Review of the Amazing Performance of This 50x Leverage Whale on Hyperliquid: Five Wins in Five Battles, Making $15 Million in 10 Days

He exited by "actively compressing the liquidation price," but caused the HLP vault to lose $4 million in 24 hours. This game between the whale and the platform has sparked heated discussions: Why is his strategy so precise? Will HLP's mechanism drag down the ecosystem? Will HLP's issues replay in CEX?

This week, ChainCatcher invited six leading VCs and researchers to discuss the theme "What is the Future of On-chain Trading Behind the Whale Game with Hyperliquid?" and explore the investment challenges and opportunities in a turbulent market.

For more details, please refer to X:

https://x.com/i/spaces/1zqKVjgRLvdKB

The following content is a summary of the Space in Chinese.

1. Host Ray: The 50x leverage whale on Hyperliquid caused the HLP vault to lose $4 million in 24 hours. What issues were exposed when the on-chain exchange was "exploited"?

Sean: Platforms like HyperLiquid do expose some structural problems when faced with high-leverage capital entering. Especially in a bear market, when the capital volume decreases, the platform is more susceptible to manipulation. The key issue reflected in this incident is how to improve its mechanism.

Currently, the platform's response is to lower the maximum leverage for BTC and ETH, from 50x to 40x for BTC and from 50x to 25x for ETH. However, this does not fundamentally prevent similar incidents from happening again. Attackers can still operate in batches through multiple addresses to attack the HLP liquidity pool. At this stage, the platform's mechanism cannot effectively defend against such premeditated operations.

Lucio: From this incident, the whale established a large number of long positions using 50x leverage and controlled a huge position with a small amount of capital, guiding market trends. When the position was in profit, he withdrew the profit portion from the margin, and even if he faced liquidation, it would not cause actual losses. Ultimately, the platform took over through forced liquidation, resulting in the vault bearing the liquidation losses.

The main issues are threefold: first, the allowed leverage is too high; second, the position limits are too low; and third, the liquidation price setting is too lenient. If the platform set it so that users opening 50x leverage would trigger forced liquidation at a 0.5% drop, the risk would be significantly reduced. Overall, this reflects the platform's vulnerabilities in product design and risk control mechanisms.

Jarseed: I tracked the whale's liquidation process throughout this incident. During some of the liquidation periods, the account was still in a profitable state.

Looking back at similar cases in centralized exchanges, such as when SBF helped CZ liquidate large orders, there are also backgrounds of high leverage operations. I believe the key issue reflected in the current incident is still in the design of leverage and margin mechanisms. For example, the platform's openness to leverage and the responsiveness of the liquidation process still have room for optimization. Overall, there are no major issues with the mechanism, but the details of risk control need to be strengthened.

Yuyue: I agree with the previous points. On-chain trading lacks a KYC mechanism, and the platform cannot ban addresses, which is fundamentally different from centralized exchanges and limits risk control capabilities. HyperLiquid's mechanism is currently not suitable for handling large volumes of capital, especially under the premise of complete data transparency, making it easy to be manipulated by larger funds, amplifying slippage and liquidation risks.

In comparison to poker, if the opponent's capital volume far exceeds yours and can see your hole cards, the game will be extremely unbalanced. The lack of protective mechanisms on-chain allows strategic large players to easily suppress smaller players and even the platform.

In contrast, centralized exchanges can hide key trading information for risk control, preventing malicious attacks. This is also the reason I have lowered my expectations for HyperLiquid; structurally, it is difficult to support higher volume trading activities.

In the future, it may explore some "hybrid" protective mechanisms, such as obscuring certain addresses or behaviors, but this will also bring challenges in terms of transparency and compliance.

Danny: This incident reveals both controllable and uncontrollable issues within the platform's mechanism.

On the controllable side, the platform did not set sufficient risk exposure limits, and the hedging mechanism is also inadequate. The platform should avoid systemic risks through measures such as limiting leverage size and dynamic margin requirements.

On the uncontrollable side, the public nature of on-chain trading and the difficulty of identifying abnormal behaviors due to the lack of KYC are challenges faced by all decentralized platforms. If this issue is not properly addressed in the future, it may affect compliance and large-scale user acceptance.

Overall, this is a testing phase that HyperLiquid, as a decentralized platform, must go through during the transition between bull and bear markets.

Jt Song: I believe this incident reflects from a more macro perspective that current on-chain products are still in the early stages. The biggest contradiction lies in balancing the decentralized concept with performance, security, and risk control.

Centralized exchanges can pause trading or modify parameters during a crisis, while on-chain products are limited by contract mechanisms, making their response speed and flexibility inferior to centralized platforms. Once a platform is attacked or arbitraged, it is difficult to stop losses quickly.

Moreover, excessive transparency has become a double-edged sword. When trading volume is still mainly concentrated on centralized exchanges, large funds on-chain can easily manipulate prices. However, if on-chain becomes mainstream in the future, forming an ecosystem of "transparency against transparency," such issues may alleviate. At the current stage, the advantages of whales are still evident.

