No‐arbitrage Pricing Under Systemic Risk: Accounting for Cross‐ownership

Fischer, Thomas

doi:10.1111/j.1467-9965.2012.00526.x

Cited by 51 publications

(69 citation statements)

References 28 publications

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“…Therefore, a gap has emerged between this growing body of works on interconnectedness with ex-post valuation and the vast literature on the ex-ante valuation of corporate obligations. The latter, building on the classic Merton approach (Merton, 1974), deals with the problem of ex-ante valuation in the presence of uncertainty but does not encompass interdependence between claims, with a few exceptions (Cossin and Schellhorn, 2007;Fischer, 2014;Hain and Fischer, 2015;Suzuki, 2002).…”

Section: Introductionmentioning

confidence: 99%

Network Valuation in Financial Systems

et al. 2016

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We introduce a network valuation model (hereafter NEVA) for the ex-ante valuation of claims among financial institutions connected in a network of liabilities. Similar to previous work, the new framework allows to endogenously determine the recovery rate on all claims upon the default of some institutions. In addition, it also allows to account for ex-ante uncertainty on the asset values, in particular the one arising when the valuation is carried out at some time before the maturity of the claims. The framework encompasses as special cases both the ex-post approaches of Eisenberg and Noe and its previous extensions, as well as the ex-ante approaches, in the sense that each of these models can be recovered exactly for special values of the parameters. We characterize the existence and uniqueness of the solutions of the valuation problem under general conditions on how the value of each claim depends on the equity of the counterparty. Further, we define an algorithm to carry out the network valuation and we provide sufficient conditions for convergence to the maximal solution.

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Section: Introductionmentioning

confidence: 99%

Network Valuation in Financial Systems

et al. 2016

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“…Valuation in a network context is considerably more complicated as all option values are interdependent and have to be solved in a self-consistent fashion. Correspondingly, almost no analytic results are known, and only recently, some extensions including interbank liabilities of different seniorities [30] or maturities [31] have been proposed.…”

Section: Contagion Via Valuation Adjustmentsmentioning

confidence: 99%

Systemic Risk: Fire-Walling Financial Systems Using Network-Based Approaches

Sasidevan¹,

Bertschinger²

2019

Network Theory and Agent-Based Modeling in Economics and Finance

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The latest financial crisis has painfully revealed the dangers arising from a globally interconnected financial system. Conventional approaches based on the notion of the existence of equilibrium and those which rely on statistical forecasting have seen to be inadequate to describe financial systems in any reasonable way. A more natural approach is to treat fi-nancial systems as complex networks of claims and obligations between various financial institutions present in an economy. The generic frame-work of complex networks has been successfully applied across several dis-ciplines, e.g., explaining cascading failures in power transmission systems and epidemic spreading. Here we review various network models address-ing financial contagion via direct inter-bank contracts and indirectly via overlapping portfolios of financial institutions. In particular, we discuss the implications of the "robust-yetfragile" nature of financial networks for cost-effective regulation of systemic risk.

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“…Zu den einschlägigen Arbeiten, in denen ähnliche Modelle sowie Erweiterungen des Modells von Eisenberg/Noe um Eigenkapital-Überkreuz-beteiligungen, Prioritätenklassen oder den Einbezug des Merton-Modells entwickelt wurden, gehören beispielsweise (Suzuki 2002), (Elsinger 2009) und (Elsinger et al 2013). In (Fischer 2014) vorgegeben, wobei l i j q , , den Wert der Verpflichtung von Partei i gegenüber Partei j beschreibt, welche die Priorität q besitzt. 6 Aus der Verpflichtungsmatrix L lassen sich die nominellen Gesamtverpflichtungen v L i ( ) und Forderungen a L i ( ) einer Partei i herleiten:…”

Section: 2 Netzwerkmodellunclassified

Ein Netzwerkmodell zur Systemrisikomessung in der betrieblichen Altersversorgung

Clever

Zwiesler

2015

ZVersWiss

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ZusammenfassungIn der vorliegenden Arbeit diskutieren wir das Thema Systemrisiko im Kontext von Systemen der betrieblichen Altersversorgung (bAV). Dazu wird ein Netzwerkmodell aus dem Bankensystem um zustandsabhängige Verpflichtungen erweitert, so dass sich auch bAV-Systeme einschließlich ihrer oftmals komplexen rechtlichen Beziehungen darin erfassen lassen. Anschließend wird das Modell auf das konkrete Beispiel des deutschen Pensionsfonds-Systems angewendet. Insbesondere wird diskutiert, inwiefern verschiedene Aufsichtsregeln und Solvenzkapitalanforderungen das Systemrisiko beeinflussen können.Abstract In this paper we discuss systemic risk with respect to pension systems. We adopt a network model from banking by incorporating state-dependent liabilities enabling the inclusion of complex pension structures. We apply this model to the German pension fund system and discuss how different regulatory approaches and solvency capital requirements influence the systemic risk. 332

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No‐arbitrage Pricing Under Systemic Risk: Accounting for Cross‐ownership

Cited by 51 publications

References 28 publications

Network Valuation in Financial Systems

Network Valuation in Financial Systems

Systemic Risk: Fire-Walling Financial Systems Using Network-Based Approaches

Ein Netzwerkmodell zur Systemrisikomessung in der betrieblichen Altersversorgung

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