How Whales Exploit the Timing and Conditions in Hyperliquid's $XPL Pre-Market Trading to Harvest Profits—Early holders hedge by shorting, creating 'crowded trading', ultimately triggered by 'ignition strategies'—this is not a coincidence of market fluctuations, but a systematic risk stemming from structural flaws in the pre-market.
The story begins with AI Aunt's tweet:
Original text:
https://x.com/ai_9684xtpa/status/1960506447965642864
This article does not evaluate the ins and outs of the XPL incident, but aims to discuss some structural and systemic risk points of the 'pre-market trading market'. Advantages in patterns also come with disadvantages; this is not about right or wrong, but aims to point out the risk points and their causes.
Section I: A New Paradigm: Pre-Market Trading
Pre-market trading (more accurately, 'Pre-Launch Trading') is centered around creating a synthetic market for a token that has not yet been issued or circulated publicly. This is not a response to existing asset information, but a pure price discovery process for future assets. The trading subject is not the token itself, but a type of futures, with some platforms being spot, others being forward OTC, and others being perpetual contracts.
This mechanistic shift fundamentally alters the nature of risk. The primary risks of traditional pre-market trading are illiquidity and increased volatility, but the existence and fundamental value of the asset are indisputable. However, the cryptocurrency pre-market introduces new dimensions of risk: first is settlement risk or conversion risk, meaning that the project may never issue tokens, leading to the market not being convertible to a standard spot or perpetual contract market and possibly being suspended or delisted.
Secondly, there is price anchoring risk. Since there is no external spot market as a price reference, the market price is entirely determined by the internal buying and selling behavior of the platform, forming a self-referential closed loop, making the market more susceptible to manipulation. Therefore, the innovation of cryptocurrency pre-market trading lies in creating a market from scratch, but the cost of this is the construction of a structurally weaker, more diverse risk environment.
It's not that everyone is unaware of this risk, but exchanges can gain traffic, market makers can achieve 'price discovery' in advance, and project teams/early investors can 'hedge risks'—under the premise of profits for many, everyone tacitly agrees to this arrangement (risk).
Section II: DEX Hedging is Like Juggling a Double-Edged Sword with Eyes Closed
2.1 Rational Hedgers: Why Early Holders Short Pre-Market Futures to Lock in Value
Before the TGE of a new token, early holders (including private investors, team members, airdrop recipients, etc.) face a common dilemma: they hold tokens or token entitlements that are not yet tradable or circulating, but the value of these future assets is exposed to significant market uncertainty. Once the tokens go live for trading, their prices may be far below expectations, leading to a substantial reduction in paper wealth.
The pre-market futures market provides an almost perfect solution to this dilemma. By shorting an equivalent amount of perpetual contracts in the pre-market, holders can lock in the future selling price of their tokens in advance. For example, an airdrop user expecting to receive 10,000 tokens can hedge risk by shorting 10,000 contracts at a pre-market futures price of $3. Regardless of the spot price at TGE, their total profit will be locked in at around $30,000 (ignoring transaction costs and basis). The essence of this operation is to create a delta-neutral position: the risk of their spot long (held airdrop) is offset by their futures short (shorting perpetual contracts). For any rational risk-averse person, this is a standard and wise financial operation.
2.2 The Formation of Crowded Trading: When Collective Hedging Creates Concentrated Fragility
When a large number of market participants trade based on similar logic, at the same point in time, using the same strategies, 'Crowded Trading' emerges. This risk does not stem from the fundamentals of the asset (exogenous risk), but from the high correlation of market participants' behaviors, making it an endogenous risk.
If you've seen that episode of ALPACA before, you know this operation is a 'market consensus'—with market consensus, there is direction; with direction, there are opportunities; with opportunities, there are games.
In the pre-market, this crowding phenomenon is structural and predictable. The nature of airdrops and early token distributions ensures that there is a large, homogeneous group (i.e., token recipients) who face the same risk exposure at the same time (prior to the TGE) and have the same hedging motives (shorting). Meanwhile, the group of speculators willing to take risks and buy these futures contracts is relatively small and dispersed. This inherent long-short imbalance inevitably leads to extreme crowding in the short direction, forming a typical crowded short.
The greatest danger of crowded trading lies in its fragility. Since the vast majority stand on the same side of the boat, once a catalyst forces them to liquidate (e.g., a price reversal), there will not be enough counterparties in the market to absorb these liquidation orders. This will trigger a 'stampede' to the 'exit', resulting in extreme, violent one-sided movements in prices. For crowded short positions, this stampede manifests as a devastating short squeeze. This tool originally used for risk management, due to its collective usage, creates a new and greater systemic risk point.
2.3 Identifying Imbalances: Detecting Crowded Conditions Through Data Analysis
Although individual traders cannot know exactly how many others hold the same positions, analyzing publicly available market data can effectively identify signs of crowded trading.
Open Interest (OI) Analysis: OI is a key indicator measuring the total number of outstanding derivative contracts in the market, reflecting the total amount of funds flowing into the market and market participation. In the pre-market, if OI continues to rise rapidly while prices stagnate or even slightly decline, this is a strong signal indicating that large amounts of funds are flowing into short positions, forming a bearish consensus, i.e., a crowded short is forming.
On-chain Data Analysis: Although the token has not circulated, analysts can track activities related to airdrops via blockchain explorers. By analyzing the number of wallets that meet airdrop criteria, the concentration of token distribution, and the historical behavior of these wallets, one can roughly estimate the total amount of 'spot' positions needing to be hedged. A large-scale and dispersed airdrop often indicates stronger hedging demand and higher crowding risk.
