Author: danny (@agintender)
The asset deposit scale of CEX is 100 times that of DEX, and the trading volume is 10 times that of DEX. How does Hyperliquid ensure it is not led by the nose by Binance? Is it through a decentralized structure? Is it through algorithms?
When we talk about a "decentralized" exchange, what do we mean? Which parts exactly need to be "decentralized"? Assets? Matching? Price? Clearing?
Introduction: A Futures Storm Reveals the Centralization vs. Decentralization Debate
In March 2025, the JELLYJELLY contract triggered a market turmoil on Hyperliquid.
Within just a few hours, the contract price surged 429%, nearly triggering massive liquidations. If liquidated, short positions would be transferred to the on-chain liquidity pool HLP, causing millions of dollars in floating losses. The on-chain positions were on the verge of collapse, and the community was in an uproar. Meanwhile, Binance unusually launched a perpetual contract for JELLYJELLY overnight... It seemed about to be jointly crushed by CEX...
Just before the nuclear bomb was about to detonate, Hyperliquid validators urgently voted to intervene, forcibly delisting, closing positions, and freezing trades, immediately raising big questions about "decentralized" exchanges.
This incident not only became a heated debate in the crypto community but also exposed a core issue:
On a decentralized trading platform, what determines the price? Who ultimately bears the risk? Are algorithms truly neutral?
This article will use the JELLYJELLY incident as a starting point to analyze the algorithmic differences in index prices, mark prices, and funding rates across three platforms, and deeply explore the financial philosophy and risk transmission mechanisms behind them. You will see how different algorithms shape different trading styles, serve different types of traders, and determine whether you can survive the storm.
This is not just a technical dissection of a contract, but a philosophical contest in market order design.
To compensate for this shortcoming (Hyper lacks Binance's massive fund accumulation and arbitrage, and the price is likely not to return in a short time), three Hyperliquid-specific settings emerge:
The first is a terrifying funding rate that can reach 4% per hour in extreme cases, which is 96% per day, and the frequency and upper limit of funding rate collection do not change with asset fluctuations.
The second is that the funding rate is based on oracle price rather than mark price, which to some extent prevents price manipulation. Even in an extreme scenario where you control the in-platform price and there are no arbitrageurs to balance the price, the funding rate can gradually bring the price back.
The third is the funding rate collection frequency. Algorithmically, Hyperliquid's funding rate is calculated every 8 hours, but when collecting, it is indeed collected at 1/8 per hour. For example, if the 8-hour funding rate is 0.1%, then in the next hour, long positions will pay 0.0125% funding rate to short positions. This "small steps, fast run" approach accelerates the "speed" of price return, making up for the limitations of Binance's order book depth model.
In contrast, Binance's funding rate relies on a longer settlement cycle (usually 8 hours), calculating by simulating the impact of large market orders on buy and sell prices based on order book depth, and considering borrowing rates (fixed at 0.01%). Its design aims to provide smoother and more predictable funding costs for institutional investors and medium to long-term traders.
OKX's funding rate algorithm is relatively simple, calculated based on the price deviation of the best bid and ask prices, with a similarly long settlement cycle. Lacking comprehensive consideration of order book depth and borrowing costs leads to violent funding rate fluctuations, suitable for high-frequency and short-term aggressive strategies, but also bringing higher liquidation risks.
Hyperliquid has found its own balance between Binance's "market structure" and OKX's "market orientation" - based on a relatively smooth algorithm (order book depth and Premium), combined with high-frequency funding rate settlement and off-chain price feeding, supplemented by high funding rates in extreme cases, allowing in-platform prices to quickly return to market prices in extreme environments.
These algorithmic differences have profound impacts in actual trading. To add, these three algorithms provide a good edge for the HLP vault, thereby creating a positive cycle for HLP. A long article will be written later to explain the importance of HLP vault for Hyperliquid.
III. Algorithms Determine Destiny: Different Platform-Adapted Trading Strategies and Behind Financial Philosophy
[The rest of the translation continues in the same manner, maintaining the specified translations for specific terms.]On-chain Transparency: All transaction data and settlement processes are publicly recorded on the chain, aiming to eliminate the black box operations of centralized exchanges.
Market Behavior Feedback: Hyperliquid practices an institutional structuralist financial philosophy - even if the world is chaotic, as long as algorithmic rules are sufficiently transparent and immutable, a relatively "neutral" market order can be constructed. It attracts traders seeking to rebuild trust systems through verifiable code and distributed governance. However, the JELLYJELLY incident reveals the tension in this philosophy: although the marked price logic is intended to be tamper-proof, when the system faces an existential crisis, higher-level governance (validator node voting) can still intervene and override protocol behavior, indicating that "code is law" still needs to face the test of "human governance" in extreme situations.
In summary:
Binance: Designed for "institutional rationalists", with clear rules, suitable for stable capital growth.
OKX: Designed for "trading instinctivists", fast and fierce, suitable for gamblers and traders.
Hyperliquid: Designed for "on-chain structuralists", algorithm-first, suitable for on-chain arbitrage and extreme trading of large capital.
Conclusion: At the end of algorithms is the human heart
Price is the appearance of trading; algorithm is the order of trading. But whether it's Binance's institutional buffer, OKX's market behavior supremacy, or Hyperliquid's on-chain consensus, they essentially try to answer the same question: How do we trust an invisible market?
Some systems choose "stability" as an anchor, telling you the rules will never change; some systems choose "volatility" as an anchor, believing traders can always adapt to risks; and some systems try to write everything into on-chain contracts, no longer relying on people, but on transparent code, distributed nodes, and cold, hard formulas.
However, when the market is in an extreme situation, algorithms will exit, and humans must take the stage. The JELLYJELLY crisis tells us that even the most decentralized systems need a temporary "central bank" to take over positions; even the most neutral consensus cannot completely eliminate disputes about "justice". Ultimately, prices are not determined by "algorithms", but by who we choose to believe.
Perhaps we cannot design a perfect system, but we can design a system that continuously self-corrects in imperfection. Binance uses institutional buffers to manage uncertainty, OKX uses gaming to stimulate market vitality, and Hyperliquid tries to establish a new consensus through governance and transparency. There is no right or wrong here, only choices, after all, there is no perfect solution in this world.
In the future financial world, algorithms will continue to expand their territory. But we must recognize that every logic written into code casts a shadow of a value judgment.
You want freedom, but seek fairness when liquidated;
You want fairness, but want transparency when liquidated;
You want transparency, but want to control everything when liquidated.
What you ultimately chase is not price, but the illusion of order.
People must always be responsible for their own values.
Let us always maintain a heart of reverence for the market.
Be like a Fujian person
