Algorithmic stablecoins: What are they and how do they try to hold their peg?

Algorithmic stablecoins have been the talk of the town since the Terra-Luna collapse that wiped out over $40 billion in investor wealth in a matter of days in May 2022.

The historic de-pegging of the TerraUSD stablecoin sent shockwaves through the financial world last year, and many crypto investors remain skeptical of such algorithmic stablecoins. In this explainer, we'll dive into the fundamentals of what can be considered algorithmic stablecoins and the risks that come with them.

What are algorithmic stablecoins?

Algorithmic stablecoins are a type of digital currency that leverage computer algorithms and smart contracts to stabilize their value, typically pegging it to another asset like the U.S. dollar. Unlike centralized stablecoins such as Tether, which are backed by physical assets, or decentralized stablecoins like MakerDAO's DAI, which are over-collateralized with cryptocurrency, algorithmic stablecoins often operate under-collateralized. This means they don't rely on a reserve of assets for their value.

These stablecoins use a system of 'balancer' or 'share' tokens to absorb market volatility and maintain their peg. For example, in the Terra blockchain system, the algorithmic stablecoin TerraUSD interacted with the governance token Luna to attempt to keep its value steady. When the value of TerraUSD rose above $1, Luna holders would profit by exchanging their Luna for TerraUSD. Conversely, when TerraUSD's value fell, traders could benefit by exchanging it for Luna, thus reducing the supply and increasing the price.

The stability of these algorithmic stablecoins is heavily dependent on market demand. If demand decreases below a certain threshold, the entire system can falter. Furthermore, these stablecoins rely on independent investors to perform price-stabilizing arbitrage, which can introduce significant risk. Despite these potential downsides, the transparency and decentralization offered by algorithmic stablecoins can be attractive to some users, as their operations are governed entirely by auditable code and are not subject to regulatory oversight.

Types of algorithmic stablecoins

Let's delve into the different types of algorithmic stablecoins to better understand their unique characteristics and how they function.

Firstly, we have the "rebasing" algorithmic stablecoins. These stablecoins typically use price-elastic ERC-20 tokens, the total supply of which isn't fixed and is adjusted regularly. The Ampleforth protocol, for example, uses a rebasing feature that alters the token supply based on the token's price over time.

Secondly, we have "seigniorage" algorithmic stablecoins. This model generally comprises two forms of cryptocurrencies — the stablecoin and seigniorage shares. Examples include Basis Cash, which adjusts its supply to keep the price of BAC stable, and Luna/UST.

Lastly, we have "fractional" algorithmic stablecoins. These stablecoins merge the features of fully algorithmic and fully collateralized stablecoins to avoid over-collateralization and reduce custodial risks. An example is Frax, which uses a partial-collateral protocol.

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Trading risks, benefits

Algorithmic stablecoins carry a unique set of risks and benefits that are essential for traders to understand. On the one hand, they represent a true embodiment of the decentralized principle, operating solely through auditable code without any regulatory oversight. This lack of tangible asset requirement eliminates the risk of user error and reintroduces the concept of seigniorage into the crypto ecosystem, allowing for the assessment of profit or loss on the creation of currency in the digital asset world.

However, the architecture of these algorithmic stablecoins also presents inherent weaknesses. These uncollateralized digital assets, which use algorithms and market incentives to attempt to peg to the price of a reference asset, are vulnerable to de-pegging risk. They require a certain degree of demand to function correctly, and if this demand falls below a certain level, the system can collapse. 

It's important to note that their stability can be severely impacted in times of crisis, when traders acting on ambiguous information may cause the stablecoin to lose value, triggering a herd mentality that can result in a significant drop in the stablecoin's price. For instance, the TerraUSD stablecoin experienced a significant de-pegging event when its price fell below $1, leading to a massive sell-off and a consequent drop in the price of Luna, the governance token of the Terra blockchain system.

Are algorithmic stablecoins regulated?

While the decentralization and transparency offered by algorithmic stablecoins can be appealing, it's crucial to understand that they currently operate in a largely unregulated space.

This lack of regulation can present both opportunities and risks. On one hand, the absence of regulatory oversight allows for greater innovation and flexibility within the market. On the other hand, it also means that there are fewer protections in place for investors.

For example, when the price of TerraUSD fell significantly below its intended $1 value, investors experienced considerable losses. This incident highlighted the potential risks associated with algorithmic stablecoins and sparked calls for greater regulation.


Disclaimer: This article was produced with the assistance of OpenAI’s ChatGPT 3.5/4 and reviewed and edited by our editorial team.

© 2023 The Block. All Rights Reserved. This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.

About Author

Timmy Shen is an Asia editor for The Block. Previously, he wrote about crypto and Web3 for Forkast.News from Taiwan after spending more than three years in Beijing covering finance and current affairs at Caixin Global and Chinese tech at TechNode. His China-related reporting has also appeared in The Guardian. When he's not chasing headlines, you'll find him savoring hot pot and shabu shabu in a Taipei local haunt. Timmy holds an MS degree from Columbia University Graduate School of Journalism. Send tips to [email protected] or get in touch on X/Telegram @timmyhmshen.