86 research outputs found
Entangling credit and funding shocks in interbank markets
Credit and liquidity risks represent main channels of financial contagion for
interbank lending markets. On one hand, banks face potential losses whenever
their counterparties are under distress and thus unable to fulfill their
obligations. On the other hand, solvency constraints may force banks to recover
lost fundings by selling their illiquid assets, resulting in effective losses
in the presence of fire sales - that is, when funding shortcomings are
widespread over the market. Because of the complex structure of the network of
interbank exposures, these losses reverberate among banks and eventually get
amplified, with potentially catastrophic consequences for the whole financial
system. Building on Debt Rank [Battiston et al., 2012], in this work we define
a systemic risk metric that estimates the potential amplification of losses in
interbank markets accounting for both credit and liquidity contagion channels:
the Debt-Solvency Rank. We implement this framework on a dataset of 183
European banks that were publicly traded between 2004 and 2013, showing indeed
that liquidity spillovers substantially increase systemic risk, and thus cannot
be neglected in stress-test scenarios. We also provide additional evidence that
the interbank market was extremely fragile up to the 2008 financial crisis,
becoming slightly more robust only afterwards
A Declarative Validator for GSOS Languages
Rule formats can quickly establish meta-theoretic properties of process
algebras. It is then desirable to identify domain-specific languages (DSLs)
that can easily express rule formats. In prior work, we have developed
Lang-n-Change, a DSL that includes convenient features for browsing language
definitions and retrieving information from them. In this paper, we use
Lang-n-Change to write a validator for the GSOS rule format, and we augment
Lang-n-Change with suitable macros on our way to do so. Our GSOS validator is
concise, and amounts to a few lines of code. We have used it to validate
several concurrency operators as adhering to the GSOS format. Moreover, our
code expresses the restrictions of the format declaratively.Comment: In Proceedings PLACES 2023, arXiv:2304.0543
True scale-free networks hidden by finite size effects
We analyze about two hundred naturally occurring networks with distinct
dynamical origins to formally test whether the commonly assumed hypothesis of
an underlying scale-free structure is generally viable. This has recently been
questioned on the basis of statistical testing of the validity of power law
distributions of network degrees by contrasting real data. Specifically, we
analyze by finite-size scaling analysis the datasets of real networks to check
whether purported departures from the power law behavior are due to the
finiteness of the sample size. In this case, power laws would be recovered in
the case of progressively larger cutoffs induced by the size of the sample. We
find that a large number of the networks studied follow a finite size scaling
hypothesis without any self-tuning. This is the case of biological protein
interaction networks, technological computer and hyperlink networks, and
informational networks in general. Marked deviations appear in other cases,
especially infrastructure and transportation but also social networks. We
conclude that underlying scale invariance properties of many naturally
occurring networks are extant features often clouded by finite-size effects due
to the nature of the sample data
Systemic liquidity contagion in the European interbank market
Systemic liquidity risk, defined by the International Monetary Fund as "the risk of simultaneous liquidity difficulties at multiple financial institutions," is a key topic in financial stability studies and macroprudential policy-making. In this context, the complex web of interconnections of the interbank market plays the crucial role of allowing funding liquidity shortages to propagate between financial institutions. Here, we introduce a simple yet effective model of the interbank market in which liquidity shortages propagate through an epidemic-like contagion mechanism on the network of interbank loans. The model is defined by using aggregate balance sheet information of European banks, and it exploits country and bank-specific risk features to account for the heterogeneity of financial institutions. Moreover, in order to obtain the European-wide topology of the interbank network, we define a block reconstruction method based on the exchange flows between the various countries. We show that the proposed contagion model is able to estimate systemic liquidity risk across different years and countries. Results suggest that our effective contagion approach can be successfully used as a viable alternative to more realistic but complicated models, which not only require more specific balance sheet variables with high time resolution but also need assumptions on how banks respond to liquidity shocks
Systemic liquidity contagion in the European interbank market
Systemic liquidity risk, defined by the International Monetary Fund as “the risk of simultaneous liquidity difficulties at multiple financial institutions,” is a key topic in financial stability studies and macroprudential policy-making. In this context, the complex web of interconnections of the interbank market plays the crucial role of allowing funding liquidity shortages to propagate between financial institutions. Here, we introduce a simple yet effective model of the interbank market in which liquidity shortages propagate through an epidemic-like contagion mechanism on the network of interbank loans. The model is defined by using aggregate balance sheet information of European banks, and it exploits country and bank-specific risk features to account for the heterogeneity of financial institutions. Moreover, in order to obtain the European- wide topology of the interbank network, we define a block reconstruction method based on the exchange flows between the various countries. We show that the proposed contagion model is able to estimate systemic liquidity risk across different years and countries. Results suggest that our effective contagion approach can be successfully used as a viable alternative to more realistic but complicated models, which not only require more specific balance sheet variables with high time resolution but also need assumptions on how banks respond to liquidity shocks
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