Vitalik Buterin: How to create algostablecoins that don’t turn into ponzis and don’t collapse

Ethereum co-founder Vitalik Buterin shared two thought experiments on how to evaluate the stability of an algorithmic stablecoin.

Buterin’s comments were prompted by the multibillion-dollar losses caused by the collapse of the Terra (LUNA) ecosystem and its TerraUSD (UST) algorithmic stablecoin.

In a May 25 blog post, Buterin noted that the increased focus on crypto and DeFi following the collapse of Terra is “very welcome,” but warned against a complete write-off of all algorithmic stablecoins.

“We don’t need a stablecoin booster or stablecoin doomerism, but rather a return to principle-based thinking,” Vitalik Buterin emphasized.

“While there are many automated stablecoin projects that are fundamentally flawed and doomed to failure, and many others that could theoretically survive but are very risky, there are also many stablecoins that are very reliable in theory and have withstood the extreme conditions of the crypto market. practice,” he added.

His article focused in particular on the Reflexer (RAI) stablecoin, fully backed by Ethereum (ETH), which is not pegged to the value of fiat currency and relies on automatic interest rate algorithms to proportionally counter price movements and incentivize users to return RAI to its target price range.

Buterin stated that it is “an example of a pure ‘ideal type’ of a collateralized automated stablecoin” and its structure also gives users the ability to extract their liquidity in ETH if trust in the stablecoin collapses significantly.

The Ethereum co-founder also proposed two thought experiments to determine whether an algorithmic stablecoin is “really stable.”

1: Can a stablecoin “roll up” to zero users?

If the stablecoin project’s market activity “drops to near zero,” Buterin said, users should be able to extract the fair value of their liquidity from the asset.

Buterin emphasized that UST does not meet this parameter due to its structure in which LUNA, or what he calls a volatile coin (volcoin), must maintain its price and user demand in order to maintain its peg to the US dollar. If the opposite happens, then it will become almost impossible to avoid the collapse of both assets.

“Firstly, the price of Volcoin is falling. Then the stablecoin starts shaking. The system is trying to support the demand for stablecoins by issuing more volcoins. With low trust in the system, there are few buyers, so the price of Volcoin drops rapidly. Finally, as soon as the Volcoin price approaches zero, the stablecoin also collapses.”

On the contrary, since RAI is backed by ETH, Buterin argued that declining confidence in the stablecoin would not lead to negative feedback between the two assets, reducing the likelihood of a wider crash. At the same time, users will still be able to exchange RAI for ETH locked in vaults that support the stablecoin and its lending mechanism.

2: Negative interest rate option

Buterin also sees it as vital that an algorithmic stablecoin be able to implement a negative interest rate when it tracks a “basket of assets, consumer price index, or some arbitrarily complex formula” that grows at 20% per year.

“Obviously, there is no real investment that can generate at least 20% returns per year, and definitely no real investments that can increase their returns by 4% per year forever. But what happens if you try? Buterin suggested.

He stated that in this case, there are only two outcomes: either the project “charges holders with some kind of negative interest rate, which balances out to effectively neutralize the US dollar growth rate embedded in the index.”

Or:

“It turns into a Ponzi, generating amazing profits for stablecoin holders for some time, until one day it suddenly collapses with a bang.”

In conclusion, Buterin noted that the fact that an algorithmic stablecoin is able to handle the scenarios described above does not make it “safe.”

“It can still be fragile for other reasons (for example, due to insufficient provisioning ratio), contain errors or vulnerabilities in management. But stability in steady state and in extreme cases should always be one of the first things we test.”

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