Kalshi, a regulated U.S. exchange that specializes in event‑driven contracts, has announced that its election‑related market data will be streamed live to the DoubleZero platform in the weeks leading up to the 2026 midterm elections. This development marks a notable step forward for both professional traders and market‑making firms that rely on granular, real‑time information to shape their strategies.
By making the entire order‑book depth – every bid and ask at every price level – publicly accessible, DoubleZero is providing a level of transparency that has traditionally been reserved for internal analytics teams at large financial institutions. ### Why the data matters Political prediction markets have grown from niche betting venues into sophisticated forecasting tools that attract hedge funds, quant shops, and even academic researchers. The markets function by allowing participants to buy and sell contracts that pay out based on the outcome of a specific political event, such as whether a particular party will win a majority in the House of Representatives. Prices of these contracts reflect the collective belief of market participants about the probability of each outcome, and the order‑book depth reveals the intensity of that belief across a range of price points.
When traders can see the full depth of the book, they gain insight into hidden liquidity, potential price barriers, and the size of hidden orders that could move the market if executed. For algorithmic strategies that rely on order‑flow analysis, this information is invaluable.
It enables the creation of models that anticipate short‑term price swings, detect emerging consensus, and even identify moments when the market may be mispricing an outcome due to temporary imbalances in supply and demand. ### Institutional and automated access The partnership between Kalshi and DoubleZero is designed with institutional users in mind. Rather than a simple ticker feed, the data stream includes every level of the order book, timestamps to the millisecond, and metadata about order types (limit, market, stop, etc.).
This richness allows firms to feed the data directly into high‑frequency trading engines, back‑testing frameworks, and risk‑management dashboards without the need for manual preprocessing. Automated traders, especially those employing machine‑learning techniques, can now train models on a much larger and more detailed dataset. The expanded dataset improves the signal‑to‑noise ratio, which is crucial when trying to predict political outcomes that are influenced by a complex mix of polling data, macro‑economic indicators, and sudden news events. Moreover, the real‑time nature of the feed means that models can be updated on the fly, allowing traders to adjust positions within seconds of new information hitting the market.
### Impact on market efficiency Transparency tends to improve market efficiency, and the introduction of full‑depth data is expected to narrow bid‑ask spreads and reduce the prevalence of arbitrage opportunities that arise from information asymmetry. When all participants have equal access to the same depth information, price discovery becomes more accurate, and the market price of a contract better reflects the true consensus probability of an event occurring. In the context of the upcoming midterms, this could lead to a more stable pricing environment. Historically, election markets have experienced sharp spikes in volatility as new poll releases or unexpected campaign developments emerge.
With deeper visibility into order flow, traders can better gauge whether a price swing is likely to be short‑lived or indicative of a genuine shift in market sentiment. ### Technical implementation DoubleZero has integrated Kalshi’s API using a secure WebSocket connection that pushes updates as soon as they occur on the exchange.
The feed adheres to the FIX protocol for financial data, ensuring compatibility with most institutional trading systems. Data latency is reported to be under 200 milliseconds, a benchmark that meets the requirements of most high‑frequency strategies. For firms that require historical data for back‑testing, Kalshi is also offering a bulk download of past election‑related order‑book snapshots.
This archive spans the last three election cycles, providing a rich historical context that can be used to validate predictive models against real‑world outcomes. ### Compliance and regulatory considerations Because Kalshi operates under the oversight of the U.S. Commodity Futures Trading Commission (CFTC), all market data is subject to strict reporting and record‑keeping standards. The data feed includes compliance tags that help firms meet their own regulatory obligations, such as tracking trade‑through events and monitoring for potential market manipulation.
Institutions that are required to maintain audit trails will find the built‑in logging features useful. Each data packet is timestamped and carries a unique identifier that can be cross‑referenced with Kalshi’s official trade logs, simplifying the process of reconciling internal records with exchange‑reported activity. ### Looking ahead The launch of this data feed comes at a time when political markets are gaining broader acceptance as a legitimate source of insight for investors.
As more asset managers incorporate political risk into their portfolio construction, the demand for high‑quality, granular market data is expected to rise. Kalshi has hinted at expanding the scope of its data offerings beyond election contracts to include other event‑driven products, such as macro‑economic releases and regulatory decisions. If successful, the DoubleZero integration could become a template for how other specialized exchanges deliver deep market data to professional users.
In summary, the real‑time, full‑depth election data now available on DoubleZero equips institutional and automated traders with a powerful new tool for navigating the uncertainty of the U.S. midterm elections.
By democratizing access to the same granular information that was previously confined to a handful of market participants, the partnership promises to enhance price discovery, improve market efficiency, and enable more sophisticated trading strategies across the political prediction‑market landscape.