What Proof Is

Proof is a derivatives exchange with two layers. The first is a set of ordinary perpetual futures — leveraged contracts on assets, each trading on its own central limit order book, with no expiry and the usual funding mechanism that keeps the contract tethered to its underlying. If you have traded perps before, this layer will be familiar. The second layer is what makes Proof distinct: conditional markets, which let you trade an asset conditioned on whether a real-world event happens, alongside a market on that event's probability itself. You can take asset-level exposure that only fires if a specific event resolves the way you expect — and if it resolves the other way, the position is simply voided and your margin returned, with no loss to absorb. Both layers run on the same matching engine and share one cross-margined collateral pool, so a perpetual and a conditional position offset each other for margin inside a single account.

Why conditional markets are different

Most trading tools force a choice between the asset and the event. A perpetual or future gives you clean asset exposure, but against every move — not just the one you care about, and it stays just as expensive to hold when an unrelated catalyst moves the price against you. A prediction market gives you the event, cheaply and with clean price discovery, but it pays in dollars that sit outside your trading account and tell you nothing about how far your asset actually moves if the event happens. Options pay on movement over a window, which is not the same thing as a specific outcome — you can be right about the event and still lose on premium if the realized move was moderate or landed outside the expiry.

A conditional market closes that gap. From one underlying perpetual and one binary event, Proof creates a linked set of order books — a family — that prices the asset and the event together:

• A conditional perpetual for each outcome. The YES conditional perpetual is the underlying asset if and only if the event resolves YES; the NO conditional perpetual is the asset if it resolves NO. Each trades on its own book at its own price, carries leverage like an ordinary perpetual, and behaves like one while the event is open.
• A prediction binary for each outcome — a simple instrument priced between $0 and $1 whose price is the market-implied probability of that outcome. It pays $1 if its outcome wins and $0 if it loses.

Three properties make this family behave very differently from a stack of separate instruments:

1. Voiding, not loss. When a conditional perpetual's branch does not win — the other outcome resolves, or the event turns out to be unresolvable — the position is voided rather than settled to a loss: its profit-and-loss is zero and your margin is returned, while the winning branch cash-settles to the underlying's mark. This is the single most misunderstood property of the product, and the full mechanic — voiding, the three resolution outcomes, and how each leg pays — is in Settlement, Resolution & Void.

2. One price for the event, one for the impact. The prediction binary's price gives you the event probability p directly. The two conditional perpetuals give you the conditional impact — how far the underlying's expected price differs between a YES outcome and a NO outcome. That conditional impact is precisely the quantity a plain prediction market forces you to estimate yourself; here the market discovers it for you.

3. Real capital efficiency from cross-margin. Because the whole family shares one collateral pool, genuinely offsetting positions cost almost nothing to hold. A fully matched hedge — long the YES conditional perpetual, long the NO conditional perpetual, short the underlying — has a payoff that is locked in every outcome, so the engine charges it essentially zero margin, rather than full margin three times over. That efficiency is what makes hedging a specific event worthwhile instead of prohibitively expensive.

The books in a family are linked not because the engine forces their prices into line — it does not — but because their fair values are tied together by no-arbitrage relationships, and because they settle against the same event and the same underlying. The two that matter most: the underlying forward equals the probability-weighted blend of the two conditional prices, F = p·CY + (1 − p)·CN; and the two prediction binaries sum to about a dollar, BY + BN ≈ $1. These are relationships that hold between fair prices, not rules the exchange imposes; arbitrage, not the matching engine, keeps the family coherent.

What this documentation covers

This corpus explains how Proof works — conceptually, at the level of the design and the math behind it. It is for traders, integrators, and partners who want to understand the product deeply enough to use it well and reason about its risks. It is not an integration guide: there are no endpoints, payloads, code samples, wire formats, or error codes here. Those live in a separate integration reference. Everything in this corpus is plain English, inline math, and short worked examples.

The documents layer from the concrete to the abstract:

• Market structure and instruments — what trades on Proof: the order book model, the perpetual, and the full conditional-market family and how its books fit together. The natural starting point after this overview.
• Settlement, resolution, and voiding — how an event resolves YES, NO, or unresolvable; how the winning branch cash-settles and the losing branch voids; and the early-exit path for getting out before resolution.
• Oracles and mark prices — where prices come from, and why Proof keeps two separate reference prices (one for margin and liquidation, one for funding) that can diverge by design.
• Funding — the periodic long/short payment that tethers a perpetual to its underlying, and why it applies to perpetuals only and never to the conditional legs.
• Pricing — a sequence of documents building from the core idea that each conditional perpetual is fair at its conditional expectation (not the plain forward), through the spread between the YES and NO legs and what drives it, to how the prediction binaries reveal probability, and how arbitrage holds the family's five books coherent.
• Cross-margin and conditional-market margin — the portfolio margin model that checks your solvency across event outcomes, and how it treats conditional positions.
• Liquidation and backstops — what happens when an account falls below maintenance margin, and the layered loss-absorption design behind the exchange.
• Trading and strategy — how the pieces come together in practice, framed conceptually.
• Glossary and notation, and an about note on the documentation itself.

How to read the rest of the corpus

A few conventions run through every document, worth knowing up front:

• Conditional markets is the umbrella term for the whole product area, used everywhere. The five-book set built from one underlying and one event is a family; its outcomes are branches (YES / NO); a single book is a leg.
• A small, consistent notation recurs: F the underlying forward, p the YES probability (also the YES binary's price), Δ the impact (the spread between the two conditional prices), CY / CN the YES / NO conditional perpetual prices, BY / BN the YES / NO binary prices, σ / ρ volatility and correlation, and IM / MM initial and maintenance margin. (In this corpus MM always means maintenance margin, never "market maker.") Each symbol is reintroduced the first time it appears in a document, so any doc stands on its own.
• No-arbitrage identities are relationships, not guarantees. Wherever you see F = p·CY + (1 − p)·CN, BY + BN ≈ $1, or similar, read them as how fair prices relate — held by arbitrage, not enforced by the engine.
• Numbers are illustrative. Any worked figure is an example chosen to make a mechanism concrete, not a live or canonical value.

You can read straight through from here, or jump to whichever document answers your question — each is written to stand alone. If you are new to Proof, the most direct path is this overview, then market structure and instruments, then settlement, then the margin documents; pricing and trading go deeper for readers who want the reasoning underneath. Two things are worth carrying into everything else, because they correct the most common misconceptions: a losing conditional perpetual is voided with margin returned, not a loss to zero, and a hedge built from a conditional perpetual holds in the branch where that perpetual fires — so the standard practice is to plan for the post-resolution position you want and to flatten or fully box ahead of resolution.