Conditionals variants
Conditionals can be defined in two ways:
Event conditionals: branches are real-world outcomes (Cut / Hold / Hike, Approve / Reject, Beat / Miss).
Price conditionals: branches are terminal price ranges (bins) at a fixed expiry.
Both variants use the same underlying mechanics:
Shared collateral: one USDC deposit supports all branches simultaneously.
Deterministic resolution: non-realized branches are cancelled; the realized branch settles to the observed settlement value.
Scalar exposure: inside a branch, scalar long/short tokens give bounded linear exposure to the settlement price.
If you want the full token lifecycle, start with:
Event conditionals
Event conditionals are the first type of conditional on Butter. They can be considered an extension of event / prediction markets.
Definition
An event conditional market is defined by:
an event (e.g., FOMC decision, earnings release, election outcome),
an asset/datapoint (e.g., BTCUSD, SPX, CPI, a KPI),
and one branch per mutually exclusive event outcome.
Example branches for a Fed decision:
BTCUSD | Cut
BTCUSD | Hold
BTCUSD | Hike
What is being priced
Each branch price is the market’s forecast of the asset’s value if that outcome occurs.
This is the key difference vs other venues:
prediction markets price probabilities
options markets price volatility over time
conditionals price each branch of the future “as if it happens”
Settlement
Settlement occurs after the event resolves or when the market’s expiry date is reached (whichever happens first).
At settlement:
positions in unrealized branches are set to zero
only positions in the realized branch can be redeemed according to the payout rule
Use cases
Event-aware hedging Hedge spot exposure only in the outcomes you care about (e.g., hedge BTC downside specifically in the “Hike” branch).
Event-driven dispersion (without complex derivatives) Take a view on pre-/post-event dispersion and magnitude by trading multiple branches.
Tail risk insurance (event-specific put analogue) Selectively short the asset in low-probability “bad” branches while leaving collateral in other branches.
Concentrated tail exposure (event-specific call analogue) Concentrate exposure in a low-probability “good” branch by trading away conditional USDC in other branches so that only exposure in that target outcome remains.
Event-impact isolation Trade the asset inside an outcome branch so the event result is held constant. Branch prices are insulated from shifts in event probabilities.
For an intuition-first explanation of trading branch prices, see: How to trade
Price conditionals
Price conditionals use the same conditional-token and scalar-token machinery, but change what “the outcomes” are.
Instead of outcomes like “Cut / Hold / Hike”, outcomes are terminal price ranges (bins) at a fixed expiry.
Definition
A price conditional market is defined by:
an asset/datapoint (e.g., BTCUSD),
an expiry,
and a set of non-overlapping bins that partition terminal price.
Example bins:
BTC < 60k
60k–70k
…
BTC > 130k
Each bin is a branch. Intuitively: “BTC | 95–100k” is the branch where the expiry price lands in 95–100k.
What is being priced
Price conditionals are a way to trade the terminal distribution of an asset at expiry, at the resolution defined by your bins.
They do this by giving you two useful building blocks per bin:
Bin membership (digital) exposure You can hold exposure that only pays out if the terminal price ends in that bin.
Within-bin (scalar) exposure Inside the realized bin, scalar long/short payoffs vary linearly between the bin endpoints (and clamp outside them).
Together, these let a single market support a wide family of terminal payoff curves without listing a full strike grid.
Use cases
Terminal risk hedging (range and threshold) Hedge “ends in this range” or “ends above/below this level” directly.
One-market option synthesis Compose calls/puts/spreads/ranges from bin building blocks. Basis risk becomes primarily a function of bin resolution.
Trading the distribution itself Express views like “95–100k is overpriced, 105–110k is underpriced” by rotating exposure between bins.
Structured overlays at expiry Build bounded payoff profiles (caps/floors) using bin and scalar components.
Note: price conditionals are terminal-only. If you need path-dependent payoffs (barriers, Asians), you need additional state variables beyond “where did we end at expiry?”
Event vs price conditionals
Use event conditionals when the risk you care about is scenario/event-driven:
“What is BTC worth if the Fed hikes?”
“What is SPX worth if Candidate A wins?”
Use price conditionals when the risk you care about is terminal-distribution-driven:
“Where will BTC finish at expiry?”
“Give me a 90k call-like payoff at expiry.”
Summary
Branches are defined by
event outcomes (Cut/Hold/Hike)
terminal price bins (95–100k, 100–105k, …)
What you trade
conditional price “as if outcome happens”
terminal distribution + within-bin exposure
Best for
event risk, event hedging, impact isolation
strike/range payoffs at expiry, distribution trading
Settlement timing
after event or at expiry
at expiry
Payoff cookbook
This section shows how to recreate common payoff structures using either variant.
1. Binary contract on an event outcome (YES/NO)
Closest analogue: prediction market YES share
Recipe (event conditional) Hold exposure to the outcome branch you want:
“USDC | Outcome A” pays if outcome A is realized
all other outcomes expire worthless
Use this when you want pure outcome exposure (probability-like), not price exposure.
2. Range digital on terminal price
Closest analogue: range option / “in-range” event contract
Recipe (price conditional) Buy exposure to a single bin [L, U) (or a union of adjacent bins for a wider range):
“USDC | 95–100k” pays if expiry price lands in 95–100k.
To hedge outside the range, hold the complement basket (all other bins).
3. Digital above a strike (terminal threshold)
Closest analogue: digital call (cash-or-nothing)
Recipe (price conditional) Construct “S_T ≥ K” as the union of all bins whose lower bound is ≥ K.
If K is exactly a bin boundary, this is exact.
If K is not a boundary, either accept small approximation error or split/refine the bin at K.
4. Scenario forward / scenario future
Closest analogue: forward conditional on a scenario
Recipe (event conditional) Go long or short the asset inside a specific outcome branch.
Examples:
long “BTC | Cut” if you want BTC exposure only if Cut happens
short “BTC | Hike” to hedge BTC downside only if Hike happens
5. Call spread / put spread (bounded payoff)
Closest analogue: vertical spread
Recipe (either variant) A scalar long token has a bounded linear payoff between its lower and upper bound and clamps outside those bounds.
long scalar ≈ call-spread-like profile
short scalar ≈ put-spread-like profile (complement)
This is the simplest way to get “option-like” bounded convexity.
6. Vanilla call / put (European, terminal)
Closest analogue: standard call/put payoff — “0 below K, then linear above K”
Recipe (price conditional) Recreate calls/puts as piecewise-linear payoffs using bin membership + within-bin scalars:
bin membership provides the stepwise offsets between bins above/below strike
within-bin scalars provide the linear movement inside the realized bin
Practical guidance:
Align K to a bin boundary for exact replication.
If you need a strike inside a bin, split/refine the bin at K.
Tail note To replicate an unbounded call, your bin set must extend far enough into the tail (or you accept a capped call).
7. Straddle / strangle / condor at expiry
Closest analogue: common option combinations
Recipe (price conditional) Build these as linear combinations of the call/put recipes above, or directly as “in-range” / “out-of-range” baskets of bins.
8. Event-specific far OTM call / put analogues
Closest analogue: “BTC call if Fed cuts” / “BTC put if Fed hikes”
Recipe (event conditional)
Tail risk insurance (put analogue): short the asset in low-probability “bad” outcome branches while keeping collateral in other branches.
Concentrated tail exposure (call analogue): trade away conditional USDC in non-target branches so only exposure in a low-probability “good” branch remains.
These structures are useful when the scenario itself is the hedge, and you want to avoid basis to proxy instruments.
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