Why Real-Time Election Odds Mislead Crypto Traders on Prediction Markets

You can be correct about who will win an election and still overpay to bet on that outcome. On prediction markets, the price displayed when you open the app may no longer be available by the time you attempt to buy, particularly when news triggers a rush of other traders toward the same outcome.

The market quickly identified a business opportunity in this dynamic. On September 9, DoubleZero announced that it had integrated Kalshi’s election and politics markets into Edge, a service designed to deliver trading data over a dedicated network. This service provides access to the exchange’s order book, displaying the prices and quantities at which participants are willing to buy and sell.

DoubleZero told CryptoSlate that faster, more reliable information enables professional trading firms to offer improved pricing. If this competitive advantage is passed on to customers, retail bettors could benefit. However, utilizing these feeds effectively requires specialized software and capital, giving well-resourced companies another avenue to compete against individuals placing bets via mobile apps.

Election betting appears to serve as a great equalizer for both professional trading firms and retail users. Some participants wish to back a political judgment for months, while others aim to profit from short-term price movements. Faster data particularly benefits the latter strategy.

What happens between the prediction and the payout

On Kalshi, a standard yes-or-no contract pays $1 if the outcome occurs and nothing if it does not. Buying a yes contract for 60 cents means risking 60 cents for a potential 40-cent profit before fees. The price is commonly interpreted as reflecting roughly a 60% probability, though costs and trading conditions can significantly erode that figure.

You can also sell contracts before the election concludes. Suppose you buy 1,000 contracts at 60 cents and sell them at 65 cents. Provided both trades execute at those prices, you earn $50 before fees, regardless of the final election winner. Predicting the next buyer’s willingness to pay can therefore be profitable long before the actual outcome is known.

This dynamic gives traders a reason to monitor the order book. The best bid represents the highest price a buyer offers, while the best offer is the lowest price a seller accepts. The gap between them is known as the spread. The quantities available indicate how much volume can trade before buyers or sellers must accept a different price.

Imagine positive news about a candidate prompts traders to buy. A participant receiving updates quickly can see cheaper offers being consumed and reassess their entry price. Someone viewing an older snapshot might still see contracts that have already been sold. Their purchase depends on what is available when their order reaches the exchange.

Edge delivers information about this market activity. Subscribers receive bids and trades, but not insider information regarding the elections themselves. Kalshi already provides a streaming connection called WebSocket, which sends updates to trading programs. Services like Edge compete based on how efficiently that data reaches the recipient.

However, receiving the data is only the first step. Trading software must then interpret the update and decide whether to trade, and orders must still reach Kalshi. The exchange uses price-time priority, meaning that both the price and the timestamp of an order determine its position in the queue. A faster feed helps someone act sooner, but the subscription itself does not guarantee a reserved position.

Who gets the better deal?

This structure is particularly advantageous for market makers, firms that continuously offer to buy and sell to ensure liquidity for other traders. They aim to earn enough from the spread to cover their losses and operating costs.

Suppose a market maker offers a contract at 60 cents, but news convinces buyers it is worth closer to 70 cents. The market maker might take the old offer while the seller is still processing the information. Repeated losses of this kind can force companies to widen spreads or reduce the number of contracts offered, making trading more expensive for everyone else.

Faster information helps market makers update their quotes, including when other traders reprice related contracts. If multiple firms can manage this risk and compete for customers, they can offer narrower spreads. An occasional bettor might then secure a better deal without purchasing a faster connection themselves.

This is the potential benefit in DoubleZero’s pitch, but it requires evidence from actual trades. Delivering data sooner and providing customers with better prices are distinct achievements. To make a convincing comparison, we would need to examine the prices and quantities available during busy political events, when traders most require reliable information.

The company’s connection guide describes a paid feed and software that converts incoming data into messages an application can read. This reduces the effort required to connect, but subscribers still need a program capable of making decisions and handling interruptions, along with funds to trade. Large companies can spread these costs across much higher activity volumes than an independent trader.

Access to the same subscription therefore leaves significant room for unequal capabilities. For someone holding a bet for months, a tiny delivery advantage with profits measured in fractions of a cent may be irrelevant. However, for a company continuously updating thousands of quotes, it can significantly impact the profitability of repeated trades.

The odds travel beyond prediction markets

DoubleZero brings crypto infrastructure into this sector. Its network combines privately supplied fiber links and hardware, and its blockchain services include connections for Solana validators. Both validators and trading firms have incentives to pay for dependable communication.

Distributing election data provides political probabilities with another route into financial decisions. Consider a hypothetical crypto investor who believes a particular congressional outcome would improve the prospects for legislation affecting the industry. Election odds could become one input when assessing crypto companies or a Bitcoin position, with software receiving updates automatically.

The investment judgment still involves several uncertain steps. Winning a chamber does not guarantee legislation will pass, and passing legislation does not determine an asset’s price. Other investors may have already priced in the same news. Even an accurate political forecast can lead to a bad trade if the buyer pays too much.

CryptoSlate has examined the commercial value of prediction-market information, but a number does not become more reliable simply because it travels faster. Its value depends partly on the market behind it. A price supported by only a few contracts reveals nothing about where a larger transaction could execute, and a sudden movement might reflect sellers withdrawing rather than new evidence about the election.

This also affects how the public interprets the odds. When a probability appears in political coverage, the number can seem more authoritative than it actually is. Knowing the amount of money available at that price provides context, although even a deep market represents only those willing and able to trade, with no way of knowing if they resemble the actual electorate.

Confidential information creates a separate problem. In its February 25 enforcement advisory, the CFTC described Kalshi disciplinary cases involving a candidate trading on his own candidacy and a YouTube editor trading contracts tied to unpublished videos. Those cases involved conduct and information advantages that went beyond the speed of a connection.

Platforms must distinguish how someone learned something from how quickly their computer received it. Faster distribution makes public market data more accessible, while surveillance addresses prohibited conduct; neither function substitutes for the other.

For ordinary bettors, the benefit of this infrastructure will come through the prices they can actually secure. Competition between professional trading firms could make entering and exiting positions cheaper, even as those firms gain capabilities most customers never use. Demonstrating this benefit requires measuring what happens to prices and available contracts when political news breaks, specifically when a person opening the app discovers the cost of their prediction.

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