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Topic cluster / Hyperliquid HIP-4 markets

How do Hyperliquid HIP-4 markets differ from perps?

Perps are open-ended derivative exposure. HIP-4 outcomes are binary-side assets with their own market metadata, so the contract definition, calendar, and side structure matter more than the usual perp habit of tracking one symbol and its funding.

What to remember

  • Time-to-expiry becomes a first-class feature.
  • Side-specific liquidity matters because the two sides are separate assets.
  • You should not assume perp concepts like funding translate cleanly.

At the API layer, they are different objects

Perp endpoints use the perp `meta` response and integer asset indices. By contrast, Hyperliquid's official outcome docs say outcome assets are built from an `outcome` id plus a binary `side`, with representations like `#<encoding>`, `+<encoding>`, and `100_000_000 + encoding`.

That is a useful signal for researchers: HIP-4 markets are not just one more perp namespace. They are a separate instrument family with their own identity scheme.

At the contract layer, they ask a different question

Hyperliquid's perp and hyperp docs revolve around continuous exposure, mark prices, and funding logic. The official `outcomeMeta` example instead centers on fields like `expiry`, `targetPrice`, and `Yes` or `No` side specs.

So the research object changes. One side of your work is no longer a continuous contract you can think about in the same way as a perp; it is a defined outcome question with dated terms.

What changes for traders and quants

The biggest mistake is to port perp intuition straight across. Outcome markets can still trade on the same venue, but the features you care about and the failure modes you watch are different.

  • Time-to-expiry becomes a first-class feature.
  • Side-specific liquidity matters because the two sides are separate assets.
  • You should not assume perp concepts like funding translate cleanly.

Why this matters for Alphora-style research

This is exactly the sort of surface where explicit metadata, forward testing, and run provenance matter. A clean chart is much less useful if you lost the actual market question the chart came from.