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TLDR below. This is not financial advice.
FEI protocol had all of Twitter talking last week. Backed by significant VCs, this new algorithmic stablecoin mechanism, $FEI, managed to raise US$1 billion worth of Ether within the first 24 hours. And within 24 hours of launch, the price of $FEI dropped significantly, as did $TRIBE, the governance token.
So what went wrong? How did the economics model and incentive design fail so terribly? And what was the tipping point that caused this massive disaster? Today, we analyse the lessons to learn from $FEI, this new mechanism to create an algorithmic stablecoin.
TLDR: FEI had great ideas in the pure engineering side of the mechanism design. But economics is not pure systems engineering. It includes human interaction, which can make or break an ecosystem. The human element is what separates engineering from economics.
Over the weekend (on Sunday), we had a community chat on Discord, discussing stablecoins. We touched on the topic of FEI protocol since it was the topic of the week. It is a very interesting experiment that went south, so it’s good to unpack what happened and learn from it.
About FEI Protocol
Here’s a quick summary of the FEI protocol, because you’ve probably read about it a zillion times.
What is $FEI? A stablecoin pegged to $1, algorithmically. That means $FEI’s economics is determined mathematically to get the $1 peg. The economics can be supply, withdrawal fee, minting fee, etc.
What is $TRIBE? A governance token to adjust the parameters to change the mechanisms of $FEI.
What is so special?
Instead of using $ETH to create a token valued at $1, you sell your $ETH for $FEI.
The protocol owns part of the assets as part of governance to manage that $1 peg.
Direct incentives are used to reward and punish users in the system. If $FEI is below $1 and you sell it for $ETH, you have to pay a “punishment fee” and you get less than $1 worth of $ETH back. If you deposit $ETH to mint more $FEI when it is less than $1, you get more $FEI in return.
How did it get so popular? It was backed by large VCs and strong personalities on Twitter.
How much did it raise? 1.3 billion in $ETH, of which 1 billion was raised in 24h.
What happened within 24h of it releasing? People wanted to get their $ETH back by returning $FEI. This caused massive sell pressure, and with the value of $FEI, with the incentive, dropped significantly. At one point it was less than $0.40 when it is meant to be pegged at $1. This was a 60% value loss.
Why did people put money in, in the first place?
Of course, everything is governed by a bonding curve!
Catch the discussion on YouTube
Economics Mechanism of FEI Protocol
So let’s dive into the economics mechanism analysis. We will never stray too far from economics fundamentals — supply, demand, willingness to buy/sell, incentives, punishments and behaviours.
Mechanism Design of FEI Protocol
Fundamentals: Incentives, Punishments, Supply/Demand
Mechanism design is the design of rules governing the system — participants and general token usability.
With stablecoins, one needs to bootstrap the community since most of the value of stablecoins come from their usability. To bootstrap, $FEI is sold at a discount and capped at $1.01. If you enter the bonding early (e.g. $0.99), you get to profit from the difference between the price you purchased at and the market value, $1.
Even at $1.01, people are still purchasing $FEI for $ETH because they also receive $TRIBE. Since $FEI is technically priced at $1, and if you value $TRIBE more than $0.01, you are getting a deal by receiving $TRIBE.
The mechanism also has direct punishments for users. When prices are below $1 and you want to sell it, you have to pay a punishment fee. That is the difference in cents, squared. So if it is currently priced at 0.95, the difference is $0.05. And the punishment is $0.25. That means your $FEI is really worth $0.75.
In this case, the value before punishment cannot be less than $0.90, since the squared difference is $1. That means at $0.90 per $FEI before punishment, you are selling $FEI for nothing in return.
And this is important because it leads to the effects of a circular economy explained next.
Economics 101: Secondary and Tertiary Effects
Fundamentals: Supply/Demand, Willingness to buy/sell
A circular primary economy is a very important feature in the crypto market. This type of economy means that in addition to thinking of first-order effects, secondary and tertiary effects of any behaviours also need to be considered and modelled.
About $TRIBE Supply
Firstly, as mentioned above with free alpha and free $TRIBE, early access is by VCs. In a very normal economics 101 understanding, their willingness to sell is high because they get free returns (arbitrage) and $TRIBE was given for free. So any value in $TRIBE is just risk-free money.
And that raises the point of supply and demand. When $TRIBE has less use-case and the value of it now is risk-free, users will want to sell $TRIBE. That causes an oversupply in the market. Prices fall.
