The model where losers fund the gains of winners may face its ultimate test in the near future.

Written by Ma He, Foresight News

An on-chain casino with a maximum 1000x leverage offering saw $1.28 million siphoned off on its launch day, with the exploiter only putting up $52,000 in capital.

This incident took place on Papertrade.

That very night, a professional trader first purchased roughly 6,060 ETH to push the price up by 0.12%!，(MISSING)— instantly doubling the margin on their 1000x long positions. An hour later, they opened 30 short positions with a combined notional value of $297 million, then sold off 6,590 ETH to drive the price down. They incurred approximately $52,000 in costs on the Hyperliquid side, and extracted roughly $1.28 million from the Papertrade side. This trader had nearly two years of transaction history on Hyperliquid, and all of their trades during this exploit went through the platform’s standard transaction channels.

Winners Siphon Value, Losers Supply Capital

Papertrade is a synthetic perpetual contract platform built on Hyperliquid’s HyperEVM, which launched on October 10. It features no order book, no market makers, and no funding rate: all users bet against a shared USDC liquidity pool, with prices directly pulled from the mid-price of the best bid and ask on Hyperliquid’s order book.

Following this incident, the community has gradually begun to realize there is significant uncertainty around the long-term viability of the protocol’s "losses as mining rewards" model.

The core and most controversial design of PaperTrade is the binding relationship between its liquidity pool (LP) and the PAPER token.

This pool starts completely empty, and is filled entirely by realized losses or liquidations from traders. When users earn profits, the payouts come directly from the pool; if the pool does not hold enough capital to cover payouts at a given time, excess profits are placed in a queue, to be settled once subsequent trader losses refill the pool. In exchange, users who incur losses receive PAPER tokens.

According to the protocol documentation, when the pool’s tracked cash balance falls below $2 million, 100 PAPER tokens are minted for every $1 of losses incurred. Once the balance exceeds this threshold, the minting ratio gradually decreases based on the high water mark. PAPER tokens can be staked to share in the protocol’s revenue, which includes a percentage cut from profitable trades, as well as any excess capital in the pool above its predefined cap.

The team describes this mechanism as "turning liquidations into ownership": losers receive a share of the platform’s future returns while incurring losses, effectively gradually becoming co-owners of the platform’s house. In theory, as long as the majority of high-leverage traders continue to lose money, the pool will be continuously refilled, PAPER holders will receive dividend payouts, and the system will remain operational.

However, the core point of controversy is whether this model can remain stable over the long term in an adversarial environment. It relies on a core premise: the volume of losing traders must exceed the volume of winning traders, and the rate of losses must be sufficient to cover profit payouts. If concentrated large-scale profits occur (such as targeted extraction achieved by manipulating external price feeds), the pool will be rapidly depleted.

On top of that, the dynamic that most participants in high-leverage markets are destined to lose money, driven by basic human nature, is likely to hold true in the short term. Early data from the platform’s launch partially validates this point. Data shows that traders’ net realized losses on the first day were estimated to fall between $18 million and $30 million, while stakers received rewards ranging from $10.3 million to $12.6 million. The official team later stated that roughly $25 million in rewards had been distributed to staking users, and the liquidity pool size at one point reached approximately $5 million.

Yet sustaining this continuous inflow of losses is fraught with uncertainty: the model requires losses to be a perpetual cash flow, rather than a static stock of capital. But the market will not perpetually supply new losing participants in perpetuity. Trending price moves, professional traders, targeted value siphoning — any one of these factors could one day turn the pool’s net inflow into an outflow.

Before the protocol launched, Delphi Digital analyst tempest publicly warned about this exact risk: circular long-short wash trading would dilute the airdrop rewards received by genuine losing traders, and inflate the apparent metrics of "loss inflows" into the pool. As a result, the protocol’s reported loss inflow figures may not be as high as the official numbers claim.

The price movement leveraged in this exploit was only 0.12%!。(MISSING)

If BTC or ETH ever moves in a one-sided trend of 1%!—(MISSING)2%!的(MISSING), causing all position holders on the winning side to turn a collective profit, the $5 million liquidity pool will face its true stress test against notional exposures running into the billions of dollars, when the payout queue is finally put to the test.

Beyond the question of whether the protocol can sustain payouts, its queue system has also drawn widespread criticism from the community.

Profit Payouts Require Queueing

Because the liquidity pool launches from zero, and is filled entirely by subsequent trader losses, the protocol immediately returns a user’s initial margin when they close a profitable position. But if the pool’s current capital is insufficient to cover all accrued profits, the excess amount enters a queue, processed on a first-in, first-out (FIFO) basis to be settled once losses from subsequent traders are added to the pool.