2. Host Ray: Is the current game between whales and platforms a zero-sum game or can they mutually promote development? Can the community constrain whale behavior through collective action?

Sean: We can look back at the period from 2018 to 2019 when centralized exchanges began to offer contracts; many platforms were actually doing what HyperLiquid is trying to achieve now.

Theoretically, if CEX also had its own bot or HLP mechanism, its APY should be higher than HyperLiquid's because HyperLiquid gathers a lot of smart money and whale capital.

The relationship between whales and platforms is not necessarily antagonistic. For whales, HyperLiquid is one of the few places that allow maximum leverage and maximum capital exposure; for the platform, large orders from whales on-chain attract a lot of attention, creating a traffic effect.

However, for ordinary HLP users, the presence of whales may compress their expected returns and even cause harm. Whether it is a win-win situation depends on whether the platform's mechanism can be optimized. I suggest designing mechanisms from the perspective of market impact, such as setting a cap on the impact of orders on market prices and seeking decentralized, permissionless solutions. This may be a healthier win-win path.

Danny: I believe the operational behavior of whales is essentially similar to some people who shout orders on Twitter or operate on-chain. They attract market attention through trading, driving price fluctuations, while hedging their own risks in various ways to ensure they do not incur losses.

Such behavior must be profitable for whales; for the platform, the active behavior of whales can attract users and topics, creating positive traffic. So at this stage, it is a win-win situation. The platform, whales, and users all gain value at different levels.

Jarseed: I agree with the previous speakers. The order behavior of whales itself triggers other users to follow, creating a market around their trading behavior.

This incident is more about the whale discovering loopholes in the platform's mechanism and achieving low-risk arbitrage. His hedging ability is extremely strong, and he may even operate across multiple platforms.

From an ecological perspective, the activity of whales helps increase the activity and exposure of on-chain platforms. However, if whale behavior leads to sustained losses for HLP, affecting the platform's survival, the game itself will end. Therefore, the design of the platform's mechanism still needs improvement.

3. Host Ray: Some communities have proposed "whale hunting actions," hoping to counteract whales through collective hedging. Could this become an effective constraint mechanism?

Jt Song: I believe this whale hunting action may instead become part of the whale's strategy. For example, suppose I have a $100 million position on an exchange, and at the same time, I open a $5 million short position on HyperLiquid, enticing the community to target me, causing the price to rise by 5% and triggering my short liquidation.

On the surface, it seems the community has won, but in reality, my larger position on CEX profits far exceeds the losses on-chain. This combination of "open conspiracy + hidden conspiracy" can easily maximize benefits.

So whale hunting actions may backfire, helping whales complete off-chain sales; it is a double-edged sword.

Lucio: I believe the relationship between whales and platforms is fundamentally a game between users and the system. When there are loopholes on-chain, users will naturally exploit them; this is neither illegal nor against the rules.

Similar situations have occurred on GMX, for instance, when YFI doubled in a short time at the end of 2023, with whales opening long positions on GMX and coordinating off-chain funds to drive up prices, ultimately leading to significant losses for the platform.

So the issue is not whether users are malicious, but whether the platform's design is robust enough. If the platform's mechanism can withstand such operations, then even if whales arbitrage, it will not harm the system. As for whale hunting actions, I believe they are unrealistic. Community members have unequal knowledge, and strategies cannot be unified, making it easier for whales to exploit them in reverse.

4. Host Ray: Mainstream DEX revenues are declining: What is the root cause, and how can they break through in the future? Can CEX provide mature experiences for reference?

Jt Song: I believe there are two directions worth focusing on. The first is to enhance the chain's performance and response speed, making DEX's product functions stronger and more stable, thereby enhancing sustainability.

The second is to combine smart contracts with AI models to achieve smarter risk control. For example, when abnormal market conditions or attacks occur, the system can automatically adjust leverage ratios or identify malicious trades that exploit rules for arbitrage, thus intervening.

In the future, we can consider using AI for customized recognition of user behavior, providing personalized risk parameter settings. Such a platform system would be closer to the risk control efficiency of centralized exchanges while retaining the characteristics of decentralization.

Sean: I would like to share some reasons for the decline in revenue for mainstream DEXs. Uniswap has attempted to expand to more chains to increase revenue, but the actual effect has been poor. The multi-chain strategy has led to increased maintenance costs and dispersed trading volumes, which did not bring higher returns.

Additionally, a batch of products with "disruptive innovation" has emerged, such as GMGN, Phantom, and Pepeboost, which directly change user interaction modes and trading logic, diverting traffic and revenue from mainstream DEXs like Uniswap.

However, from a subjective perspective, the overall trading revenue on-chain during this cycle should be much higher than in the previous cycle, especially in areas like on-chain lending, bots, and contract DEXs. Therefore, not all DEXs are declining; rather, there is a clear differentiation in revenue among different types of products.

The key to breaking through in the future lies in innovative product design, rather than blindly imitating CEXs. Especially under the current geopolitical and regulatory context, CEXs themselves are facing increasing restrictions, providing DEXs with opportunities to surpass in certain areas.