Willingness toSell $FEI
Another problem is that $TRIBE can only be sold via $FEI. That means to really liquidate $TRIBE, you have to sell $FEI. Even if someone wants to keep $FEI to use it in the future, the only way to cash out the $TRIBE money is through $FEI. This leads to high sell pressure of $FEI as well as $TRIBE. Hence, prices fall.
Not only that, when prices fall due to over-supply, the punishment causes the prices to fall even further. And the fear of a bank-run makes users more likely to want to sell, only worsening the situation.
Willingness of Buy $FEI
The direct incentives discussed above are not only punishments. There are also rewards. Users are incentivised to deposit $ETH for $FEI. Why are people not doing that instead?
Because in economics 101, you are likely to be a seller if there are buyers in the market. In FEI protocol, who is buying FEI? No one. So if no one is buying $FEI, no matter now many direct incentives are provided, no one wants to change $ETH to $FEI.
It’s economic fundamentals.
Community vs VC
Lastly, it is about human social behaviours. The most beautifully engineered system (and economic model) fails because human behaviour is complex and hard to model.
In the book, we discussed how asymmetric information can cause lots of economic problems, including moral hazard. This is an example of a moral hazard. When early entrants add liquidity early, they are usually rewarded with perks like discounts on tokens or additional alternate tokens.
When the pool is open to the public, users participate in the fundraising perhaps due to big-name VCs joining or because they are keen on the game. When things are going well, it is all rainbows and butterflies. But when things go south — when it rains, it pours.
Now that the fundraising has closed and the team is opening the governance voting to the community, the users can see the disparity of VCs vs Community at play. The community chooses between $1, $0.90 or no change to the system. That means 1 $FEI is able to be exchanged for $1, $0.90 or the continuation of the mechanism.
At the time of writing, the voting has not concluded. The community went from accepting the $1 exchange rate to no change in the mechanisms.
FUD — Fear Uncertainty Doubts
This is where FUD kicks in. FUD is ‘fear, uncertainty and doubt’. It is not a technical risk, but a social risk. And to make matter worse, the direct disincentive aggravates this effect. When $FEI is 5.96% off its peg, the punishment is 35%. This means when $FEI is priced at $0.94 on Uniswap, you are only getting $0.65 worth of ETH back. It worsens the FUD and creates all sorts of fear and negative behaviour.
In this game theory analysis, we see that the punishment fees can help to restore the price. The funds gained through the fees will be used to sustain the value. However, those who exist at a loss are unlikely to return, resulting in the less than ideal outcome of users leaving.
The technical idea is great, but selling and being punished for this is not robust in the long term. It’s unlikely that the system will be sustainable in the long run.
Think Secondary Effects
We have mentioned secondary effects. When it comes to Algo stablecoin, the prices have to be pegged. How do we allow the price to return to peg when it goes off?
When it is more than $1, that is simple. Increase the supply to rebalance the value.
When it is less than $1, that is where the challenge lies. By making the real value lower through a punishment tax only worsens the situation. It might also be challenging for sellers to receive this currency where they are unable to cash out. Modelling the participants and behaviours is needed to test the robustness of the system.
At the end of the day, this is a great experiment. But it is important to constantly engineer the protocol as the systems and dynamics change. This model of $FEI could have worked if it was a smaller group of true believers, who were not apeing into the protocol for quick wins.
As the users change, their behaviours and how they interact with the tokens change. The mechanism design needs to be able to update with the changing landscape and adapt to it.
One other topic that we have not discussed is the engineering behind reweights of the PCV.
In general, the reweights could act like the bonds of ESD mechanisms. One could game the system and accumulate before dumping when the time is right. The more frequent the reweights, the better the system, but it also benefits bots. The less frequent the reweights, the less benefit to bots frontrunning, but it does not hold in the pegged value and increases punishments. Both systems are bad for the users.
Right now, the practical thing could be to sell $ETH and reimburse users who lost money. Ideally, the VCs backing the protocol can use their power and influence to do something good. But realistically, the truth is that the protocol needs to build faith and trust in the system again. The problem is that it is extremely challenging. Once trust and faith are broken, it is very difficult to restore them.
Nonetheless, this is a great experiment. It brings in features of DeFi — bonding curve, quadratic fees and DEX liquidity mechanism. It is great to experiment by bringing them together. However, more analysis and modelling could have been done before launching the protocol.
When launching projects in a bull market it is easy to receive liquidity and support. But do not force to test, test and test again. We’re building the future. It’s not just about design and builds. Test, test and test again.