A lockdrop model with immediate liquidity, using Uniswap
Airdrops are coming back in vogue due to the regulatory uncertainty surrounding token sales.
Historically, the v1.0 model of airdropping tokens to random Ethereum addresses has proven to be largely useless. So teams are experimenting with new distribution models, particularly those teams that have raised private rounds and are now more nervous about a public sale despite getting closer to mainnet launch.
Livepeer pioneered Merkle mine, which has been widely dissected. Other teams are experimenting with variations of that ‘proof-of-work’ model. Edgewere is working on a lockdrop, whereby in order to get airdropped the EDG token one will have to lock up ETH into a smart contract for a certain period of time, after which the ETH gets unlocked (effectively giving up the opportunity cost of lending ETH on Compound/Dharma etc). DxDAO are planning something similar.
This post is a rough brain dump about a version of lockdrop that puts the idle ETH at work by leveraging Uniswap, a protocol for automated market making.
It roughly goes like this:
- XYZ tokens available to be distributed are locked into a smart contract
- smart contract can receive ETH contributions for up to a fixed period of time (contribution period)
- after contribution period lapses, smart contract creates a market for XYZ/ETH on Uniswap and uses XYZ and ETH balances as liquidity pool
- ETH contributors can withdraw ETH and XYZ from the smart contract proportionally to their ETH contribution, or keep earning a share of the trading fees from that market.
One potentially interesting aspect of this is the automated price discovery: a market price for the token is established without actually having to sell tokens or design a bonding curve. The total amount of ETH contributed during the contribution period sets the price of XYZ token in ETH terms (a potential issue here is ETH volatility during the contribution period). In that light, it could also work with a series of contribution periods, where the tokens are made available in subsequent chunks. So contributors in the second/third etc periods have a reference point on pricing. [Need to think more about this scenario].
The other interesting implication is obviously the immediate liquidity for the token enabled by Uniswap. In that light, the game theory is particularly intriguing. Many whom I’ve share this draft with raised the point that one would be incentivized to maximise the ETH contribution in order to get as many tokens as possible. However, for this actor to be able to then sell off the tokens and profit s/he would first have to withdraw most of the liquidity from the market, resulting in not enough liquidity to absorb the sale order. Imagine this actors contributed 99% of the ETH, he’d only be able to sell at best ~1% of this stash. Smaller ETH contributors on the other hand, if they knew there was a whale, would rush to sell the token, removing the incentive for whales to maximize contribution in the first place.
A few open questions remain:
- Where would the equilibrium settle, if at all? Is there a chance no one ends up contributing for fear of others selling out before/to them?
- Would the incentives change at all if ETH contributions were confidential until the contribution period lapses, as something like the Aztec protocol would enable?
- On the more technical side, there’s the open question of how to distribute Uniswap liquidity shares back to ETH contributors from the smart contract that owns them. One way to achieve something similar could be for the smart contract to be a DAO agent interacting the Uniswap in the background and granting DAO shares back to the ETH contributors proportionally. Then there would be some governance around managing the liquidity and fees.
- What are the regulatory implications of this model? Needless to say, PLEASE do not take this post as legal advice, I am not a lawyer!
Anyways, this is very rough and many details have not been thought true enough. But I thought I’d share to get some feedback before spending more time on it.
Buyer of Jack Dorsey’s ‘genesis tweet NFT’ reportedly detained in Iran
Iranian Cyber Police have reportedly arrested Bridge Oracle CEO Sina Estavi, according to a tweet pinned to Estavi’s Twitter account.
A rough translation of the tweet reads:
“The owner of this account was arrested on charges of disrupting the economic system by order of Special Court for Economic Crimes. Official judicial authorities will provide additional information.”
The same tweet is also pinned to the official account of Bridge Oracle, a Tron Network-based public oracle system. At the time of writing, the price of Bridge Oracle’s native token, BRG, has taken a sharp dive, crashing by more than 65%, according to data from TradingView.
