GraphShield uses dynamic graph learning to detect and visualize financial risks.
problem Detecting and mitigating risks in financial networks.
method Enhanced Cross-Domain Information Learning, Advanced Risk Recognition, Risk Propagation Visualization.
result GraphShield effectively identifies and visualizes hidden financial risks.
New algorithm assesses credit risk in multilayer networks over time.
problem Quantifying evolving credit risk in complex, interconnected networks.
method Personalized PageRank algorithm for multilayer networks.
result Credit risk evolves and propagates through multilayer networks over time.
Network analysis improves risk assessment for surety bonds.
problem Network effects in surety bonds increase risk assessment complexity.
method Modelled contractor network as directed graph, extended Friedkin-Johnsen model with stochastic process.
result Network effects increase average risk for surety organizations.
New method identifies extreme risk propagation in financial networks.
problem Understanding extreme risk in financial networks.
method Max-linear structural equation model, hard-thresholding, Hamming distance.
result Sparse DAG for extreme risk propagation estimated.
Framework for quantifying uncertainty in dynamic processes.
problem Quantifying uncertainty in dynamic stochastic processes.
method Define dynamic uncertainty sets and dynamic robust risk measures.
result Dynamic robust risk measures are time-consistent under specific uncertainty sets.
Network models assume unrealistic idiosyncratic risk, which can be mitigated by allowing for correlated shocks.
problem Network models assume idiosyncratic risk, which can be unrealistic and lead to incorrect predictions.
method Proposed a production-based asset pricing model to account for substitutability between trade partners and correlation in supply and demand shocks.
result Assets positively exposed to average propagation of upstream and downstream shocks earn lower average risk premia.
Algorithm maximizes revenue-risk by estimating price impact kernel and optimizing control problems.
problem Maximizing revenue-risk in a risky asset liquidation with unknown price impact.
method Alternates exploration and exploitation phases, uses novel kernel estimation and stability results.
result Sublinear regret achieved with high probability.
Study examines cryptocurrency risk spillover effects before and after pandemic.
problem Analyzing risk propagation among cryptocurrencies during extreme events.
method Asymmetric breakpoint approach and network analysis.
result Cryptocurrency risk spillover effect increased during pandemic.
Study extends Gai-Kapadia framework to assess systemic risk in global equity markets.
problem Systemic risk and default cascades in global equity markets.
method Network analysis, threshold filtering, Monte Carlo simulations, tail risk assessment.
result System exhibits strong global resilience with negligible probability of large-scale failure.
As economic entities become increasingly interconnected, a shock in a financial network can provoke significant cascading failures throughout the system. To study the systemic risk of financial systems, we create a bi-partite banking network model composed of banks and bank assets and propose a cascading failure model …
This study maps systemic risks in TradFi and DeFi, highlighting their interdependence.
problem Systemic risks in traditional and decentralized finance.
method Conceptual model and comparative analysis of TradFi and DeFi.
result Systemic risks in DeFi can affect TradFi and vice versa, creating a crosstagion effect.
A growing body of studies on systemic risk in financial markets has emphasized the key importance of taking into consideration the complex interconnections among financial institutions. Much effort has been put in modeling the contagion dynamics of financial shocks, and to assess the resilience of specific financial ma…
The 2008 financial crisis revealed banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.
problem Fundamental vulnerabilities in interconnected banking systems during the 2008 financial crisis were inadequately addressed by existing frameworks.
method Developed a unified spatial-network framework using spectral analysis of network Laplacian operators combined with spatial difference-in-differences identification.
result Banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.
Optimal portfolio choice with cross-impact propagators, solving complex equations.
problem Maximizing revenue-risk in a continuous-time portfolio choice problem with cross-impact.
method Formulated as a maximization problem, solved explicitly using operator resolvents and stochastic Fredholm equations.
result Sufficient conditions for the absence of price manipulation, providing financial insights.
Proposes a new neural network architecture inspired by biology to improve learning and information flow.
problem Improving artificial neural networks to match biological neuron properties like multidirectional propagation and probabilistic modeling.
method Extends KAN approach with joint distribution neurons that can propagate values and distributions, including variance and higher-order moments.
result Proposed architecture can predict and propagate distributions, including expected values and variances.
