Payment Systems ABM Model
How do banks' individual liquidity management strategies, payment queuing decisions, and bilateral netting behavior generate systemic gridlock risk, cascading settlement failures, and the need for central bank intraday liquidity provision in large-value payment systems?
Agent-based models · Sources
Payment Systems ABM sources, papers, and evidence trail
Primary papers, model variants, source notes, and review signals behind the Payment Systems ABM page.
References
Reference sources
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[S1] Reference
Galbiati and Soramaki (2011) -- stylized agent-based payment system with learning banks choosing how much liquidity to post (not a TARGET2 calibration)
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[S2] Reference
Arciero et al. (2009) -- multi-agent simulation of Italian payment system evaluating liquidity-saving mechanisms
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[S3] Reference
Beyeler et al. (2007) -- congestion and cascade dynamics in Fedwire-calibrated payment flows
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[S4] Reference
Diehl (2013) -- comprehensive simulation framework for RTGS, DNS, and hybrid payment system design
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[S5] Reference
Bech and Garratt (2003) -- two-player intraday liquidity management GAME (theory, not Fedwire data) supplying the strategic structure behind ABM behavioral rules
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[S6] Reference
Cont, Moussa, and Santos (2013) -- systemic risk from interbank CREDIT-exposure networks using Brazilian supervisory data; a solvency-contagion study, not a payment/clearing model
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[S7] Reference
Paddrik et al. (2020) -- payment network resilience under multi-system operational disruptions
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