Forecast Market Sparks a Storm: Hyperliquid Challenges Polymarket and Kalshi

Kao Zhu, Golden Finance

Summary

On April 30, the decentralized cryptocurrency exchange Hyperliquid is currently proposing to add a prediction market feature to its platform, directly competing with Kalshi and Polymarket. The proposal, numbered HIP-4, is currently in public testing and will allow users to trade bets on the outcomes of real-world events on the Hyperliquid platform.

Existing prediction platforms such as Kalshi and Polymarket will gain a new rival—Hyperliquid is also moving into prediction markets. At present, Hyperliquid has already published the fee structure for its outcome tokens. These tokens are the assets that support prediction market trading on its platform. This move indicates that the launch of the prediction market is imminent.

1. Hyperliquid prediction market fee structure

According to Hyperliquid’s official website:

Fees are calculated based on your rolling trading volume over the past 14 days, and settled at the end of each UTC day. Trading volume from sub-accounts is included in the main account, and all sub-accounts share the same fee tier. Vault trading volume is calculated separately from the main account. Referral rewards apply to users whose first trading volume reaches $1 billion, and referral discounts apply to users whose first trading volume reaches $25 million.

Maker rebates will be continuously paid to each transaction’s wallet. Users can claim referral rewards on the “Referral” page.

The fee standards for perpetual contracts and spot trading are different. Perpetual contract trading volume and spot trading volume are combined to determine your fee tier, and spot trading volume is counted at a 2x ratio toward your fee tier. For example: (14-day weighted trading volume) = (14-day perpetual contract trading volume) + 2 * (14-day spot trading volume).

For each user, all assets (including perpetual contracts, HIP-3 perpetual contracts, and spot) are subject to the same fee tier. When HIP-3 deployers enable growth mode, protocol fees, rebates, trading volume contributions, and L1 user rate limit contributions will be reduced by 90%. HIP-3 deployers can configure an additional fee split between 0-300% (0-100% in growth mode). If the split percentage exceeds 100%, protocol fees will also increase to equal the deployer’s fee.

For spot trading pairs between the two spot quote assets, the taker-side trading fees and the maker-side rebates and user trading volume contribution will be reduced by 80%.

Aligned quote assets are eligible for a discount of 20% on taker-side fees, an increase of 50% on maker-side rebates, and an increase of 20% on trading volume contribution.

In most other protocols, the primary beneficiaries of trading fees are the team or insiders. In the Hyperliquid protocol, all fees are owned by the community (including HLP, the aid fund, and deployers).

2. What is HyperLiquid HIP-4 outcome trading?

HIP-4 is an upgraded version of HyperLiquid “result trading.” Essentially, it is equivalent to on-chain binary options. It introduces fully collateralized contracts that settle within a fixed price range, thereby enabling a profit structure similar to prediction markets and options. These outcome contracts bring a new way to trade derivatives, which can be combined with portfolio margin and HyperEVM, while eliminating nonlinear returns, expiring contracts, leverage, and forced liquidation.

One of the biggest innovations of HIP-4 is full collateralization, which sharply contrasts with traditional derivatives. Its characteristics include: no leverage, no liquidation (no liquidation mechanism), maximum loss equal to the principal invested, and nonlinear profit structures. This makes prediction markets more like information games rather than games of price.

3. Comparison of HyperLiquid, Polymarket, and Kalshi

Although Hyperliquid, Polymarket, and Kalshi are all running prediction markets, they take different approaches.

1. Hyperliquid: Embed prediction markets into the derivatives system

As the latest entrant to the sector, Hyperliquid integrates prediction markets into its existing derivatives system. Through the Outcome contracts introduced by HIP-4, it is essentially closer to a standardized on-chain binary option—users are, in fact, trading financial contracts with a clearly defined payoff structure.

In Hyperliquid’s trading mechanism, it uses an order book model (meaning that the price is formed by matching real buy and sell orders, rather than calculated through algorithmic price curves). The benefit is that pricing is more precise and spreads are smaller, which is especially suitable for high-frequency trading and large-volume traders.

For details, see “Hyperliquid’s Art of Precision.”

And because of this, Hyperliquid’s target users are very clear: it does not try to attract everyone, but instead prioritizes those who are already active in the derivatives market. These users are accustomed to using leverage, performing arbitrage, and building complex strategies. For them, prediction markets are not entertainment tools, but a new dimension of trading.

2. Polymarket: An information consumption product

Polymarket chooses AMM (Automated Market Maker) as its core mechanism. This means users do not need to wait for counterparties to appear, and can complete trades at any time. For ordinary users, the ability to trade whenever they want is very important—it gives prediction markets a sense of immediacy similar to social media. However, this convenience comes at the cost of efficiency. AMM models often produce larger slippage when handling large trades, and prices may deviate from real market consensus. Therefore, Polymarket is more suitable for ordinary users to participate in, and not ideal for professional traders.

In addition, the predictions across different domains on Polymarket also give the platform a public voting attribute. Political elections, wars, and various social events often become hot prediction topics on Polymarket. Even followers can sometimes use Polymarket’s prediction results as a reference for real public sentiment.

3. Kalshi: A legally recognized financial product

Kalshi’s biggest difference from other prediction markets is that it has obtained regulatory approval, putting prediction markets in the “legal financial product” costume.

In terms of trading mechanics, Kalshi also uses an order book model and relies on professional market makers to provide liquidity. This keeps it aligned with traditional exchanges in terms of pricing efficiency and makes it easier for institutional investors to accept. Kalshi’s main users are hedge funds, macro traders, and other professional financial institutions. For them, prediction markets mean providing a new risk-hedging tool, not a place of entertainment.

Unlike Polymarket, due to regulatory constraints, Kalshi’s response to hot events is slower.

In short, Polymarket has the lowest barrier to entry and is best suited for ordinary users, and it can reflect information about public opinion. Kalshi emphasizes compliance and hopes to bring prediction markets into the existing financial system. Meanwhile, Hyperliquid is the latest to enter and wants to turn prediction markets into a financial module within existing derivatives markets.

4. The impact of Hyperliquid entering the prediction market

Hyperliquid’s entry into the prediction market marks the official shift of DeFi-native prediction markets into the mainstream stage of competition. Leveraging low fees and high transparency, Hyperliquid will attract traders from Polymarket and Kalshi, and may also pressure other platforms to reduce their trading fees. By integrating prediction markets into the DeFi derivatives ecosystem, it can not only lower the participation threshold for users, but also improve capital efficiency and expand the overall trading scale of prediction markets.

The biggest change may be to shift the prediction track from “public opinion polls” to “financial markets.” As mentioned above, prediction markets are often seen as platforms for polling public sentiment around political or macro events, and their prices mainly reflect emotions and public discourse. As derivatives platforms join, prediction markets will gradually acquire pricing functions similar to interest rate markets and futures markets.

Competition among these three will not stop at the product level; it will also become a battle over the evolution path of the next generation of prediction markets.