| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| Price to beat: $69,431.61 | 49% | 47¢ | 49¢ | — | $6K | Trade → |
This market asks whether Bitcoin (BTC) will be higher or lower over a 15-minute window; it matters to traders and scalpers who want to express a very short-term directional view on BTC price movements.
Bitcoin is known for pronounced intraday volatility, so 15-minute windows can show meaningful moves driven by order flow, liquidity shifts, or breaking news. This market is offered on KALSHI and will resolve according to the exchange's published settlement rules; the exact start/close timestamps are listed on the market page when they are set.
Market prices here represent the consensus of traders active on the contract and change in real time as new information and orders arrive. Treat those prices as a reflection of current market sentiment and liquidity rather than a guarantee of the eventual outcome.
The market's contract specifies the exact start and end timestamps for the 15-minute window; check the settlement or rules section on the KALSHI market page for the authoritative timing used to determine the outcome.
The contract will name the reference data source or index used for settlement—review the market details to see which exchange or aggregated feed provides the official start and end prices.
Outcomes are determined by comparing the official reference price at the start of the 15-minute window with the price at the end: a higher end price is 'Up' and a lower end price is 'Down'; the contract also defines how ties or identical prices are handled, so check those tie-break rules.
Relatively low traded volume can mean wider bid/ask spreads and that single large orders have outsized impact on the market price, so market quotes may be more sensitive to individual trades than in higher-volume markets.
Short-term historical patterns (recent 15-minute moves, intraday volatility, and behavior around similar events) can provide context, but 15-minute windows are noisy and dominated by liquidity and order flow, so historical behavior should be used cautiously alongside real-time data.