arXiv research

Study systemic risk measures adjusted to financial markets.

Unified asymptotic treatment for VaR- and expectile-based systemic risk measures.

The paper extends static Systemic Risk Measures to a conditional setting.

Systemic risk refers to the risk that the financial system is susceptible to failures due to the characteristics of the system itself. The tremendous cost of systemic risk requires the design and implementation of tools for the efficient macroprudential regulation of financial institutions. The current paper proposes a…

We axiomatically introduce risk-consistent conditional systemic risk measures defined on multidimensional risks. This class consists of those conditional systemic risk measures which can be decomposed into a state-wise conditional aggregation and a univariate conditional risk measure. Our studies extend known results f…

The financial crisis has dramatically demonstrated that the traditional approach to apply univariate monetary risk measures to single institutions does not capture sufficiently the perilous systemic risk that is generated by the interconnectedness of the system entities and the corresponding contagion effects. This has…

Paper uses stochastic algorithms to estimate systemic risk measures.

This paper introduces a new systemic risk measure, JMES, and its associated contribution measures.

Study systemic risk measures and capital allocation rules, showing commonalities.

New risk measures for financial networks avoid external capital, reducing systemic risk.

This paper measures temperature in agent systems using volatility.

This work introduces a method to learn dynamical systems from noisy sensor measurements using multiple shooting.

We establish dual representations for systemic risk measures based on acceptance sets in a general setting. We deal with systemic risk measures of both "first allocate, then aggregate" and "first aggregate, then allocate" type. In both cases, we provide a detailed analysis of the corresponding systemic acceptance sets …

This paper reformulates systemic risk measures and finds new properties and estimators.

New approach measures systemic risk by absorbing shocks before financial systems deteriorate.

Dynamic regressor selection (DRS) systems work by selecting the most competent regressors from an ensemble to estimate the target value of a given test pattern. This competence is usually quantified using the performance of the regressors in local regions of the feature space around the test pattern. However, choosing …

In our previous paper, "A Unified Approach to Systemic Risk Measures via Acceptance Set" (\textit{Mathematical Finance, 2018}), we have introduced a general class of systemic risk measures that allow for random allocations to individual banks before aggregation of their risks. In the present paper, we prove the dual re…

Invariant measures found for contact Hamiltonian systems split into Reeb and Liouville dynamics.

Paper introduces contribution measures for systemic risk in crypto markets.

The study measures systemic risk using common and tail dependence factors.

Systemic risk is concerned with the instability of a financial system whose members are interdependent in the sense that the failure of a few institutions may trigger a chain of defaults throughout the system. Recently, several systemic risk measures have been proposed in the literature that are used to determine capit…

In this paper, we introduce the rich classes of conditional distortion (CoD) risk measures and distortion risk contribution ($Δ$CoD) measures as measures of systemic risk and analyze their properties and representations. The classes include the well-known conditional Value-at-Risk, conditional Expected Shortfall, and r…

Simplifies study of multivariate shortfall risk measures.

Formulates LGFO to measure fair ML systems using legal signals.

New risk measures assess cryptocurrency market vulnerabilities during financial distress.

Unified control theory and machine learning for safety in uncertain systems.

The paper introduces Patterson-Sullivan systems and proves their rigidity, with applications to random walks and entropy rigidity.

Global balance index measures systemic risk in financial networks.

Systemic risk measures are crucial for the stability of financial markets, yet classical formulations fail to capture the complexity of market volatility. We propose a new framework for systemic risk measurement on the variable-exponent Bochner-Lebesgue space $L^{p(\cdot)}$, where the exponent $p(\cdot)$ is a random va…

Measures time-delay embedding for noisy, sparse data.

Extends rigidity results to non-homogeneous manifolds.

The financial crisis showed the importance of measuring, allocating and regulating systemic risk. Recently, the systemic risk measures that can be decomposed into an aggregation function and a scalar measure of risk, received a lot of attention. In this framework, capital allocations are added after aggregation and can…

I show that the solution of a standard clearing model commonly used in contagion analyses for financial systems can be expressed as a specific form of a generalized Katz centrality measure under conditions that correspond to a system-wide shock. This result provides a formal explanation for earlier empirical results wh…

Study measures inequality in social-economic systems using Fokker-Planck equations and Lotka-Volterra dynamics.

This paper presents a simple model to measure the relative economic growth of economic systems. The model considers S-Shaped patterns of economic growth that, represented with a linear model, measure how an economic system grows in comparison with another one. In particular, this model introduces an approach which indi…

Paper uses deep learning for systemic risk measures.

This paper focuses on using the first curvature $κ(t)$ of trajectory to describe the stability of linear time-invariant system. We extend the results for two and three-dimensional systems [Y. Wang, H. Sun, Y. Song et al., arXiv:1808.00290] to $n$-dimensional systems. We prove that for a system $\dot{r}(t)=Ar(t)$, (i) i…

Due to the insufficient measurements in the distribution system state estimation (DSSE), full observability and redundant measurements are difficult to achieve without using the pseudo measurements. The matrix completion state estimation (MCSE) combines the matrix completion and power system model to estimate voltage b…

Introduces an artificial cyber lab to test and identify cyber resilience measures.

Study dual representations for quasiconvex systemic risk measures.

A new method extracts features and reconstructs moments in dynamical systems using information geometry.

In this article we propose a novel measure of systemic risk in the context of financial networks. To this aim, we provide a definition of systemic risk which is based on the structure, developed at different levels, of clustered neighbours around the nodes of the network. The proposed measure incorporates the generaliz…

The increasing role of recommender systems in many aspects of society makes it essential to consider how such systems may impact social good. Various modifications to recommendation algorithms have been proposed to improve their performance for specific socially relevant measures. However, previous proposals are often …

The paper proposes a new framework for accurate uncertainty representation and propagation.

The ongoing concern about systemic risk since the outburst of the global financial crisis has highlighted the need for risk measures at the level of sets of interconnected financial components, such as portfolios, institutions or members of clearing houses. The two main issues in systemic risk measurement are the compu…

AI measures financial risk using linear quantile lasso regression.

Paper proves finite BMS measure for SPR groups in higher rank Lie groups.

Measurement and management of credit concentration risk is critical for banks and relevant for micro-prudential requirements. While several methods exist for measuring credit concentration risk within institutions, the systemic effect of different institutions' exposures to the same counterparties has been less explore…