribution. Furthermore, we highlight several inconsistenciesin the CoVaR-method and suggest alternative approaches." @default.
- W2898889573 created "2018-11-09" @default.
- W2898889573 creator A5033231426 @default.
- W2898889573 date "2018-01-22" @default.
- W2898889573 modified "2023-09-26" @default.
- W2898889573 title "Modeling Systemic Risk Contribution Using Copula" @default.
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- W2898889573 hasPublicationYear "2018" @default.
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