Optimal Algorithmic Monetary Policy

TL;DR

This paper proposes a model to optimize rule-based algorithmic stablecoins, analyzing trade-offs between price stability and supply, with implications for private stablecoins and CBDC design.

Contribution

It introduces a model for optimizing algorithmic stablecoin rules and studies the effects of various design features on stability and policy outcomes.

Findings

Trade-offs between price stability and supply stability are quantifiable.

Design features significantly impact stablecoin performance.

Implications for private sector stablecoins and CBDC implementations are discussed.

Abstract

Centralized monetary policy, leading to persistent inflation, is often inconsistent, untrustworthy, and unpredictable. Algorithmic stablecoins enabled by blockchain technology are promising in solving this problem. Algorithmic stablecoins utilize a monetary policy that is entirely rule-based. However, there is little understanding of how to optimize the rule. We propose a model that trade-off the price for supply stability. We further study the comparative statics by varying several design features. Finally, we discuss the empirical implications for designing stablecoins by the private sector and Central Bank Digital Currency (CBDC) by the public sector.