What is an Algorithmic Stablecoin?
What is the definition of an algorithmic stablecoin?
In order to understand how algorithmic stablecoins are supposed to work, it’s important to know the definition and role of a stablecoin. Briefly, a stablecoin is a type of cryptocurrency that remains stable in its value relative to a fiat currency such as the US dollar. The value of one unit of stablecoin is therefore said to be “pegged” to one unit of the associated fiat currency. As examples, each unit of the stablecoins USD Coin (USDC) and Tether (USDT) is often said to be pegged to 1 US dollar (US$1).
The measure of a particular stablecoin’s stability refers to the degree to which it maintains its so-called peg. For example, as shown in Figure 1, the price of 1 USDC stablecoin hasn’t deviated from the value of 1 US dollar by more than $0.01 over a two-year period (as of January 2020). Hence, the stability of USDC is evident.
Figure 1: The history of the stablecoin USD Coin up to and including January 2023 (source: Coindesk.com)
To ensure liquidity, reliability and market confidence, the issuers of some stablecoins such as USDC and USDT will hold in their reserves (aka: treasuries) a blend of fiat cash and nearly-cash-equivalents that, in total value, match the supplies of their stablecoins (at its pegged value). For example, in its public disclosure, Circle–the issuer of USDC–graphically shows how USDC is not only 100% asset-backed, but also how that backing is distributed across actual US dollars (cash) and short-dated US Treasury Bonds valued in US dollars. Typically, with an asset-backed stablecoin, as more coins are minted, the matching treasury is equally engorged with assets in order to maintain the stablecoin’s peg. Conversely, as tokens are burned, the matching treasury will shrink accordingly.
Whereas asset-backed stablecoins are typically collateralized by issuers that hold the matching assets in their treasuries, purely algorithmic stablecoins are typically not backed by any such assets. Thus, algorithmic stablecoins are considered to be uncollateralized cryptocurrencies. Some stablecoins–referred to as fractionalized or hybrid stablecoins–are partially asset-backed and partially non-asset-backed.
As can be seen from figure 1, even an asset-backed (non-algorithmic) stablecoin like USDC is constantly moving off its peg by fractions of a penny. As USDC ebbs and flows off its peg, Circle sits vigil, constantly responding in an effort to keep the stablecoin as close to its US$1 peg as possible.
How does an algorithmic stablecoin work?
Meanwhile, contrary to popular belief, maintaining an algorithmic stablecoin’s peg is usually less about an automated algorithm running on a stablecoin’s underlying blockchain and more about the algorithms used by arbitrageurs and other traders to spot and and act immediately on potentially lucrative arbitrage opportunities involving the coin itself. In other words, many algorithmic stablecoins literally depend on open market arbitrageurs to do what they do best (arbitrage) to maintain their peg; an external and unpredictable dependence that should deter many enterprises from using them.
Arbitaguers are expert traders that typically know how to find and capitalize on buy-low/sell-high opportunities that may last for mere seconds at a time. Such opportunities (and the traders that chase after them) exist in every financial and commodities market, including the markets for cryptocurrencies. The basic idea of an algorithmic stablecoin — especially algorithmic stablecoins of the seniorage type — is not only to stimulate this natural appetite for arbitrage opportunities, but to do so in a way that the law of supply and demand is constantly nudging the coin’s value back to its peg.
For example, imagine an algorithmic stablecoin that has the fictitious name AlanCoin, a coin whose value is pegged to US$1. For whatever reasons (e.g., increased demand through cryptocurrency trading on centralized exchanges and decentralized exchanges), should the value of an AlanCoin start to increase in value relative to its US$1 peg, the easiest way to nudge it back to its peg would be to increase the total supply of the coin in a way that not only reduces the value of each coin, but that also eases the demand against the scarce supply that’s pressuring the coin’s value to rise off its peg in the first place.
Should the price of AlanCoin fall below the price of US$1 (indicating weaker demand), the dynamics would work in reverse. A reduction in AlanCoin’s circulating supply would result in an increase to the value of each coin, pressuring it back to its peg.
As with sovereign government-backed fiat currencies however, the million dollar question (or billion dollar question in the case of the world of cryptocurrency) is “Who gets to decide when to mint new coins or burn existing ones in an effort to adjust a stablecoin’s supply such that its price stays on its peg?”
In the case of many algorithmic stablecoins, the answer is essentially to let the open market decide; mainly aribtrageurs.
While there are variations in the exact mechanisms mechanisms from one algorithmic stablecoin to another, the supplies (and therefore the values) of many algorithmic stablecoins depend on their inversely proportional relationships to the supplies (and values) of specific “companion” non-stablecoin cryptocurrencies. In the context of this inversely proportional relationship, other articles and posts on the Web may refer to these companion coins as governance tokens. But in the context of their role in maintaining a stablecoin’s peg, these companion coins—which, in other contexts, could easily be a standard payment token—are better described as “counterbalancer coins.” Such was the case with US$1-pegged algorithmic stablecoin TerraUSD (UST) whose supply and peg was notoriously maintained through its inversely proportional relationship to the supply of the counterbalancing non-stablecoin Luna.
