This paper uses reinforcement learning (RL) to approximate the policy rules of banks participating in a high-value payments system (HVPS). The objective of the RL agents is to learn a policy function for the choice of amount of liquidity provided to the system at the beginning of the day....

This paper uses reinforcement learning (RL) to approximate the policy rules of banks participating in a high-value payments system. The objective of the agents is to learn a policy function for the choice of amount of liquidity provided to the system at the beginning of the day. Individual...

We present a policy framework for electronic money and payments. The framework poses a set of positive questions related to the areas of responsibility of central banks: payments systems, monetary policy and financial stability. The questions are posed to four broad forms of e-money: privately...

A well-functioning monetary system is characterized by public and private forms of money that exchange at par as value flows freely between them. This is essential for efficient transacting and contracting in a market economy. A relevant retail public money - whether in the form of cash, a...

This paper presents simulation results for Canada's new large-value payments system: Lynx. We simulate the settlement process of Lynx using a large sample of payments observed in the current system (LVTS), taking the initial level of liquidity as given. We calculate the resulting liquidity...

Should a central bank take over the provision of e-money, a circulable electronic liability? We discuss how e-money technology changes the tradeoff between public and private provision, and the tradeoff between e-money and a central bank's existing liabilities like bank notes and reserves. The...

Digital currencies store balances in anonymous electronic addresses. We analyze the tradeoffs between the safety and convenience of aggregating balances in addresses, electronic wallets and banks. In our model, agents balance the risk of theft of a large account with the cost to safeguarding a...

This paper uses reinforcement learning (RL) to approximate the policy rules of banks participating in a high-value payments system. The objective of the agents is to learn a policy function for the choice of amount of liquidity provided to the system at the beginning of the day. Individual...