Author name cluster

Jinyun Tong

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

6 papers

2 author rows

AAMAS Conference 2026 Conference Paper

Capital Provision to Reduce Liquidity Defaults and the Role of Central Banks

Jinyun Tong
Bart de Keijzer
Carmine Ventre

We study to what extent the interbank market and central bank intervention can reduce funding liquidity defaults in banking networks. We build a multi-period agent-based model to simulate the banking network and interbank market for the long term. Based on this model, we define a strategic game in which each systemically important bank faces a decision of whether to lend and to which type of distressed bank to lend. We conduct an empirical analysis based on datasets published by the European Banking Authority. We compute the equilibria of the induced game using Empirical Game-Theoretic Analysis with different equilibrium solvers and analyse bank behaviour at different equilibria. The experimental results show that in the non-cooperative scenario, if all demand banks are solvent, central bank lending can significantly reduce liquidity defaults. Our results also suggest that the central bank can indirectly intervene in the interbank market by coordinating banks through recommendations, thus increasing interbank lending and reducing liquidity defaults, even without central bank lending.

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AAMAS Conference 2026 Conference Paper

Interbank Lending Games

Jinyun Tong
Bart de Keijzer
Haoxiang Wang
Carmine Ventre

We define and study a lending game to model the interbank money market, in which lending banks strategically allocate their cash to borrowing banks. The interest rate offered by each borrowing bank is within the interest rate corridor set by the central bank and ultimately depends on the demand and the supply of cash in the interbank market. Lending banks naturally aim to maximise the income coming from the interest repayments. In its purest form, this is an infinite-strategy game that we show to be an exact potential game which has a unique pure strategy Nash equilibrium. We then define and solve a constrained optimisation problem and propose a strongly polynomial-time algorithm to compute this Nash equilibrium. We also study some variants of best-response dynamics of this lending game, showing that they converge to the Nash equilibrium in both discrete and continuous-time scenarios.

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AAMAS Conference 2025 Conference Paper

Agent-based Modeling and Simulation of Ambiguity in Catastrophe Insurance Markets

Yu Bi
Lingxiao Zhao
Jinyun Tong
Zhe Feng
Carmine Ventre

Pricing covers for catastrophes is challenging for insurers due to uncertainty in loss probabilities. This paper addresses this so-called ambiguity problem in competitive catastrophe insurance markets through three key approaches. First, it introduces ambiguity in premium pricing and capital holdings. Second, it develops an Agentbased Model simulator to mimic general insurance markets and the Lloyd’s market. Third, it applies Empirical Game-Theoretical Analysis to explore insurers’ ambiguity preferences in different markets. The study evaluates the effects of ambiguity by analyzing their impact on individual companies, differences between small and large companies, and overall market performance. Simulation results reveal that the simulator effectively captures underwriting cycles and insurers’ strategic shifts following catastrophes. In markets with equally sized insurers, competition mitigates the negative effects of ambiguity by stabilizing premiums and increasing the number of underwritten risks. In markets with varying-sized insurers, large insurers gain market power while small insurers adopt aggressive ambiguity strategies to compete. In contrast, Lloyd’s lead-follow mechanism encourages conservative ambiguity strategies and reduces bankruptcy.

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AAMAS Conference 2024 Conference Paper

Reducing Systemic Risk in Financial Networks through Donations

Jinyun Tong
Bart de Keijzer
Carmine Ventre

We examine the extent to which rescue strategies within a banking system can reduce systemic risk. We focus on donations from solvent banks to banks in distress, which can in principle reduce losses and prevent default cascades. We build an agent-based model to simulate the ensuing strategic game on a randomly generated financial network, where nodes represent banks and edges represent interbank liabilities. Each bank independently decides whether to rescue (and whom) to maximise their payoffs. We analyse the rescue strategies adopted by the banks at equilibrium, using empirical game-theoretic analysis. Our results show that donations can indeed reduce systemic risk when the equilibrium strategy profile is adopted. Individual donations can benefit multiple banks in the network. Our results also indicate that lower default costs and small-variance liabilities tend to decrease the incentives to donate. We furthermore examine the impact of the banks’ rationality on the effects of rescue, finding that banks behaving rationally use their funds for rescues more efficiently than banks that behave irrationally.

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ECAI Conference 2024 Conference Paper

Reducing Systemic Risk in Financial Networks through Donations

Jinyun Tong
Bart de Keijzer
Carmine Ventre

We examine the extent to which rescue strategies within a banking system can reduce systemic risk. We focus on donations from solvent banks to banks in distress, which can in principle reduce losses and prevent default cascades. We build an agent-based model to simulate the ensuing strategic game on a randomly generated financial network, where nodes represent banks and edges represent inter-bank liabilities. Each bank independently decides whether to rescue (and whom) to maximise their payoffs. We analyse the rescue strategies adopted by the banks at equilibrium, using empirical game-theoretic analysis. Our results show that donations can indeed reduce systemic risk when the equilibrium strategy profile is adopted. Individual donations can benefit multiple banks in the network. Our results also indicate that lower default costs and small-variance liabilities tend to decrease the incentives to donate. We furthermore examine the impact of the banks’ rationality on the effects of rescue, finding that banks behaving rationally use their funds for rescues more efficiently than banks that behave irrationally.

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ECAI Conference 2024 Conference Paper

Selfishly Cancelling Debts Can Reduce Systemic Risk

Jinyun Tong
Bart de Keijzer
Carmine Ventre

The exposure of banks to systemic risk in financial networks usually requires large bailouts of taxpayer money with long-lasting and damaging societal consequences. We examine whether the banking network can reduce systemic risk from within by selfishly cancelling the debts of banks in distress. This operation can in principle reduce losses and prevent default cascades. We define an abstract model to simulate the ensuing strategic game on randomly generated financial networks, where each systemically important bank independently decides how likely it is to cancel some debts of insolvent banks. We compute the equilibrium of the induced empirical game with the empirical game-theoretic analysis and analyse its efficiency by measuring the price of anarchy. Our results show that selfish debt cancellation can reduce systemic risk when adopting the equilibrium strategy profile. However, our results also indicate that the efficiency of the equilibrium can be low and relatively few banks cancel debts at equilibrium, and we explain the reason for this through analysis of the banks’ incentives and game dynamics.

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