Prediction markets have long been slow, fixed payout venues with no leverage. HIP-3 changes that by running them on Hyperliquid’s perpetual futures rails with permissionless deployment, shared liquidity, and custom parameters. This allows binary or continuous outcomes on elections, macro data, sports, and more, traded with the same speed and capital efficiency as crypto perps.
The upside is clear. Combining the global liquidity of perps with the informational richness of prediction markets opens a new high frequency, multi event trading class. However, leverage on event markets is dangerous without structural safeguards, especially for binary outcomes.
Binary markets can jump from 0 to 100 at expiry, instantly wiping one side and forcing liquidations across the book. Without a natural hedge, market makers take direct event risk, and liquidations cannot be staged. Safe leverage without protections hovers near 1-1.5x.
In 2024 near the U.S. election, dYdX offered 20x leverage on a Trump win market by letting makers hedge in Polymarket’s liquid YES/NO contracts, backed by mature liquidations, a large insurance fund, and socialized losses. Even so, on election night the market spiked from about $0.60 to $1, draining liquidity mid liquidation and triggering random deleveraging into thin books. Hedging latency, sharp jumps, and vanishing depth resulted in losses for solvent traders.
HIP-3 currently lacks on venue hedgeable spot and these jump risk controls by default, so similar cascades are possible without built in protections.
A binary prediction perp on HIP-3 would use a BinaryHyperp contract with a 0 to 100 probability oracle. A tight clamp could ensure trading only occurring within the market’s bounds. If the oracle references Kalshi or Polymarket, LPs can hedge in those spot markets, reducing event risk and allowing more leverage. Risks remain including hedging delays, liquidity gaps, and funding basis divergence.
To scale beyond 1x for binary markets, structural controls are essential:
open_notional = OI × oracle_price
scaling_factor = (open_notional – lower_cap) / (upper_cap – lower_cap)
effective_margin = min(base_margin + max(scaling_factor × (1 – base_margin), 0), 1.0)
Together, OI based margin caps systemic exposure, bands stagger liquidations, and leverage decay reduces expiry tail risk.
Scalar markets settle to a range, such as CPI percent or BTC dominance, instead of 0 or 100. This materially reduces jump risk and supports higher leverage. Key advantages:
Incremental pricing also aligns naturally with HIP-3’s funding and margin logic, making scalar markets the safer near term wedge for adoption.
Keep core perp elements such as order book, depth chart, and leverage slider but add prediction-market-native components to the UI:
If markets hedge via external venues like Kalshi or Polymarket, flag this prominently.
Kalshi and Polymarket are curated, fixed payout, and unleveraged. HIP-3 can differentiate on:
This mix can attract professional LPs and active traders, allowing HIP-3 to serve both niche event markets and high volume global outcomes.
Currently, there are no major teams publicly working on HIP-3 prediction perps. This will soon change. With the right combination of design, liquidity, and permissionless market creation, HIP-3 can both complement and be an alternative to Kalshi and Polymarket.
Prediction markets are going to take the world by storm. The blockchain to house all of finance, is not going to miss out.
Hyperliquid.