Bridge Oracle is said to be a Malaysia-based blockchain company, but Estavi’s other venture, cryptocurrency exchange Cryptoland, was operating in Iran. Cryptoland’s Twitter account shares the same pinned tweet. No further information was shared publicly by the authorities.
Estavi is known for his heated bidding battle with tech entrepreneur and Tron CEO Justin Sun to buy Jack Dorsey’s first-ever tweet as an NFT. Twitter’s first tweet is dated March 2006 and reads, “Just setting up my twttr.”
In the end, Estavi successfully purchased the NFT for more than $2.9 million, or 1,630 Ether (ETH). Dorsey converted the proceeds to Bitcoin (BTC) and donated them to a charity organization in Africa.
Earlier this year, Estavi was sued by former Bitcoin.com CEO Mate Tokay for allegedly failing to pay him for his services. In his claim, Tokay also alleged that there’s an inconsistency between the purported and actual circulating supply of BRG.
Cointelegraph reached out to Bridge Oracle for comment. This article will be updated should they reply.
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Is Bitcoin nearing another Black Thursday crash? Here’s what BTC derivatives suggest
Bitcoin’s 51.4% crash in March 2020 was the most horrific 24-hour black swan event in the digital asset’s history. The recent price activity of the past week has probably resurrected similar emotions for investors who experienced the Black Thursday crash.
Over the past week, Bitcoin’s (BTC) price dropped 29% to reach a three-month low at $42,150. $5.5 billion in long contracts were liquidated, which is undoubtedly a record-high in absolute terms. Still, the impact of the March 2020 crash on derivatives was orders of magnitude higher.
To understand why the current correction is less severe than the one in March 2020, we will start by analyzing the perpetual futures premium. These contracts, also known as inverse swaps, face an adjustment every eight hours, so any price gap with traditional spot markets can be easily arbitrated.
Sometimes, price discrepancies arise during moments of panic due to concerns about the derivatives exchange’s liquidity or market makers being unable to participate during times of extreme volatility.
On March 12, 2020, the Bitcoin perpetual futures initiated a much larger descent than the price on spot exchanges. This move is partially explained by the cascading liquidations that took place, creating a backlog of large sell orders unable to find liquidity at reasonable prices.
The aftermath of the bloodbath resulted in futures perpetual contracts trading at a 12% discount versus regular spot exchanges. BitMEX, the largest derivatives market at the time, went offline for 25 minutes, causing havoc as investors became suspicious about its liquidity conditions.
By comparing this event with the most recent week, one will find that sustainable price discrepancies are very unusual. Even a temporary 12% gap doesn’t occur, even during the most volatile hours.
Take notice of how the perpetual contracts reached a peak 4% discount versus regular spot exchanges on May 13, although it lasted less than five minutes. Market makers and arbitrage desks could have been caught off guard but quickly managed to recoup liquidity by buying the perpetual contracts at a discount.
To understand the impact of those crashes on professional traders, the 25% delta skew is the best metric, as it compares similar call (buy) and put (sell) options’ pricing. When market makers and whales fear that Bitcoin’s price could crash, they demand a higher premium for the neutral-to-bearish put options. This movement causes the 25% delta skew to shift positively.
The above chart displays the mind-blowing 59% peak one-month Bitcoin options delta skew in March 2020. This data shows absolute fear and an incapacity to price the put (sell) options, causing the distortion. Even if one excludes the intraday peak, the 25% delta skew presented sustained periods above 20, indicating extreme “fear.”
Over the past week, the skew indicator peaked at 14%, which isn’t very far from the “neutral” -10% to +10% range. It is indeed a striking difference from the previous months’ negative skew, indicating optimism, but nothing out of the ordinary.
Therefore, although the recent 29% price drop in seven days could have been devastating for traders using leverage, the overall impact on derivatives has been modest.
This data shows that the market has been incredibly resilient as of late, but this strength might be tested if Bitcoin’s price continues to drop.
The views and opinions expressed here are solely those of the author and do not necessarily reflect the views of Cointelegraph. Every investment and trading move involves risk. You should conduct your own research when making a decision.
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