Modeling financial systemic risk with optimal control theory for stability.
problem Analyzing and stabilizing systemic risk in interconnected financial entities.
method Developed a theoretical model using optimal control theory, including steps for synthesizing stabilizing controllers.
result The model ensures that the H∞ norms of the mappings from disturbance to output are less than a predefined constant, stabilizing the system. We present a network-based framework for simulating systemic risk that considers shock propagation in banking systems. In particular, the framework allows the modeller to reflect a top-down framework where a shock to one bank in the system affects the solvency and liquidity position of other banks, through systemic mar…
Develops a framework to assess systemic risk in the economy using bank-firm network data.
problem Measuring systemic risk in the economy using multilayer network data.
method Unified framework combining techniques to reconstruct multilayer economy structure from bank and firm balance sheets, and dynamics of shock propagation.
result Identifies systemically important firms and banks, and assesses systemic risk determinants.
Employs granular data to create a multilayer network for euro area banks, revealing distinct risk patterns.
problem Lack of comprehensive, granular data integration for systemic risk assessment in euro area banks.
method Constructs an empirically grounded multilayer network integrating various supervisory and statistical datasets, each layer representing a distinct transmission channel.
result Cross-layer heterogeneity in connectivity and centrality reveals economically relevant structure and misidentifies systemically important institutions.
Study finds a phase transition in flash crashes involving large and liquid stocks.
problem Systemic risk and propagation of shocks in high frequency trading.
method In-depth investigation of co-crashes in high frequency trading.
result Large co-crashes involve mostly illiquid stocks, while small crashes involve a mix of liquid and illiquid stocks.
This paper develops a new framework to assess crypto portfolio risk using simulation methods.
problem Traditional financial risk models fail to capture crypto market characteristics like volatility and contagion.
method The framework integrates four components: volatility stress testing, hedging, contagion modeling, and Monte Carlo simulation.
result The framework robustly assesses crypto portfolio risk and is validated with real data.
Optimal liquidation strategy with price impact and signal exploitation.
problem Maximizing revenue-risk in a market with transient and temporary price impact.
method Infinite dimensional stochastic control approach, backward stochastic differential equation, operator-valued Riccati equation.
result Explicit expression for the optimal trading strategy.
We contribute to the understanding of how systemic risk arises in a network of credit-interlinked agents. Motivated by empirical studies we formulate a network model which, despite its simplicity, depicts the nature of interbank markets better than a homogeneous model. The components of a vector Ornstein-Uhlenbeck proc…
Aggregate and systemic risk in complex systems are emergent phenomena depending on two properties: the idiosyncratic risks of the elements and the topology of the network of interactions among them. While a significant attention has been given to aggregate risk assessment and risk propagation once the above two propert…
Attack graphs provide compact representations of the attack paths that an attacker can follow to compromise network resources by analysing network vulnerabilities and topology. These representations are a powerful tool for security risk assessment. Bayesian inference on attack graphs enables the estimation of the risk …
The purpose of this paper is to advance the understanding of the conditions that give rise to flash crash contagion, particularly with respect to overlapping asset portfolio crowding. To this end, we designed, implemented, and assessed a hybrid micro-macro agent-based model, where price impact arises endogenously throu…
The paper validates a centrality measure for financial networks during financial distress.
problem Systemic risk and shock propagation in financial networks.
method Statistical validation method for network centrality measures.
result The proposed centrality measure increases significantly during financial distress.
This paper uses multivariate probability models to assess financial system risks.
problem Assessing systemic risk in financial systems.
method Computes multivariate conditional probability distributions for elliptical distributions, focusing on Student-t and Normal models.
result Proposes measures of stress impact and systemic risk.
This study analyzes how carbon pricing affects credit risk measures in a portfolio.
problem Impact of carbon pricing on credit risk measures in a portfolio.
method Adapted stochastic multisectoral model to account for GHG emissions costs and carbon prices.
result Carbon pricing distorts firm value distributions, increases banking fees, and reduces profitability.
Unified deep learning from noisy crowds using BP and MF.
problem Inference and learning from noisy crowdsourced data.
method Neural-powered Bayesian framework with deepMF and deepBP.
result deepBP is more robust against wrong priors and feature overfitting.
