A "Black Swan" event is unpredictable beyond what is normally expected of a situation, is obvious in hindsight and has potentially severe consequences. Examples include the subprime crisis and subsequent meltdown of the banking sector in 2008 and the market capitulation following the start of the global pandemic.
In the financial markets, or in any industry for that matter, Black Swan events are mostly known as negative. Still, history shows that these events are also a pivotal point of positive systemic change. I believe that the same process will apply to this event.
Ahmed Ismail is president and CEO of Fluid, a DeFi liquidity aggregator, and co-founder of HAYVN, a regulated over-the-counter desk in the Middle East.
The downfall of UST as an algorithmic stablecoin is a Black Swan event and should never have happened. It was a project worth over $18 billion – practically too big to fail. Stronger regulatory controls overseeing the project’s automated trading system could have mitigated the situation a long time ago.
Terra’s meltdown spread to bitcoin, causing its price to drop by $10,000 in a matter of hours. It has also caused widespread damage to our peers in the crypto industry, notably exchanges and small and large investors.
If automated decentralized finance (DeFi) trading systems are to grow to this size, there is a need for better regulation and stakeholder safeguards.
Risks associated with algorithmic stablecoins
What has come to the fore this week are the risks associated with algorithmic stablecoins. The key message here is that computer code cannot replace asset-backed collateral.
An algorithmic stablecoin isn’t backed by assets; instead, it’s stabilized by computer code through an algorithm or algorithms designed to hold its peg. Many “algos” have failed before UST, but this historic collapse now proves that algorithmic stablecoins have loopholes in their architecture.
Unfortunately, this chink in the Terra network’s design has managed to bring what was a multibillion-dollar project close to zero within days. It also caused systemic risk across DeFi and the broader crypto industry.
The network’s builders, primarily Terraform Labs, tried to defend the UST/USD peg position by selling large amounts of BTC held in reserve.
A silver lining: It seems as though asset-backed stablecoins such as USDT, USDC and BUSD have weathered the storm and investor sentiment remains intact, although they haven’t been untouched. USDT, for instance, traded nearly 5% away from its USD peg on Thursday, showing how extreme volatility affects the price of stablecoins that are meant to be 100% asset backed.
This event has highlighted key lessons to be internalized by the DeFi industry: Algorithmic stablecoins do not work, or at least need much more research and development. Further, regulatory and technological controls must be enacted before another algo is allowed to get so big.
Crypto needs to be able to handle extreme volatility
This isn’t the first Black Swan event, nor will it be the last. They will happen again in the future. The big question, though, is why was there systemic fallout that affected other assets in the market and how can that be mitigated?
See also: Unleashing Liquidity in DeFi Trading | Opinion
The answer boils down to liquidity, volatility and how markets react in the face of Black Swans. Crypto markets are illiquid and thinly traded. Liquidity is siloed, and crypto markets are extremely inefficient. They become especially vulnerable, and even the most stable cryptos such as BTC and ETH are fragile. All assets will falter when liquidity cannot flow.
So, crypto markets need liquidity aggregators. These systems could help investors manage the turbulent waters caused by Black Swan events – when volatile conditions occur, market participants need access to liquidity quickly and at the best possible price to maintain equilibriums.
As for regulatory controls, I am certain lawmakers will look at the implosion of one of the largest crypto assets ever and find ways to tame the industry.
That’s just our industry growing and learning.
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