The next generation of digital currencies: in search of stability. Bruegel Policy Contribution Issue #15 December 2019

Four major developments have challenged the status quo and reopened the debate on the forms that money will take in the future: 1) use of cash as a medium of exchange has declined; 2) distributed ledger technology (DLT) has led to the emergence of thousands of digital cryptocurrencies; 3) some global tech giants are planning to provide private digital currencies to their billions of users in the form of stablecoins; and 4) in turn, public authorities are thinking about providing their own digital currencies to the general public. • These developments raise questions about the implications for financial stability, the transmission of monetary policy and financial intermediation. This Policy Contribution focuses on the consequences stablecoins and central bank digital currencies could have. • Stablecoins, such as Facebook’s Libra, differ from earlier generations of cryptocurrencies in three fundamental ways. First, they would start with large networks of users and global accessibility, two pivotal features for the critical uptake of a new currency. Second, given the current limitations of DLT, including in terms of energy efficiency, new stablecoins would rely on (more) centralised systems to validate transactions. Third, stablecoins would focus particularly on reducing the volatility in the value of the new currency. • These new features of stablecoins attempt to correct some of the critical deficiencies identified in first-generation cryptocurrencies, which meant they did not acquire the main functions of money. However, new stablecoins raise other questions and potentially create new problems. One issue could arise from the more centralised (permissioned) validation system, which could lead to collusion problems. Another issue could arise from the reserve system that is supposed to ensure the stability of stablecoins, such as Libra, which could be incompatible with the profit maximisation behaviour of a private issuer. • Facebook’s Libra plan has been a wake-up call to central banks and governments which, afraid of losing their monetary sovereignty, have renewed their interest in central bank digital currencies (CBDCs) as a potential solution. CBDCs could make private digital currencies less attractive and slow down their adoption. • But there are other reasons to give the general public access to central bank liabilities. One important reason to provide CBDCs to citizens is that if cash disappears, citizens will lose direct access to sovereign money. Another benefit of the introduction of CBDCs is that monetary policy could be strengthened by transmitting it directly to the general public. • However, the introduction of CBDCs could also be disruptive and create risks. In particular, CBDCs could have major consequences for financial intermediation. These risks would have to be evaluated by policymakers before any decisions are taken. • If CBDCs are introduced, central banks would have to carefully calibrate their properties to minimise these risks. But, eventually, if these risks – and in particular the risk of structural financial disintermediation – do materialise, central banks would have various instruments to counter the

A Smart Contract Oracle for Approximating Real-World, Real Number Values

A key challenge of smart contract systems is the fact that many useful contracts require access to information that does not natively live on the blockchain. While miners can verify the value of a hash or the validity of a digital signature, they cannot determine who won an election, whether there is a flood in Paris, or even what is the price of ether in US dollars, even though this information might be necessary to execute prediction market, insurance, or financial contracts respectively. A number of promising projects and research developments have provided a better understanding of how one might construct a decentralized, binary oracle - namely an oracle that can respond by one of two possibilities, typically "yes" or "no", even while not requiring the interaction of a trusted third party. In this work, we extend these ideas to construct a general-purpose, decentralized oracle that can estimate the value of a real-world quantity that is in a dense totally ordered set, such as R. In particular, this proposal can be used to estimate real number valued quantities, such as required for a price oracle. We will establish a number of desirable properties about this proposal. Particularly, we will see that the precision of the output is tunable to users\u27 needs

CONFIDENCE MATTERS: A SIMULATION-BASED STABILITY ANALYSIS OF ALGORITHMIC STABLECOINS

The crash of various stablecoins led to continuous adjustments of their design, most recently by backing algorithmic stablecoins with cryptocurrency pools. However, as this seems to be more of a trial-and- error process, the aim of this work is to support design decisions on their peg stability mechanism by an agent-based simulation model as a base to forecast the probability of a stablecoin run dependent on market participants’ confidence levels. Our model is tailored to the algorithmic stablecoin USDD which is i.a. pegged to the Fiat-backed stablecoin USDT and hence to the USD. As main result of our numerical study, stability depends on the price and volatility assessment of market participants and a stablecoin run can’t be prevented for sure. Methodologically, this work belongs to design science research, even though empirical market data is used to calibrate the simulation model, which can be used as base for design recommendations

