Stablecoins are supposed to be… well, stable. But if you’ve spent any time in crypto, you’ve probably seen algorithmic stablecoins blow up spectacularly despite promising cutting-edge tech, math-backed logic, and clever code. So what’s going on?

This article pulls back the curtain to explore how algorithmic stablecoins are designed to work, why they sometimes succeed (briefly), and the reasons so many eventually fail.

Let’s dive into the mechanics, myths, and meltdowns.

What is an Algorithmic Stablecoin?

In the simplest terms, an algorithmic stablecoin is a type of crypto asset designed to maintain a stable price—usually $1—without being backed by fiat or crypto collateral.

Instead of holding dollars or USDC in reserve, algorithmic stablecoins use smart contracts and economic incentives to expand or contract supply based on market demand.

Think of it like this: If the price of the coin goes above $1, the algorithm increases supply to push the price back down. If it drops below $1, supply is reduced to nudge the price up again.

Sounds elegant, right?

Well… not so fast.

How Algorithmic Stablecoins Work (In Plain English)

Let’s use a common two-token model to explain the typical setup. The most well-known example of this was Terra (UST) and Luna.

Step 1: The Peg

The stablecoin (e.g., UST) is pegged to the U.S. dollar, aiming to stay at $1.

Step 2: The Sister Token

There’s a second token (e.g., LUNA) that absorbs price volatility. You can mint UST by burning LUNA, and vice versa.

Step 3: Arbitrage Mechanism

If UST is worth more than $1:

• Users can burn $1 of LUNA to mint 1 UST and sell it for profit.
• This increases UST supply and pushes the price back toward $1.

If UST is worth less than $1:

• Users can buy UST cheaply, then burn it to mint $1 worth of LUNA.
• This reduces UST supply and helps restore the peg.

The system relies on arbitrageurs and speculators to do the heavy lifting.

When Algorithmic Stablecoins Seem to Work

In bull markets, everything is great. Here’s why:

• Demand for the stablecoin is high
• The secondary token (LUNA, in this case) has strong market value
• The peg appears stable
• Investors keep piling in because of attractive yields (hello, Anchor Protocol...)

That illusion of stability can last weeks, months, even years. But the key word here is: illusion.

Why Algorithmic Stablecoins Fail (Almost Always)

1. Reflexive Death Spirals

Algorithmic stablecoins hinge on market participants believing they’ll stay pegged, until everyone rushes for the exits. TerraUSD (UST) famously broke its $1 peg in May 2022, triggering billions in mass redemptions that ballooned LUNA’s supply from hundreds of millions to trillions in hours, vaporizing nearly $45 billion in market cap.

A similar reflexive collapse hit Iron Finance’s IRON/TITAN in June 2021 when a large TITAN sell-off skewed its TWAP-price oracle, letting bots mint effectively unlimited IRON and crash both tokens to near zero within a day.

2. Lack of Hard-Asset Backing

Without dollar or crypto reserves locking in value, there’s no floor to catch a falling peg. Basis Cash (BAC), which launched in 2020 after its predecessor returned investor funds over regulatory fears, never regained its $1 target. It traded as low as $0.80 before quietly winding down.

Likewise, “seigniorage” coins like Empty Set Dollar (ESD) and Dynamic Set Dollar (DSD) used rebasing supply tweaks to chase $1, but once yield-driven speculator interest dried up, both permanently traded well below their pegs.

3. Overreliance on Speculator Incentives

Some models assume arbitrageurs will always inject capital to restore the peg, but they don’t. Tron’s USDD launched in May 2022 with a $10 billion reserve pledge but fell to $0.95 within weeks, as mint/burn incentives alone couldn’t stem broader sell pressure.

Fei Protocol (FEI) debuted in spring 2021 with its “Protocol Controlled Value” model, yet after an ~$80 million hack and misaligned redemption mechanics, governance voted in August 2022 to wind down the DAO, effectively admitting its incentive design couldn’t sustain the peg.

4. Governance-Exploit Vulnerabilities

Decentralized governance can be its own undoing. Beanstalk’s governance contract let a flash-loan attacker amass enough “Stalk” tokens to push through malicious proposals, draining $76 – 182 million before anyone could react.

Fei’s TribeDAO merger with Rari Capital ended in discord: after a major $80 million hack, initial governance votes promised redress, but subsequent vetoes by the Fei team left victims uncompensated and the DAO insolvent.

Are There Any Good Uses for Algo Stables?

They’re still a fascinating idea, especially in:

• DeFi experiments
• Academic research
• Emerging economies with unstable currencies
• Fully decentralized finance protocols

Some projects are hybrid models, blending crypto collateral + algorithms + governance mechanisms to create more durable systems. Examples include Frax (FRAX) and Liquity (LUSD).

Still, none have come close to replacing fiat-backed stablecoins for real-world business use.

What Should You Use Instead?

If you’re a business, DAO, or fintech team looking for actual stable stablecoins, stick to these:

• USDC: Fully backed, regulated, and audited.
• USDT: Hugely liquid, though less transparent.
• DAI: Crypto-collateralized with decentralized governance.

They’re more boring, but in this case… boring is exactly what you want.

Final Takeaways

Algorithmic stablecoins are one of crypto’s boldest and riskiest ideas. They aim to maintain a peg without collateral by using incentives, arbitrage, and game theory. But the reality is… they usually fail. Fast.

If you’re just dabbling in DeFi or building on-chain tools, it’s okay to experiment. But if you’re managing funds, paying contractors, or storing treasury reserves—don’t risk it. Go with stability you can count on.

Learn more about stablecoins here