Kalshi's Transaction Data Authenticity Questioned by Traders
The U.S. compliant prediction market exchange Kalshi has recently faced concentrated questioning from the trader community. The issue arose due to a severe mismatch between its cryptocurrency perpetual contract transaction data and the scale of open interest. Many traders calculated that there is a discrepancy of up to approximately 14 times between the transaction volume disclosed by Kalshi and the actual capital invested.
Quantitative analyst Beni pointed out on September 21 that Kalshi's ETH perpetual contract had a 24-hour transaction volume of $538.6 million, while the corresponding open interest was only about $3.1 million, resulting in a turnover rate of 174 times, equivalent to completing a full turnover every 8 minutes and 18 seconds on average. Meanwhile, the largest single position on the platform was only $17,600, contrasting sharply with the massive transaction volume. Further analysis indicated that the market makers for this product previously received a rebate of 0.3 basis points, while the takers paid a fee of 0.3 basis points, making the bilateral cost nearly hedge to zero. This fee structure is also believed to potentially provide space for wash trading; Kalshi previously had a liquidity partnership with quantitative trading firm Jump Trading.
Kalshi's head of cryptocurrency business, icobeast.eth, later responded that the third-party data platform Artemis shows the transaction share of the prediction market business, not the perpetual contract data; Kalshi's cryptocurrency prediction market itself does not provide similar market-making rebates; the company's method of calculating contracts and notional amounts is consistent with Polymarket, ensuring comparability; as an exchange regulated by the U.S. Commodity Futures Trading Commission (CFTC), all incentive programs must be publicly filed, making it more transparent than offshore exchanges. He also refuted the claim that "self-settling members" (SCM) are equivalent to platform-designated market makers, stating that under the "fair access" regulatory requirements, any institution that meets CFTC qualifications can apply to become an SCM; he acknowledged that mainstream exchanges, including CME, Hyperliquid, and Binance, also have rebate and incentive mechanisms, emphasizing that Kalshi's perpetual contract business is still in its early stages.
The questioning quickly spread to the core prediction market business. Notable prediction market trader retardmode stated that about 61% of the transaction volume disclosed by Kalshi comes from "multi-event combination bets" (i.e., parlay bets that require guessing all events correctly to win), with nearly half of the combination bets wagering on more than 11 events, resulting in a very low probability of winning. He pointed out that Kalshi calculates transaction volume not based on the actual funds invested by users, but based on the notional value of each contract (i.e., the potential payout amount if all bets are correct) — for example, if a user spends $1 to buy a combination bet that could yield $14.1 if all bets are correct, the platform counts it as $14.1 in transaction volume. When recalculated based on actual funds, Kalshi's true transaction amount for the day was about $136 million, while the official disclosed figure was $1.91 billion, a discrepancy of about 14 times.
Top Polymarket trader caronpolymarket further calculated that the actual transaction amount of Kalshi's combination bets could account for only about 7.1% of the disclosed transaction amount; if this ratio is extrapolated monthly, there could be a huge gap where the "real transaction amount is about $4 billion, while the disclosed figure is as high as about $57 billion."
This controversy occurs against the backdrop of Kalshi's rapidly rising valuation — the company completed a $1 billion Series F financing in May this year, reaching a valuation of $22 billion, and by June was seeking to raise funds at a valuation of $40 billion, nearly doubling its valuation in about six weeks, which is seen as further widening the gap with competitor Polymarket. Combination betting products are also the core engine of Kalshi's recent business growth — previous data showed that the proportion of such products in the exchange's total transaction volume had rapidly increased from less than 3% earlier to about 22%, while retail investors' cumulative losses in such combination bets had reached about $117 million (15% of the total betting amount of about $800 million). Kalshi shares this "take" revenue with institutional market makers (including quantitative trading firm Sukvihana International Group), with estimates suggesting that Kalshi's fees from this could reach at least $35 million. In contrast, traditional sports betting companies usually have a higher "take" rate for combination bets (often exceeding 18%, sometimes over 20%), but retain all the profits without sharing with market makers. The authenticity of transaction volume data directly relates to investors' and regulators' judgments on the business scale and valuation rationality of this emerging exchange.
