Reviewing the amazing performance of this 50x leverage whale on Hyperliquid: five battles, five victories, earning $15 million in just 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 the HLP mechanism drag down the ecosystem? Could the issues with HLP be repeated 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 game between Hyperliquid and whales?" 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 issues when faced with high-leverage funds entering the market. Especially during a bear market, when the volume of funds decreases, the platform becomes more susceptible to manipulation. The key issue reflected in this incident is how to improve its mechanisms.

Currently, the platform's response is to lower the maximum leverage for BTC and ETH, reducing BTC from 50x to 40x and ETH from 50x to 25x. However, this does not fundamentally prevent similar incidents from happening again. Attackers can still operate in batches through multiple addresses to attack the HLP fund 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 positions were in profit, he withdrew the profit portion from the margin, so even if he faced liquidation, it would not result in actual losses. Ultimately, the platform took over through forced liquidation, causing the vault to bear 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 a rule 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. I observed that even during some periods of liquidation, the account remained in a profitable state.

Looking back at similar cases in centralized exchanges, such as when SBF helped CZ liquidate large orders, there is a background 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 is not much problem 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 fundamentally differs from centralized exchanges and limits risk control capabilities. HyperLiquid's mechanism is currently not suitable for handling large amounts of funds, especially under the premise of complete data transparency, making it easy to be manipulated by larger funds, amplifying slippage and liquidation risks.

Analogous to poker, if your opponent's capital far exceeds yours and they can see your hole cards, the game becomes extremely unbalanced. The lack of protective mechanisms on-chain allows strategic large players to easily suppress small and medium 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 transparency and compliance.

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

On the controllable side, the platform has not set sufficient risk exposure limits, and the hedging mechanisms are also inadequate. The platform should avoid systemic risks by limiting leverage scales and implementing dynamic margin requirements.

On the uncontrollable side, the openness of on-chain trading and the difficulty in 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 undergo during the transition between bull and bear markets.

Jt Song: I believe this incident reflects that current on-chain products are still in their early stages from a macro perspective. 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 quickly stop losses.

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 trading becomes mainstream in the future, forming a "transparent to transparent" ecosystem, such issues may alleviate. At the current stage, the advantages of whales are still evident.

2. Host Ray: Is the current game relationship between whales and platforms a zero-sum game, or can they promote each other's 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, as HyperLiquid gathers a lot of smart money and whale funds.

The relationship between whales and platforms is not necessarily antagonistic. For whales, HyperLiquid is one of the few places that allows 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 profit expectations and even cause harm. Whether it is a win-win situation depends on whether the platform's mechanisms 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 is certainly 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 placement behavior of whales itself triggers tracking by other users, creating a market around their trading behavior.

This incident is more about the whale discovering vulnerabilities in the platform's mechanisms and achieving low-risk arbitrage. Their hedging ability is extremely strong, and they may even operate across multiple platforms.

From an ecological perspective, the activity of whales is beneficial for increasing the activity and exposure of on-chain platforms. However, if whale behavior leads to sustained losses for HLP, affecting the platform's survival, then the game itself will come to an end. Therefore, the design of platform mechanisms 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 that such whale hunting actions 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 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 "overt and covert" strategies can easily maximize benefits.

Therefore, whale hunting actions may backfire, inadvertently helping whales offload their positions off-chain; it is a double-edged sword.

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

Similar situations have occurred with GMX, for example, when YFI doubled in a short time at the end of 2023, a whale opened long positions on GMX and coordinated with off-chain funds to pump the price, ultimately leading to significant losses for the platform.

So the issue is not whether users are acting maliciously, but whether the platform's design is robust enough. If the platform's mechanisms 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 performance and response speed of the chain, making DEX product functions stronger and operations more stable, thereby increasing 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, allowing for intervention.

In the future, it may be considered to use 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 tried to expand to more chains in the past to increase revenue, but the actual effect has been poor. The multi-chain strategy has led to increased maintenance costs and dispersed trading volume, which has not resulted in higher returns.

Additionally, a number of products with "disruptive innovation" have emerged, such as GMGN, Phantom, and Pepeboost, which have directly changed user interaction patterns 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 simply imitating CEX. Especially under the current geopolitical and regulatory context, CEX itself is facing increasing restrictions, providing DEX with opportunities to surpass in certain areas.

Danny: The core lesson DEXs can learn from CEXs is their counter-cyclical ability. CEXs have spot trading during bull markets and contract trading during bear markets, which smooths out their income. In contrast, most DEXs lack trading volume during bear markets, resulting in poor counter-cyclical capabilities.

The solution is through business integration. For example, bundling 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 gamified trading into DEXs.

The second point is capitalization. If a DEX can successfully raise funds at market peaks, integrate projects within its ecosystem, and expand revenue sources, it will have a better chance of withstanding bear market pressures and even surpassing some centralized second-tier exchanges.

For instance, Jupiter continued to raise funds during its business peak and sought to acquire and integrate ecosystem 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 already seen significantly higher trading volumes than in the last cycle. The overall growth trend for DEXs is clear.

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

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

The second category is aggregators, like 1inch and Jupiter, which consolidate liquidity sources from multiple DEXs.

The third category consists of trading products aimed at end-users, such as Trading Bots, Pepeboost, and GMGN, which directly serve end users and emphasize usability and participation.

A core driving force 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 boost on-chain activity.

CEXs also attracted traffic in their early stages by actively listing high-volatility assets. For instance, Binance created a wealth effect by listing mid-tier tokens to gain user trust. Now, the price discovery process for assets is gradually shifting to being front-loaded 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 the innovative models, potential trends, and narrative explosion paths they have observed to predict the next breakthrough point in on-chain trading. This breakthrough may manifest in product forms, asset types, chain architectures, or new logic from a new chain.

Jarseed: I'll throw out a direction for discussion. Currently, when trading small tokens on-chain, many scenarios only allow for one-sided trading (i.e., buying) and do not permit shorting. If a mechanism could emerge in the future that allows users to participate in shorting new assets early on, such as through borrowing tokens or contracts to establish short positions, it would greatly enrich the gamified structure.

Of course, such a mechanism would require extremely high risk control capabilities, as new asset prices can be highly volatile and risky. However, whoever can establish solid risk control in this area will find these products both market-attractive and with significant profit potential. I believe this is one of the important evolutionary directions for on-chain trading.

Sean: At EVG, we have recently focused on several independent narratives that center around "specialized chains." We have invested in Berachain and are optimistic about projects like Celestia. Their commonality lies in addressing structural issues in specific scenarios.

For example, HyperLiquid focuses on trading; Berachain emphasizes the stability of liquidity proof; 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 it must be technically permissionless, self-custodial, and contract trustworthy. 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 integrate with AI and achieve upgrades 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 the asset but can also customize and continuously train this AI model, even integrating it with the Twitter API to automate social behaviors. 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, offering competitive costs while achieving a balance between on-chain transparency and high-performance computing. We aim to promote the on-chaining of AI data and execution processes, enhancing traceability and security across the industry and addressing issues like "AI hallucinations."

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

The directions mentioned earlier are all 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 by boosting their development from the perspectives of liquidity, resources, and market.

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。