The protocol documentation explicitly states that the pool is allowed to hold a negative balance under specific scenarios, and unsettled profits become public claims, rather than immediately withdrawable balances for users.

This mechanism was particularly visible in the platform’s early launch phase. Expecting large volumes of concurrent user trades, the platform implemented a queuing priority system. The official team acknowledged that, under technical constraints, small notional value orders cannot receive the exact same priority as large orders — otherwise the front end would be vulnerable to congestion from high volumes of spam requests.

The team stated that the existing queuing mechanism is designed to maximize fairness within existing constraints, but community feedback shows that some users experienced noticeable confirmation delays and priority discrepancies on the platform’s first day.

Some users complained that "winners have to wait in a FIFO queue to withdraw, waiting for the next loser to get liquidated", arguing this is more like issuing IOUs against unrealized accounting profits, rather than an exchange offering immediate settlement.

Queuing issues overlap with controversies around price manipulation. In their official response, the team noted that position limits were set relatively loose in the early launch phase due to expected congestion, and the inherent uncertainty around transaction confirmation times for the queue itself acts as a natural defense against manipulation. As user traffic has declined, the team has begun tightening position limits at both the on-chain and relayer levels.

But from a user perspective, the uncertainty of the queuing system creates two key impacts: first, profits cannot be withdrawn in a timely manner, which disrupts capital turnover; second, in an adversarial environment, if targeted extraction continues, the queue will likely lengthen, further reducing new users’ willingness to join and continue trading.

From a mechanism design perspective, queuing is an inevitable outcome of the pool’s "zero bootstrap" structure: with no external market makers or pre-seeded capital, profit payouts can only depend on the pace of incoming trader losses. This is theoretically self-sustaining, but in actual operation, confirmation delays, priority discrepancies, and potential queue backlogs all increase user friction.

Current public data does not yet provide a full time series of queued debt obligations, but this feature remains a major pain point compared to centralized exchanges and other decentralized exchanges (DEXs). For a platform that markets itself on high leverage and zero slippage, settlement uncertainty may erode its user experience advantage relative to traditional perpetual contract exchanges. If queues persist long-term or repeatedly lengthen during market volatility, this could impact the platform’s user retention and the efficiency of liquidity pool refilling.

If the pool holds insufficient capital, winners will have to wait in the queue; as queue wait times lengthen, some users may choose to leave, reducing the inflow of new losses, making it even harder for the pool to recover, and creating a vicious cycle.

When the first major market move arrives one day that causes the payout queue to build up, this "losers fund winners" assembly line will face its ultimate test.

Airdrop Farmer Arbitrage: Open Interest Plunges 88%!<(MISSING)

It took only a few days for the platform to go from grand, lofty narratives to total operational chaos.

After the protocol officially launched, the platform’s cumulative notional trading volume at one point crossed the eye-popping threshold of $600 billion, while open interest (OI) skyrocketed to over $3.3 billion.

However, according to the latest data from the platform’s official website, its OI has now cliff-dived to around $400 million, representing a blood loss of approximately 88%!。(MISSING) This is far from a simple market cooldown: it is a classic "locust plague" pattern. Once the underlying mechanism loopholes were fully mapped out, professional trading teams and airdrop farmers extracted maximum value from the liquidity pool, then rapidly exited, leaving behind a stark liquidity vacuum.

Driving this multi-billion-dollar false boom was the risk-free "wash trade for token minting" arbitrage pipeline. In this 1000x leverage zero-sum playground built on the "losses as mining rewards" model, genuine retail traders became the minority, while airdrop farmers had no concern whatsoever for long or short direction. They used dual accounts to open neutral hedge positions at identical prices and equal sizes. Under extreme leverage, tiny price movements would cause the position on one side to be rapidly liquidated, triggering the payout mechanism to mint PAPER token rewards at extremely low cost. Meanwhile, the profitable position on the other side could exit without any risk, pulling real USDC capital directly from the LP pool.

This structural open secret of "moving funds from left hand to right hand" essentially treats the protocol’s backstopped liquidity pool as an unconditional ATM. When airdrop farmers drained the initial pool capital, pushing withdrawal payouts into endless queue wait times, the break-even point of this "token farming game" was breached.

Currently, PaperTrade is built on HyperEVM, with pricing pulled directly from Hyperliquid’s best bid and offer (BBO). Trading activity on PaperTrade consumes Hyperliquid’s block space and liquidity attention. But if PaperTrade continues to attract high-leverage trading demand, it may divert a portion of extreme leverage users who would otherwise trade on Hyperliquid. Conversely, if the protocol’s model and risk controls are repeatedly proven to be fragile, it may end up as a marginal, niche product.