Whenever UST rose off its US$1 peg, investors (mainly arbitrageurs armed with automated software bots) could exchange 1 US dollar’s worth of Luna for 1 UST at whatever its current US$1+ value was on the open market. For example, if increased demand for UST drove it off its peg to US$1.01, holders of Luna could trade 1 US dollar’s worth of Luna for one unit of UST which, in turn, could be traded for $1.01 of fiat currency thereby earning a profit of 1 penny (done frequently enough at scale, this form of arbitrage could yield small fortunes). In the course of processing such a swap, the underlying blockchain’s (Terra) special swapping function would burn a US dollar’s worth of Luna in order to mint a new unit of UST. Algorithmically (and theoretically), the resulting increase in UST’s supply would cause its value to ebb back to its US$1 peg. For arbitrageurs, the bait (the arbitrage stimulus) was essentially the discount at which the swapping function conducted the swap.
Conversely, if UST slipped-off its US$1 peg, holders of UST could trade one unit of UST at its current value (eg: US$0.99) for 1 US dollar’s worth of Luna (again, earning a profit of 1 penny). In the course of effecting that trade, the Terra blockchain’s swapping function would burn a unit of UST in order to mint the corresponding amount of Luna, thus reducing the supply of UST and driving the price back up to its peg. Arbitrageurs could use any of the many centralized exchanges or decentralized exchanges that supported Luna and UST as a “trading pair” to execute their swaps and, on behalf of those traders, those exchanges would access the Terra blockchain’s special swapping function via an application programming interface (API) to take advantage of the discounted offer.
If it could be said that the Terra blockchain operated an actual algorithm to support the the algorithmic stablecoin UST, that algorithm existed as a part of this API-based swapping function. But it was less of an algorithm and more just a special discount that arbitrageurs armed with automated bots would take advantage of whenever their arbitrage-optimized algorithms saw the opportunity to profitably act.
Whereas UST involved a vulnerable relationship with the counterbalancing non-stablecoin Luna as well as open market arbitrageurs (which led to UST’s collapse and, subsequently, widespread fear and dismissal of algorithmic stablecoins), it’s important to note that there are other types of algorithmic stablecoins.
For example, instead of minting and burning non-stablecoins on a companion blockchain, some algorithmic stablecoins are able to mint or burn coins that are held in accounts by private parties. In such cases, regardless of whether the algorithm intends to grow or shrink the currency’s supply, all holders of the stablecoin will maintain their percentage share of the supply. An account that holds 1% of the stablecoin supply before the supply is “adjusted” will continue to hold 1% of the supply after the adjustment (even though each account will hold more or fewer coins). Other algorithmic stablecoins burn coins by offering to purchase them at a small profit to the holder. Then, the coins sold by the holder and acquired by the issuer are burned.
What are examples of algorithmic stablecoins?
What is the relevance of algorithmic stablecoins to enterprises and other businesses?
When it comes to enterprises and businesses, one of the biggest barriers to enterprise adoption has to do with the risks of keeping any amount of cryptocurrency in reserve, even if only to pay the fees associated with the coin-operated business models of most if not all distributed ledgers. Holding any amount of any chain’s native cryptocurrency can expose an organization to the risks of cryptocurrency volatility and, from a compliance point of view, constantly shifting local to international regulatory conditions.
However, similar to other revolutionary technologies (PCs, the internet, web, mobile, cloud, etc.) that have inspired waves of innovation and disruption, distributed ledger technology (DLT) presents organizations with a game-changing opportunity to innovate new offerings, digitally transform themselves, disrupt the status quo of their industries, and engage their customers, partners, employees and other stakeholders in more meaningful and effective ways. History has proven that the organizations–incumbents or startups–that are early to embrace such game-changing technologies are the ones that will profit from the next generation of technological innovation.
For enterprises and businesses looking to leverage the disruptive potential of DLT sooner rather than later (and in absence of government-backed central bank digital currencies), stablecoins could buffer organizations from the risks associated with cryptocurrency volatility and regulatory uncertainty. For example, instead of holding volatile cryptocurrencies in reserves, an organization might consider holding stablecoins instead and then exchanging them as necessary for other cryptocurrencies on an as needed basis. Working with stablecoins that are pegged to major fiats like the US dollar and the euro is also easier on enterprise financial systems that were never designed with volatile non-fiat currencies in mind.
What are the risks of working with algorithmic stablecoins and their companion cryptocurrencies?
But once an organization decides to hold stablecoins, it must consider the benefits and risks of holding asset-backed stablecoins versus algorithmic stablecoins. Given the unproven track record of algorithmic stablecoins (never mind the collapse of USDN, UST and their counterbalancer cryptocurrencies) and how they’re often times designed to also serve the interests of retail cryptocurrency investors and arbitrageurs, it would seem unwise for enterprises to explore algorithmic stablecoins as any sort of hedge against non-stablecoin cryptocurrency volatility and regulatory uncertainty.
Additionally, two other hidden dangers of algorithmic stablecoins that enterprises must take great care to avoid have to do with the companion chains whose native cryptocurrencies are used as the algorithmic counterbalancer (the way Luna was used to keep UST on its peg) and the governance of the underlying blockchain that services both the stablecoin and its counterbalancing cryptocurrency:
But for other use cases, algorithmic stablecoins could have a possible role in the enterprise. For example, in an enterprise where currency trading is a core part of its business or for enterprises that are actively engaged in decentralized finance (DeFI) activities. In such cases, an algorithmic stablecoin can be used as collateral for a loan (where accepted) or deposited into an interest bearing account that accepts the given algorithmic stablecoin. But on the larger global financial stage, few such opportunities exist.
For now, enterprises that are in lines of business that are not specific to DeFi concerns, using and holding algorithmic stablecoins is a very risky undertaking.