Danny: The core lesson DEXs can learn from CEXs is the ability to withstand cycles. CEXs have spot trading in bull markets and contract trading in bear markets, allowing them to smooth out revenues. However, most DEXs have no trading volume in bear markets, resulting in poor cyclical resilience.

The solution is through business integration. For example, packaging contract-based on-chain gambling products or volatility products with aggregators to form a more complete trading ecosystem. Current on-chain projects like Manta and Merlin are already attempting to introduce speculative trading into DEXs.

The second point is capitalization. If DEXs can successfully raise funds at market peaks, integrating projects within the ecosystem and expanding revenue sources, they will have a better chance of withstanding bear market pressures and even surpassing some centralized second-tier exchanges.

For example, Jupiter has continued to raise funds during its business peak, seeking to acquire and integrate ecological projects, gradually expanding its influence.

Finally, in response to the data mentioned by Sean, based on my observations, Uniswap's trading volume is indeed lower than in the previous cycle, but platforms like GMX, Jupiter, and dYdX have seen their trading volumes significantly exceed those of the last cycle. The overall growth trend of DEXs is clear.

Jarseed: I would like to add from the perspective of product classification regarding the current evolution path of DEXs. They can be roughly divided into three categories:

The first category is the most basic DEXs, such as Uniswap and Raydium, which provide raw liquidity;

The second category is aggregators, such as 1inch and Jupiter, which consolidate liquidity sources from multiple DEXs;

The third category is trading products aimed at end users, such as Trading Bots, Pepeboost, and GMGN, which directly serve end users, emphasizing usability and participation.

One of the core driving forces behind this round of asset explosion is the emergence of new issuance mechanisms. For example, on Solana, platforms like Pump.fun have significantly lowered the barriers to token issuance, utilizing lightweight liquidity and rapid appreciation mechanisms to drive on-chain activity.

CEXs also used to attract traffic by actively listing high-volatility assets in their early stages. For instance, Binance created wealth effects by listing mid-tier tokens to gain user trust. Now, the price discovery process of assets is gradually being brought on-chain.

In the future, whoever can gain an advantage on the asset side will dominate the competitive landscape of DEXs.

5. Host Ray: Everyone is welcome to share their thoughts on innovative models, potential trends, and narrative explosion paths to predict the next breakthrough point in on-chain trading. This breakthrough may manifest in product forms, asset types, chain architectures, or new logic of a new chain.

Jarseed: I would like to throw out a direction. Currently, when trading small tokens on-chain, many scenarios can only perform one-sided trades (i.e., buying) and cannot short. If a mechanism could emerge in the future that allows users to participate in shorting early on new assets, such as through borrowing tokens or contracts to establish short positions, it would greatly enrich the game structure.

Of course, such a mechanism requires extremely high risk control capabilities because the price fluctuations of new assets are severe, and the risks are significant. However, whoever can solidify risk control sufficiently will find that such products are both market-attractive and have huge profit potential. I believe this is one of the important evolutionary directions for on-chain trading.

Sean: The independent narratives that my organization, EVG, has recently focused on are centered around "specialized chains." We have invested in Berachain and are optimistic about projects like Celestia. Their commonality lies in focusing on solving structural problems in specific scenarios.

For example, HyperLiquid focuses on trading; Berachain focuses on building the stability of liquidity proofs; Celestia provides modular block space support. The logic behind these projects is that Ethereum and Solana cannot comprehensively meet all scenarios, so in the future, chains with independent business structures will emerge to serve specific needs.

For an independent narrative to explode, it must meet several conditions: there must be a scenario with a strong demand pain point, a practical application product that can run, and technically achieve permissionless, self-custodial, and contract trustworthiness. If these conditions are met, it is not just an L1, but a decentralized platform with an independent business structure.

Jt Song: Our 0G chain is also working in this direction. As a decentralized AI chain, we believe that future asset issuance must be integrated with AI and upgraded based on existing logic.

One of our focuses is to launch a "smart NFT" standard that directly binds AI model training data or small models to NFTs. Users not only hold assets but can also customize and continuously train this AI model, even connecting it to the Twitter API for automated social behavior. In this model, AI not only participates in asset construction but also directly becomes part of the asset.

Additionally, our mainnet benchmarks against AWS on the storage layer, is competitive in terms of costs, and achieves a balance between on-chain transparency and high-performance computing. We hope to promote the on-chainization of AI data and execution processes, improving traceability and security across the industry, and addressing issues like "AI hallucination."

Lucio: My perspective is more execution-oriented. I am not very good at predicting what the next narrative will be, but I excel at identifying trends from data. Once a chain or product shows clear inclinations in user growth, popularity, and data performance, I will immediately pay attention and support it.

The directions mentioned earlier are very enlightening. Whether it is specialized chains, AI assets, or more professional on-chain contract platforms, as long as the data is good enough and user behavior is genuine, there is potential for an explosion.

For our institution, we are also willing to support such teams, boosting their development from the perspectives of liquidity, resources, and market.