Funding Rate and Spread: On platforms like Hyperliquid with funding rates, a persistently negative and deepening funding rate is direct evidence of short dominance. On platforms like Aevo, although there are no funding rates, a continuously widening bid-ask spread and a significantly greater order book depth on the sell side compared to the buy side also reflect one-sided selling pressure.
This series of analyses reveals a profound phenomenon: the 'crowded hedging' in the pre-market is not an accident of market failure, but an inevitable product of system design. The airdrop mechanism creates a large group with unified motives, while the pre-market provides them with perfect hedging tools. Individual rational behavior (hedging risk) aggregates into a collective irrational state (an extremely fragile crowded position). This fragility is predictable, systematically concentrating a large number of risk-averse traders, creating a perfect prey pool for predators who understand and can exploit this structural flaw.
Short squeezes do not require reasons, narratives, or uses; rather, when funds reach a certain level, they attract whales and games—contract versions of holding treasure brings trouble.
Section III: Ignition Moment: Utilizing Crowded Trading and Triggering Chain Liquidations
3.1 Momentum Ignition: A Mechanism of a Predatory Trading Strategy
Momentum Ignition is a complex market manipulation strategy typically executed by high-frequency traders or large trading funds. Its core objective is not based on fundamental analysis but rather to artificially create one-sided price momentum through a series of rapid, aggressive trades, aiming to trigger preset stop-loss orders or liquidation lines in the market, and then profit from the resulting chain reaction.
The execution of this strategy usually follows an exact 'attack sequence':
Detection and Laying Groundwork: Attackers first submit a series of small, rapid orders to test the market's liquidity depth and create the illusion of growing demand.
Aggressive Ordering: Upon confirming insufficient market depth, attackers will strike the sell side of the order book with large market buy orders in a very short time. The goal during this phase is to quickly and violently push up the price.
Triggering Chain Reactions: A sharp price surge will hit the forced liquidation prices of many crowded short positions. Once the first liquidation is triggered, the exchange's risk engine will automatically execute market buy orders to close that short position, further pushing up the price.
Harvesting Profits: The initial attackers have established a large number of long positions during the first and second phases. When the chain liquidation begins, a massive influx of passive buy orders enters the market, allowing the attackers to reverse their operations and sell their long positions to these forced liquidated buyers, thus realizing profits at the artificially inflated prices they created.
3.2 Perfect Prey: How Illiquidity and Crowded Shorts Create an Ideal Attack Environment
The pre-market provides an almost perfect breeding ground for the implementation of momentum ignition strategies.
Extremely Low Liquidity: As mentioned, liquidity in the pre-market is extremely scarce. This means that attackers can have a significant impact on prices with relatively little capital. Manipulative actions that could be costly in mature markets with abundant liquidity become cheap and efficient in the pre-market.
Predictable Liquidation Clusters: Due to a large number of hedgers adopting similar entry prices and leverage ratios, their forced liquidation prices are densely clustered within a narrow range above the market price. This creates a clear, predictable 'liquidation cluster'. Attackers are very clear that they only need to push the price into this area to trigger a chain reaction. This is consistent with the logic of 'hunting stop losses' in traditional markets, where attackers specifically target known stop-loss clusters (via the liquidation map).
One-Sided Market Structure: Crowded shorts mean that during price increases, there is almost no natural buying power available to absorb the selling pressure from attackers. Prices can easily rise until they hit the 'wall' of the liquidation cluster. Once they hit it, passive buying due to liquidations becomes the 'fuel' pushing prices to continue rising.
3.3 Collapse: From Point Removal to Comprehensive Chain Liquidation
The entire process is a meticulously planned, phased collapse.
Short Squeeze: The initial price surge triggered by the momentum ignition strategy first triggers the liquidation of the first batch of highly leveraged, weakest short positions. The buying pressure generated by these forced liquidations further drives up the price, forming a typical short squeeze.
Chain Liquidation: The price pushed up by the first round of short squeezes now reaches the liquidation threshold for the second and third batches of short positions. This creates a vicious positive feedback loop: liquidations lead to price increases, and rising prices trigger more liquidations. The market enters an uncontrollable state, with prices surging vertically in a very short time, forming long upper wicks on the charts, known as 'liquidation candles'.
Ultimate Outcome: For early holders seeking hedges, their outcome is 'liquidation'—margins are exhausted, hedged positions are forcibly closed, resulting in huge financial losses. They not only lose the 'insurance' set up to protect the spot value but also pay a heavy price for it. Once chain liquidations have exhausted all available short positions and the attackers have completed profit harvesting, prices often quickly fall back to their initial levels, leaving devastation in their wake.
From a deeper analysis, the momentum ignition strategy in the pre-market has transcended simple market manipulation; it is more like a game among funds.
It is a structural arbitrage based on market microstructure flaws. Attackers utilize public information (airdrop scale), platform design (leverage mechanisms), and predictable group behavior (collective hedging) to calculate attack costs (the funds needed to raise prices in a low liquidity market) and potential profits (profits after triggering liquidation clusters), executing a near-certain gaming strategy. Their profits do not stem from accurately assessing asset value, but from the precise exploitation and amplification of market failures.
Knowing it exists and understanding why it does
May we always maintain a sense of awe towards the market.
