Kalshi Says Its Headline Volume Counts Maximum Payouts, Not Cash Spent

Kalshi, the US-regulated prediction market exchange, has responded to allegations that its crypto contract volumes are inflated, after a critic pointed to a series of identical $5,500 trades, CoinDesk reported. The exchange's answer was not that the trades did not happen. It was that the headline volume figure measures something other than cash spent.

By Kalshi's account, the convention across the sector is to report volume as the maximum potential payout of the contracts traded rather than the premium actually paid for them. The company said its regulatory filings are public, and pointed to them as the check on its reporting.

Why the two numbers differ so much

A prediction market contract settles at either $1 or nothing. If a contract trades at ten cents, a buyer pays ten cents for the chance at a dollar. Count the dollar and the trade is worth ten times what the buyer spent. On contracts priced far from fifty cents, the gap between notional payout and cash at risk is enormous, and it is largest precisely where outcomes are least likely, which is where a lot of crypto price contracts sit.

This is not a Kalshi invention. Options and derivatives venues have always had a notional figure and a premium figure, and the notional is bigger. The problem is that a reader comparing a prediction market's volume against a spot exchange's volume is comparing a payout ceiling to money that changed hands, and nothing in the headline number tells them so.

What the identical trades suggest

Repeated trades at an identical size are the pattern that usually prompts wash-trading questions, since matched buying and selling between related accounts inflates a volume figure at almost no cost. Kalshi has not conceded that reading, and the exchange's defence rests on the definition of the metric rather than on the trades themselves.

The two claims are separable. A venue can report volume on a notional basis, which is a disclosure question, and still have flow that is genuinely uneconomic, which is a surveillance question. Resolving the first does not resolve the second.

Why this matters beyond one venue

Prediction markets have become a reference point for onchain finance, cited in research and plugged into consumer apps. Volume is the statistic most often used to rank them and most rarely defined. Any venue whose headline number is a payout ceiling will look larger than a venue reporting premium, and the ranking it produces is an artefact of the convention, not of activity.

The useful disclosure is small and specific: publish notional and premium side by side, or state the convention next to the figure. Until a venue does that, the number ranking it against its peers is not the number a reader assumes it is. What to watch is whether Kalshi's public filings, which it cited as the transparency mechanism, break the two apart.