Algorithmic stablecoin is a type of stablecoin that maintains its value through an algorithmic protocol that automatically adjusts supply, without relying on traditional collateral assets.
This type of stablecoin helps minimize risks from centralized issuing organizations and aims for a DeFi system, stabilizing value through automatic token burning and minting mechanisms.
MAIN CONTENT
Algorithmic stablecoin maintains its value through an automatic supply adjustment mechanism, without needing collateral assets.
There are three basic models including Rebasing, Seigniorage, and Fractional Algorithmic stablecoin with different mechanisms.
The biggest challenge is to maintain a sustainable system and user trust to avoid the 'death spiral'.
What is Algorithmic Stablecoin?
Algorithmic stablecoin uses algorithms to maintain the value of tokens close to a fixed level, usually the face value of fiat currency. This is achieved through a decentralized protocol that adjusts supply by burning or minting tokens.
Unlike collateralized stablecoins, this model does not require collateral assets but relies on independent economic mechanisms to control value. The common operational method is to adjust the supply of tokens according to price fluctuations to stabilize the exchange rate.
Why do we need Algorithmic stablecoin?
Collateral-backed stablecoins like USDT face risks regarding reserve transparency and centralized management, making them susceptible to regulatory impacts and account freezing risks.
Algorithmic stablecoin aims for decentralization and complete independence from real assets, helping to minimize legal risks while supporting the development of a self-governing global financial system that does not rely on banks or governments.
Types of Algorithmic Stablecoin
Algorithmic stablecoins are categorized based on their value maintenance mechanisms, including: Rebasing, Seigniorage, and Fractional Algorithmic stablecoin.
What is Rebasing Algorithmic Stablecoin?
Rebasing stablecoin adjusts the supply of tokens daily based on the price difference from the peg price, increasing or decreasing the total number of tokens in circulation to maintain stable value.
This model automatically balances supply and demand through changes in the number of tokens without directly affecting the price of each token. This is the first model to appear and is still being researched by many projects.
What is Seigniorage Algorithmic Stablecoin?
Seigniorage stablecoins operate on a multi-token system, where the primary token is pegged to a stable price and secondary tokens play a role in maintaining stability through token minting and burning mechanisms.
For example, Basis Cash with three types of tokens BAC, BAS, and Bonds, or Terra Stablecoin with two Tokens UST and LUNA. This mechanism incentivizes users to burn or mint tokens to ensure that the value of the primary stablecoin always hovers around 1 USD.
"The Terra ecosystem has created a complete Seigniorage model that contains both utility and stable value, becoming an important example for the future of Algorithmic stablecoin."
Do Kwon, CEO of Terra Labs, 2021
Example: Basis Cash
Basis Cash consists of three tokens BAC (USD-pegged stablecoin), BAS (incentive to decrease price), and Bonds (incentive to increase price). When BAC is higher than 1 USD, the protocol creates BAS to reduce BAC supply; when BAC is lower than 1 USD, users are incentivized to burn BAC to receive Bonds.
Despite being innovative, Basis Cash faced security issues and a lack of utility for Bonds, leading to the system's performance not meeting expectations.
Example: Terra Stablecoin (UST)
Terra uses a dual-token system, including stablecoin like UST pegged to USD and Token LUNA used for fee payments, while minting and burning UST to maintain value.
Thanks to an efficient operating ecosystem and the intrinsic value of Token LUNA, Terra's model is considered more successful than many other Seigniorage projects.
What is Fractional Algorithmic Stablecoin?
Fractional is a combination of algorithmic stablecoins and partially collateralized stablecoins with fiat assets like USDC.
This model uses a token pair, where part of the stablecoin is backed by real assets and the other part is based on an algorithm that burns/locks secondary tokens. The goal is to effectively balance capital while still maintaining higher stability than purely algorithmic models.
A leading example is FRAX and Iron Finance. FRAX operates with tokens FRAX (pegged to USD) and Frax Shares (FXS). The collateral ratio is adjusted based on market price to keep stability.
Iron Finance initially followed this model but failed due to a sell-off spiral, bringing the system down to a value of 0.
The challenges of Algorithmic stablecoin
The mechanism for maintaining price stability of Algorithmic stablecoins is very difficult to sustain, especially during periods of high volatility and when user trust is lost.
Most multi-token stablecoins fail due to an inability to balance incentives for secondary tokens, leading to a 'death spiral' that can quickly cause devaluation. Only ecosystems with truly useful secondary tokens, like Terra, can maintain long-term trust and stability.
"The biggest challenge for algorithmic stablecoins is establishing a strong enough ecosystem and balanced economic incentives for users to self-maintain stable value in all market situations."
Andreas M. Antonopoulos, Blockchain expert, 2022
Conclusion
Algorithmic stablecoin is gradually becoming an important factor in DeFi, but more practical utility and supportive ecosystems are needed for sustainable survival.
The process of experimentation, failure, and improvement is inevitable for blockchain and algorithmic stablecoin projects, opening up diverse and creative futures for the cryptocurrency ecosystem.
Frequently Asked Questions
How does Algorithmic stablecoin differ from collateral-backed stablecoins?
Algorithmic stablecoin does not require collateral assets but uses an automatic supply adjustment protocol to keep the price stable, while collateral-backed stablecoins rely on actual reserves.
What is the Seigniorage model in Algorithmic stablecoin?
Seigniorage is a two or multi-token mechanism, where secondary tokens are used to adjust supply and demand or create economic incentives to maintain the stable value of the primary token.
How does the death spiral affect Algorithmic stablecoin?
This is a chain of negative feedback that causes stablecoins to devalue quickly, due to loss of trust and prolonged sell-offs, leading to the breakdown of the price adjustment system.
What is a successful example of an Algorithmic stablecoin?
Terra UST was once a prime example, leveraging utility Token LUNA to maintain stability and user trust.
Is Algorithmic stablecoin safe?
Their stability depends on the design of the ecosystem and user trust; many projects have failed due to poor balancing of economic mechanisms.
Source: https://tintucbitcoin.com/algorithmic-stablecoin-la-gi/
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