Exploring Agent-Based Methods for the Analysis of Payment Systems: A Crisis Model for StarLogo TNG

Abstract

This paper presents an exploratory agent-based model of a real time gross settlement (RTGS) payment system. Banks are represented as agents who exchange payment requests, which are then settled according to a set of simple rules. The model features the main elements of a real-life system, including a central bank acting as liquidity provider, and a simplified money market. A simulation exercise using synthetic data of BI-REL (the Italian RTGS) predicts the macroscopic impact of a disruptive event on the flow of interbank payments. In our reducedscale system, three hypothetical distinct phases emerge after the disruptive event: 1) a liquidity sink effect is generated and the participants' liquidity expectations turn out to be excessive; 2) an illusory thickening of the money market follows, along with increased payment delays; and, finally 3) defaulted obligations dramatically rise. The banks cannot staunch the losses accruing on defaults, even after they become fully aware of the critical event, and a scenario emerges in which it might be necessary for the central bank to step in as liquidity provider.

The interaction between monetary and macroprudential policy: should central banks ‘lean against the wind’ to foster macro-financial stability?

“…At the heart of the UK reserve averaging scheme 12 is a real-time gross settlement (RTGS) system [Kelsey and Rickenbach (2014); Dent and Dison (2012); Nakajima (2011); Arciero et al (2009)] which enables the CB to provide liquidity insurance to commercial banks via operational standing facilities (OSF) and, thus, to meet its lender of last resort (LOLR) function. This means that the settlement of a transaction between real sector agents takes place as soon as a payment is submitted into the system (real-time) and that payments can only be settled if the paying bank has enough liquidity to deliver the full amount in central bank money (gross settlement, i.e.…”

Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo

“…Arciero and co-authors present a model with a money market [9] which, after a critical event, either blocks or limits the activity of the bank. In their model, banks are perfectly informed on all payment requests.…”

Agent-based Models of the Economy

“…2 A presentation of the model and of its results, goals, and perspectives is in Arciero et al (2014); here we concentrate on the construction of the agent-based frame. 3 The delays in payments among banks -due to speculative reasons, despite representing a form of unfair behavior if the liquidity exists -can generate liquidity shortages that in the presence of unexpected negative operational or financial shocks can produce huge domino effects (Arciero et al, 2009). To understand this kind of problem, we adopt agent-based simulation as a sort of magnifying glass.…”