A computational model of bilateral credit limits in payment systems and other financial market infrastructures

Abstract

This paper provides the first steps towards a theoretical and structural modelling framework through which optimal decision making in financial market infrastructures such as payments clearing and settlement systems can be assessed from a market microstructure perspective. In particular, the paper focuses on the application of agent-based computational economics and stochastic games in modelling the bilateral credit limit establishing behaviour of Participants in loss sharing arrangements within financial market infrastructures such as the Canadian Large Value Payments System (LVTS). With specific focus on the LVTS, the paper presents a structural model where the payments system represents a market in which bilateral credit limits are the pricing mechanisms for intraday liquidity provisioning and the credit risk arising from the loss sharing arrangement. The data-driven stochastic game framework further illustrates how payments data, in conjunction with other financial market and credit data, can be used to assess emergent macroscopic outcomes in clearing and settlement systems from the underpinning interactions of autonomous decision making agents. The paper speaks to potential policy issues such as the effectiveness of policy levers such as the System-Wide Percentage, regulatory concerns around procyclicality and free-riding arising from the market microstructure behaviours, and design of the System.