The Law of Algorithmic Stablecoins in the EU

Algorithmic stablecoins are a specific subset of stablecoins employing algorithmic adjustments of supply and demand as the key stabilization mechanism. In the pursuit towards a fully decentralised means of payment, detached from collateral and solely stabilised by smart contracts and algorithms, algorithmic stablecoins pose unique risks and challenges due to their complex construction. This contribution explores the approach that is currently taken by regulators through exposing the unique risks posed by algorithmic stablecoins and arguing that these risks require a supplementary regulatory approach alongside existing proposals for regulation. We justify this by showing the complexity and diversity of fully algorithmic protocols and reveal where the dangers of these protocols originate. The article reviews the European Union’s Markets in Crypto-Assets Regulation (MiCAR) and determines its limited applicability to algorithmic stablecoins through general provision and crypto asset service providers. It briefly considers an international comparison by exploring different regulatory proposals from outside the EU with the aim to draw lessons to better assess MiCAR effectiveness. We conclude that MiCAR, despite being the most advanced and encompassing legislation in the area of crypto activities, does not target the specific risks of algorithmic stablecoins. Moreover, it creates a complex and ambiguous system with regards to the provisions applicable to algorithmic stablecoins and puts forward rules that are difficult to adapt or update via secondary legislation leaving room for further exploration of the regulatory framework to ensure safety and stability

What Drives the (In)stability of a Stablecoin?

In May 2022, an apparent speculative attack, followed by market panic, led to the precipitous downfall of UST, one of the most popular stablecoins at that time. However, UST is not the only stablecoin to have been depegged in the past. Designing resilient and long-term stable coins, therefore, appears to present a hard challenge. To further scrutinize existing stablecoin designs and ultimately lead to more robust systems, we need to understand where volatility emerges. Our work provides a game-theoretical model aiming to help identify why stablecoins suffer from a depeg. This game-theoretical model reveals that stablecoins have different price equilibria depending on the coin’s architecture and mechanism to minimize volatility. Moreover, our theory is supported by extensive empirical data, spanning 1 year. To that end, we collect daily prices for 22 stablecoins and on-chain data from five blockchains including the Ethereum and the Terra blockchain

What Drives the (In)stability of a Stablecoin?

In May 2022, an apparent speculative attack, followed by market panic, led to the precipitous downfall of UST, one of the most popular stablecoins at that time. However, UST is not the only stablecoin to have been depegged in the past. Designing resilient and long-term stable coins, therefore, appears to present a hard challenge. To further scrutinize existing stablecoin designs and ultimately lead to more robust systems, we need to understand where volatility emerges. Our work provides a game-theoretical model aiming to help identify why stablecoins suffer from a depeg. This game-theoretical model reveals that stablecoins have different price equilibria depending on the coin's architecture and mechanism to minimize volatility. Moreover, our theory is supported by extensive empirical data, spanning $1$ year. To that end, we collect daily prices for 22 stablecoins and on-chain data from five blockchains including the Ethereum and the Terra blockchain

Stablecoins 2.0: Economic Foundations and Risk-based Models

Stablecoins are one of the most widely capitalized type of cryptocurrency. However, their risks vary significantly according to their design and are often poorly understood. We seek to provide a sound foundation for stablecoin theory, with a risk-based functional characterization of the economic structure of stablecoins. First, we match existing economic models to the disparate set of custodial systems. Next, we characterize the unique risks that emerge in non-custodial stablecoins and develop a model framework that unifies existing models from economics and computer science. We further discuss how this modeling framework is applicable to a wide array of cryptoeconomic systems, including cross-chain protocols, collateralized lending, and decentralized exchanges. These unique risks yield unanswered research questions that will form the crux of research in decentralized finance going forward

Making Algorithmic Stablecoins More Stable: The Terra-Luna Case Study

We study the dynamics of the Terra-Luna collapse occurred in May 2022 by creating a simulation environment that embodies both the free market buying-selling transactions and the Terra-Luna protocol exchange features. The parameters used during the simulation generate the conditions necessary for triggering the deviation from the peg of the stablecoin UST, along with the subsequent collapse of its value to almost zero. Then we present three proposals to increase the stability of algorithmic stablecoins and we employ the simulation environment to show how they could help stabilize the algorithmic stablecoin’s peg