Kalshi positions itself as a financial exchange regulated by the CFTC and an "investment product," rather than a traditional gambling platform. This positioning is also the regulatory basis for its legal provision of "prediction contracts" for sports events, political events, etc.; however, the reality that combination betting products are highly similar to sports betting parlay plays is increasingly subjecting this regulatory positioning to external scrutiny.
Source: Public Information
ABAB AI Insight
Using "notional value" rather than "actual invested funds" to calculate transaction volume is not a unique statistical approach of Kalshi — traditional options and derivatives exchanges commonly use notional value to calculate transaction volume, and this practice is not controversial for low-leverage, relatively balanced probability traditional financial products; however, when the same metric is applied to "multi-leg combinations with extremely low winning probabilities" in prediction market parlay products, the multiplier effect between notional value and actual cash flow can be dramatically amplified — combination bets on more than 11 events can easily reach double-digit potential payout multiples, which is the mathematical root of the current 14 times and even more extreme calculated discrepancies. This pattern of "statistical metrics being compliant but distorted by business structure" has historically appeared in similar controversies regarding the huge gap between the notional scale of structured financial products and actual risk exposure.
Funding pathways show that Kalshi's valuation expansion speed is highly synchronized with its transaction volume growth — the company's valuation jumped from $22 billion to seeking $40 billion in financing in about six weeks, a pace far faster than traditional financial institutions' valuation growth, which typically relies on continuously high growth in transaction volume data to support primary market investors' pricing expectations; meanwhile, the company's recent business focus has clearly shifted towards combination betting (which has risen to about 22% of total volume) and cryptocurrency perpetual contracts (a new business line), both of which can rapidly amplify notional transaction volume and are precisely the focal points of this round of questioning. This means that the capital pricing path for the company's valuation largely depends on the externally disclosed transaction volume growth curve, while the statistical metrics of the transaction volume growth curve itself have the potential to be structurally amplified — forming a potential cycle of "financing valuations relying on rapidly growing transaction volume data, while the transaction volume data itself may be amplified by business design."
Such disputes over "notional transaction volume decoupled from real economic value" have historically been most directly compared to the "wash trading" controversies exposed by some decentralized exchanges (DEX) around 2021, where many platforms engaged in zero-cost matched trading to inflate transaction volume data to attract liquidity mining funds and enhance platform rankings. The current prediction market industry is at a critical competitive stage of "regulated prediction markets versus traditional sports betting, while competing for crypto-native liquidity," with Kalshi and Polymarket as the two leading platforms, both motivated to inflate externally disclosed transaction volume data to compete for market voice and financing valuation, making the transparency of transaction volume statistical metrics an unavoidable structural contradiction in the scaling process of the entire emerging industry.
This essentially belongs to a pricing power game under the backdrop of regulatory changes — Kalshi relies on its CFTC regulatory license to position itself as a "financial exchange" rather than a "gambling platform," thus legally entering markets that traditional sports betting cannot touch (such as political events, economic data predictions); however, when its core business model (combination betting) is structurally similar to the parlay play of sports betting, the originally clear regulatory boundaries between the two begin to blur, and the externally disclosed notional transaction volume data becomes one of the key indicators for outsiders to judge "whether this is a financial exchange or a gambling platform disguised in a compliant guise." From a mechanism perspective, as long as the transaction volume statistical metric continues to use "potential payout amounts" rather than "actual cash flow," the company has structural incentives to design more low-probability, high-payout combination products to amplify its reported data, creating a tension that is difficult to reconcile with regulators' and investors' demands for "transparent and real business scale."
ABAB News · Cognitive Law
The more outrageous the turnover rate, the further the reported numbers are from real funds.
The statistical metric is not fraudulent, but business design can amplify the metric.
Companies whose valuations rely on transaction volume are most afraid of someone recalculating the transaction volume.