"Shock diffusion in large regular networks: the role of transitive cycles"
(with Noemí Navarro)
This paper studies how the presence of transitive cycles in the network affects the extent of financial contagion. In a regular networks where the same pattern of links repeats for each node, we allow an external shock to propagate losses through the system of linkages. The extent of contagion (contagiousness) of the network is measured by the limit of the losses when the initial shock is diffused into an infinitely large network. This measure indicates how a network structure may or may not facilitate shock diffusion, independently to other external factors. Our analysis highlights two main results. First, contagiousness decreases as the length of the minimal transitive cycle increases, keeping the degree of connectivity constant. Second, the extent of contagion is non-monotonic as degrees of connectivity increases. Our results provide new insights to better understand systemic risk and could be used to build complementary indicators for financial regulation.
"Bank runs, fast and slow: from behaviors to dynamics"
This paper studies how bank runs occur, providing detailed dynamics on the emergence and trajectories of runs. While existing models mainly regard runs as symmetric equilibria in simultaneous games, the present paper considers continuous withdrawals that arise from a dynamic system. Depositors make decisions based on (i) their types, (ii) their private information on total withdrawal, and (iii) the observed actions of others within a network. Using both analytical and computational methods, this paper makes two main contributions. First, the model can capture both the speed and abruptness of runs, showing two distinct dynamic patterns: slow runs build up progressively vs. sudden runs occur abruptly without visible signs. Second, the model establishes empirically testable links between behavioral factors and the dynamics of runs. These results might be useful to predict large panic episodes.
This paper models systemic events as dynamic cascades of actions, providing a complementary view to the coordination-game framework. The aim is to better understand how bank runs emerge and develop in continuous time, without imposing an exogenous sequence of actions. Agents employ a switching strategy that combines strategic actions and heuristics to make decisions. When a fraction of random agents withdraw, under the right conditions, some depositors withdraw preemptively in response, increasing the probability that other depositors will withdraw subsequently. As the main result, the paper provides explicit computations of the tipping point, i.e. when the panic bursts out, to determine the time windows for interventions.
Works in progress
"Systemic events: forecasting and predictability"
"Assessing tail risk estimation by synthetic data"
Data science in finance (grad)
Machine Learning (grad)
Machine Learning in Finance (Msc. thesis)
Computational Modeling (grad)
Microeconomic Principles (undergrad)
Macroeconomics Intermediate (undergrad)
Programming & Database (undergrad)
Ph.D. in Financial Economics
GREThA, CNRS - University of Bordeaux
M.Sc. in Financial Risk Engineering
University of Bordeaux
B.A. in Economics
University Of California San Diego University of Bordeaux