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Event Contract Settlement

A prediction becomes a trade only after the event, settlement rule, probability, and all-in price are precisely defined.

A sealed event contract beside an exact mechanical stamp and a magnifying glass over a clearly defined finish line.

A binary event contract commonly pays $1 if a specified condition is met and $0 otherwise. The difficult word is “specified.” A view about the economy or an election is broader than the exact condition a contract will settle on.

Read that condition before deciding whether the price is attractive. A correct forecast of the headline can still be a wrong forecast of the contract.

The condition that settles

Imagine a contract asking whether a reported statistic will exceed 3.0%. “Exceed” differs from “equal or exceed.” A first release can differ from a revised release. An annualized quarterly figure differs from a year-over-year figure. A value rounded to one decimal place can differ from the underlying unrounded number.

Identify the measurement, source, observation period, threshold, and treatment of revisions or unavailable data. Kalshi's member agreement makes clear that individual contracts have their own trading, settlement, payout, and determination terms. Similar-looking headlines do not establish identical payoffs across venues.

From probability to expected profit

Suppose you buy 100 Yes contracts at $0.62 each. The price is $62. Assume total fees of $1 for the intended hold-to-settlement path, giving a $63 cost. If Yes occurs, you receive $100 and earn $37. If No occurs, you lose $63.

At a genuine 70% probability, expected profit is 0.70 × $37 − 0.30 × $63 = $7. At 60%, it is a $3 expected loss. The breakeven probability is 63%, including the assumed fee.

The example separates three quantities that are often confused: the market quote, your estimated probability, and your return on money committed. The market's $0.62 quote is not a certified 62% probability. Spreads, fees, risk preferences, liquidity, and constraints can affect prices.

Your probability needs a track record too

Being more confident than the market is not enough. The useful question is whether your estimates are calibrated. If you repeatedly call events 70% likely, roughly 70% should occur over a sufficiently large, comparable sample. One loss does not refute a 70% forecast, and one win does not validate it.

Record the estimate before the outcome, together with the evidence and what would change it. Separate categories you understand from those you merely find interesting. Forecasts about related events can share the same error, so 20 contracts may represent one concentrated view rather than 20 independent opportunities.

You can trade a probability change

Holding until resolution is one possible strategy. If a contract bought at $0.62 can later be sold at an executable $0.72, the gross gain on 100 contracts is $10. That is about 16.1% of the original $62 purchase cost, before entry and exit charges.

A displayed mark at $0.72 does not guarantee that all 100 can be sold there. Check the bid and available quantity. As the outcome becomes more certain, the remaining upside can become small relative to the time capital remains tied up and the loss if the apparent certainty is mistaken.

Closing time is not payout time

A market can stop trading before the official source publishes the result. Determination may then require verification, and payment can occur later still. Kalshi's market FAQ distinguishes these stages.

This matters when comparing opportunities. Earning $2 on $98 committed for a day and earning the same amount with an uncertain month-long wait are different uses of capital. Avoid annualizing a near-certain-looking payout without accounting for the possibility and size of a loss.

For the 62-cent contract, the assumed fee raised the break-even probability to 63%. An estimate of 70% leaves room for profit; an estimate of 60% does not. The disagreement becomes meaningful only when the probability concerns the exact settlement condition and the purchase can be made at the modeled cost.