The Contract Algorithm Battle Between CEX and DEX: A Comparative Analysis of Hyperliquid, Binance, and OKX

In March 2025, the JELLYJELLY contract caused a market stir on a decentralized trading platform. Within just a few hours, the contract price surged by 429%, about to trigger a massive liquidation. If liquidation occurs, the short positions will be funneled into the on-chain liquidity vault, resulting in substantial floating losses. Meanwhile, a centralized exchange unusually and swiftly launched JELLYJELLY perpetual contract trading.

As the crisis is about to erupt, validators of the decentralized platform urgently vote to intervene, forcibly delisting, closing positions, and freezing transactions, raising doubts about "decentralized" exchanges.

This event has not only become the focus of heated discussions in the crypto community, but it also exposes a core issue: what determines the price on decentralized trading platforms? Who ultimately bears the risk? Is the Algorithm really neutral?

This article will use this event as a starting point to analyze the algorithmic differences in the core mechanisms of perpetual contracts among three major platforms, and to delve into the financial philosophies and risk transmission mechanisms behind them. We will explore how different algorithms shape trading styles, serve different types of operators, and influence traders' fates during market storms.

This is not only an analysis of contract technology, but also a contest of market order design concepts.

Overview of Perpetual Contract Trading

Perpetual contract trading is mainly composed of three key elements:

1. Index Price: Tracks the changes in the spot market price and serves as the theoretical benchmark.

2. Mark Price: The decisive price used for calculating unrealized profits and losses, liquidation, and other key events.

3. Funding Rate: An economic mechanism that connects the spot and contract markets, guiding the contract price to revert to the spot.

Controlling the Algorithm for the marked price gives one the power of life and death in contract trading. The core of a decentralized platform lies in ensuring that the marked price is not manipulated and is verifiable.

Comparison of Algorithms of Three Major Platforms

Index Price/Oracle Price

A certain decentralized platform uses oracle prices, constructed by validator nodes, employing a weighted median method to guard against extreme fluctuations, with an update frequency of once every 3 seconds. This design enhances resistance to manipulation but results in a slower update speed.

Mark Price Mechanism

The marking price Algorithm of a certain centralized exchange A is based on the median of the contract market's buy/sell one prices, transaction prices, and impact prices. The impact price simulates the effect of large market orders on the order book, reflecting the real liquidity cost. Combined with exponential moving average processing, it stabilizes the marking price changes, making it suitable for large capital stable allocation.

A certain centralized exchange B uses only the bid-ask midpoint as the source for the marking price, making it extremely sensitive to small trades, with high volatility but a fast price return speed, suitable for high-frequency and short-term trading.

A certain decentralized platform integrates multiple price sources: the oracle price and the exponential moving average of the price difference in contracts, the median of the buy and sell prices within the platform, and the weighted median of the perpetual contracts from multiple centralized exchanges. Validators are responsible for updating prices and conducting consistency verification, enhancing the resistance to manipulation.

Funding Rate Algorithm

A certain decentralized platform introduces a premium index based on the existing model, sampling every 5 seconds and calculating the hourly average to prevent short-term violent fluctuations. To compensate for the slow price regression, it adopts high funding rates of up to 4%/hour, calculated based on oracle prices, and frequently charges on an hourly basis.

The funding rate of a centralized exchange A relies on a longer settlement period of (8 hours ), calculated in conjunction with order book depth and lending rates, providing institutional investors with smooth and predictable funding costs.

The algorithm of a certain centralized exchange B is relatively simple, based on the calculation of price deviation from the order book, with significant volatility, making it suitable for aggressive strategies.

Trading Strategies and Financial Philosophy Adapted to Different Platforms

( Centralized Exchange A: Design of Rational Institutionalizers

• Core Concept: Make the Market Predictable
• Mechanism: smoothed mark price, refined funding rate model, multi-layer risk buffer
• Suitable for: Institutional investors and medium to long-term traders seeking stable returns.

) Design of Trading Instincts by a Centralized Exchange B

• Core concept: The market is a reflection of human nature.
• Mechanism: sensitive mark price, highly volatile funding rate, rapid liquidation
• Suitable for: high-frequency traders, short-term traders, adept at capturing instantaneous price deviations

A certain decentralized platform: Design of on-chain structuralists

• Core Philosophy: Algorithm sets order
• Mechanism: Validator consensus price, on-chain transparent settlement, high-frequency funding rate
• Suitable for: traders who pursue verifiable code and decentralized governance.

![The Contract Algorithm Battle between CEX and DEX: Hyperliquid, Binance, OKX]###https://img-cdn.gateio.im/webp-social/moments-d70c8e1b137a0ceb5f5ce4c36fb3ca7d.webp###

Conclusion

Different contract algorithm designs reflect different understandings of the essence of the market. Some systems pursue stability, some embrace volatility, and others attempt to establish new trust mechanisms through on-chain code. However, human intervention in extreme market conditions is still difficult to avoid, reminding us to seek a balance between algorithms and human nature.

In the future, algorithms will continue to profoundly influence financial markets. However, we must also recognize that every algorithm carries inherent value judgments. Regardless of the trading system chosen, traders need to take responsibility for their choices and maintain a respectful attitude towards the market.