Papertrade, a synthetic perpetuals platform built on Hyperliquid HyperEVM, has come under scrutiny over its 1,000x leverage setup, shared liquidity pool, and a design that turns trader losses into PAPER token emissions. Foresight News framed the issue in simple terms: can a system funded by losers and paying out winners keep working once it faces adversarial trading?
On day one, the platform saw a trade that quickly became the center of the debate. A professional trader first bought about 6,060 ETH, pushing price up 0.12% and immediately doubling the margin on a 1,000x long. About an hour later, the trader opened 30 short positions with a combined notional value of $297 million, then sold 6,590 ETH to push the market lower. The reported cost on the Hyperliquid side was about $52,000, while roughly $1.28 million was withdrawn on the Papertrade side. The article said the trader had nearly two years of trading history on Hyperliquid and used normal trading rails throughout the operation.
A shared USDC pool takes the other side of every trade
Papertrade launched on Oct. 10. According to the report, it has no order book, no market makers, and no funding rate. Every user trades against a shared USDC pool, while pricing is pulled directly from the midpoint of Hyperliquid’s best bid and offer.
After the incident, the community began to focus on whether the mechanism can hold up over time, especially the link between the liquidity pool and the PAPER token.
The article said the pool starts empty and is filled entirely by trader losses and liquidations. When users make money, profits are paid out from the pool. If the pool cannot fully cover those profits at that moment, the unpaid portion is placed into a queue and settled only after later losses refill the pool. Losing users, at the same time, receive PAPER tokens.
Based on the documentation cited in the piece, when the pool’s tracked cash balance is below $2 million, every $1 of loss mints 100 PAPER. Once the balance rises above that threshold, the mint ratio declines gradually according to a high-water-mark structure. PAPER can be staked to share protocol revenue, including a portion of profitable trades and any excess above the pool’s preset cap.
The team described the mechanism as turning liquidation into ownership. In that framing, losing traders receive a claim on future platform revenue and gradually become co-owners of the house. In theory, as long as most high-leverage traders keep losing, the pool keeps filling, PAPER holders keep receiving distributions, and the system keeps moving.
The model depends on losses arriving faster than profits
That is also where the criticism starts. The article argued that the model relies on a basic condition: there must be more losers than winners, and losses must arrive fast enough to cover profit redemptions. If large concentrated profits show up, especially through targeted extraction tied to external price moves, the pool can be drained quickly.
In the short run, the report said, that assumption may hold because most participants in high-leverage markets tend to lose. Early data partly supported that view. Estimated first-day net realized trader losses were put at $18 million to $30 million, staking rewards were estimated at about $10.3 million to $12.6 million, the team later said roughly $25 million had been distributed to stakers, and the liquidity pool at one point reached about $5 million.
Still, the article stressed that what the system needs is not a one-time stock of losses but a continuing cash flow. Markets do not supply fresh losers forever. Trend moves, professional traders, and targeted extraction can all flip inflows into outflows.
Before launch, Delphi Digital analyst tempest had already warned publicly about this point. According to the article, long-short wash activity could dilute airdrops going to real losing traders and inflate the appearance of loss inflows. That means the reported loss-flow figures may not be as strong as official numbers suggest.
The price move used in the trade under discussion was only 0.12%. The article then pushed the scenario further: if BTC or ETH were to move 1% to 2% in one direction and same-side positions started winning together, a pool of about $5 million would face a real stress test against notional exposure in the billions of dollars.
Profits can be closed, but excess gains wait in line
Beyond the question of whether the pool can keep paying, the platform’s queueing system has also drawn criticism.
The report said that because the liquidity pool starts from zero and depends entirely on later losses, the protocol returns a trader’s initial margin when a profitable position is closed. But if the pool does not have enough funds to cover the full profit, the excess amount enters a first-in, first-out queue and is paid only after later trader losses refill the pool.
The documentation explicitly states that the pool may show a negative balance in certain cases, and unpaid profits become public claims rather than instantly withdrawable balances.
This mechanism was amplified during the launch period. The platform expected heavy simultaneous trading and introduced queue priority rules. The team acknowledged that, under technical constraints, small notional orders could not receive exactly the same priority as large orders, otherwise the frontend could be overwhelmed by spam requests.
The team said the current queueing setup tries to maximize fairness within those limits. Community feedback, though, showed that some users experienced clear confirmation delays and priority differences on the first day. One complaint cited in the article summed it up this way: winners have to wait in a FIFO line for the next loser to be liquidated. In that view, profits look more like IOUs than exchange balances settled on demand.
The queue issue also overlaps with the market-manipulation debate. In its response, the team said position limits were initially set relatively loose because congestion was expected at launch, and the uncertainty in confirmation timing itself provided some natural resistance to manipulation. As traffic eased, the team began tightening position limits at both the on-chain and relay layers.
From a user perspective, the uncertainty creates two problems. One is that profits cannot always be withdrawn quickly, which affects capital turnover. The other is that if targeted extraction continues in an adversarial environment, the queue may lengthen and reduce the willingness of new users to join or keep trading.
The article argued that queueing is a direct consequence of bootstrapping a pool from zero. With no outside market makers and no pre-seeded capital, profit settlement can only depend on the pace of future losses. The mechanism may be self-sustaining in theory, but in live trading, confirmation delays, priority differences, and the risk of queue buildup all add friction.
Public data does not yet provide a full time series for queued liabilities. Even so, compared with centralized exchanges and other DEXs, the queue remains a major point of criticism. For a platform selling high leverage and zero slippage, settlement uncertainty can weaken the user experience advantage it is trying to claim over traditional perpetual venues. If queues persist or repeatedly stretch during volatility, trading retention and the efficiency of refilling the pool may both suffer.
The article reduced the problem to a simple loop. If the pool lacks funds, winners wait. If the wait gets longer, some users leave. If fewer users stay, fewer losses flow in. That makes the pool even harder to restore.
After farming and arbitrage, open interest fell from above $3.3 billion to around $400 million
The report also said that after launch, cumulative notional volume on the platform briefly exceeded $600 billion, while open interest surged above $3.3 billion.
According to the latest data on the official website cited in the article, open interest has now dropped to around $400 million, down about 88% from that level. The piece did not describe this as a simple cooldown. Instead, it argued that once the underlying mechanics were fully understood, professional studios and farming accounts extracted value from the liquidity pool and then exited quickly.
In the article’s telling, the earlier multibillion-dollar boom was supported by a low-risk hedged farming pipeline. In a market where losses mint rewards, real retail traders became the minority. Farming accounts did not need to care about direction. They could open neutral hedged positions through two accounts at the same price and size. Under extreme leverage, even a tiny move could liquidate one side, trigger the payout mechanism, and generate PAPER rewards at low cost, while the profitable side walked away with USDC from the LP pool.
The article described this as a structure that effectively treated the protocol-backed liquidity pool as an unconditional cash machine. Once those participants drained the initial pool and withdrawals were pushed into long payout queues, the economics of the farming game changed as well.
How Papertrade interacts with Hyperliquid
Papertrade is built on HyperEVM and prices directly from Hyperliquid’s BBO. The article said Papertrade’s trading activity consumes Hyperliquid block space and liquidity attention. If it keeps attracting demand for extreme leverage, it could divert some users who might otherwise trade on Hyperliquid itself.
On the other hand, if the protocol’s model and risk controls keep showing weakness under repeated testing, the article said it may end up as a marginal niche product.
The original piece ended with a disclaimer that markets carry risk and the article does not constitute investment advice. Readers should decide for themselves whether the views or conclusions fit their own circumstances and bear responsibility for any investment decisions made on that basis.