Social media are nowadays one of the main news sources for millions of people around the globe due to their low cost, easy access and rapid dissemination. This however comes at the cost of dubious trustworthiness and significant risk of exposure to 'fake news', intentionally written to mislead the readers. Automaticall…
Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. Here we apply survival theory to develop general additive and multiplicative risk models under which the network inference…
Study ruin probabilities in risk processes on stochastic networks.
problem Ruin probabilities in risk processes on stochastic networks.
method Classification of agents by types, Poisson process for loss propagation, explicit ruin probabilities for infinite network size.
result Explicit ruin probabilities for agents of any type in infinite network size.
This paper optimizes cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.
problem Optimizing cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.
method Combining strategic behavior of players with contagion dynamics, a method is extended to determine optimal resource allocation based on simple network metrics weighted by risk profiles.
result The asymmetry between attacker and defender valuations drives optimal attack and defense strategies, shaping system resilience.
This research develops a new model for cyber risk and insurance pricing.
problem Accurate calculation of aggregate losses in cyber insurance pricing.
method A path-based k-generation risk contagion model in a tree-shaped network structure.
result Explicit expressions for mean and variance of local loss on a single path.
Financial markets are exposed to systemic risk, the risk that a substantial fraction of the system ceases to function and collapses. Systemic risk can propagate through different mechanisms and channels of contagion. One important form of financial contagion arises from indirect interconnections between financial insti…
New method solves supercooled Stefan problem, proving minimal solutions are physical.
problem Evolution of solid-liquid boundary in substances below freezing point.
method Construct solutions through McKean-Vlasov equation, proving tightness and propagation of chaos.
result Minimal solutions of McKean-Vlasov equation are physical under integrable initial conditions.
A time-varying network reveals community structure in cryptocurrencies.
problem Investing in cryptocurrencies from different communities can diversify risk.
method Dynamic covariate-assisted spectral clustering method.
result Investors can earn 1.08% daily return by diversifying across communities.
Multi-fidelity methods are prominently used when cheaply-obtained, but possibly biased and noisy, observations must be effectively combined with limited or expensive true data in order to construct reliable models. This arises in both fundamental machine learning procedures such as Bayesian optimization, as well as mor…
The global financial system can be represented as a large complex network in which banks, hedge funds and other financial institutions are interconnected to each other through visible and invisible financial linkages. Recently, a lot of attention has been paid to the understanding of the mechanisms that can lead to a b…
Develops neural network framework for risk-reward optimization problems.
problem Multi-period risk-reward optimization with constrained policies.
method Neural network framework with two coupled feedforward networks, parametrizing two-step policies.
result Empirical optimum converges to true optimal value as network capacity and training size increase.
Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation and market segmentation. To investigate these effects, we build a time-varying network for cryptocurrencies, based on the evolution of return cross-predictability and technological similarities. We develop a …
TRP uses tree-based approach for market-neutral portfolios.
problem Creating non-binary, market-neutral portfolios with signed signals.
method Tree-based portfolio construction with minimum-spanning-tree and sector-anchored variants.
result TRP outperforms HRP in preserving signal direction and managing exposures.
Modeling supply chain disruptions from climate hazards with adaptive firms.
problem Systemic physical climate risk in supply chains.
method Agent-based model integrating geospatial hazards and firm adaptation.
result Firms' adaptive strategies reduce disruption by 48%.
This paper uses graph neural networks to predict SME default risk using transaction and ownership networks.
problem Predicting credit risk for SMEs facing limited financial histories and collateral constraints.
method Graph Neural Networks applied to multilayer network data of SME transactions and ownership.
result Combining network data with traditional data improves credit scoring and models contagion risk.
We consider a heat kernel approach for the development of stochastic pricing kernels. The kernels are constructed by positive propagators, which are driven by time-inhomogeneous Markov processes. We multiply such a propagator with a positive, time-dependent and decreasing weight function, and integrate the product over…
Bayesian network framework assesses urban risks across multiple domains.
problem Complex interdependencies in urban systems.
method Bayesian Belief Networks (BBNs) with DAGs, Hill-Climbing search, BIC, K2 scoring, synthetic data, SMOTE.
result Identifies key risk factors and quantifies likelihood of cascading failures.
We have conducted an agent-based simulation of chain bankruptcy. The propagation of credit risk on a network, i.e., chain bankruptcy, is the key to nderstanding largesized bankruptcies. In our model, decrease of revenue by the loss of accounts payable is modeled by an interaction term, and bankruptcy is defined as a ca…