We just submitted a regulatory filing to introduce margin on a subset of long-dated prediction markets. This will not apply to sports, culture, and a few other categories. We are very excited to be taking what we believe is our most important step toward institutional adoption so far. Capital efficiency has been the biggest bottleneck for institutions, and margin is the single most requested feature. Fully collateralizing long-dated contracts ties up substantial capital for months or years, making participation impractical for many institutions. It is very difficult for a large institutional market to develop without margin. Margin addresses that problem by reducing capital requirements, subject to strict risk standards. Some important characteristics of our proposal: • Margin applies only to a narrow set of categories, excluding sports and culture. • It is geared toward institutions and subject to strict eligibility requirements. • The risk methodology is modeled on approaches used by established clearinghouses and tested over decades. It incorporates conservative safeguards around volatility, liquidity, concentration, and event risks, as well as measures to limit sharp increases in margin requirements during market stress. The goal is a better trading experience for users. Greater capital efficiency enables more institutional participation, bringing deeper liquidity and better pricing. That makes our markets more attractive to more traders, whose participation further strengthens liquidity and improves the experience for everyone.

We just launched gold and silver perpetuals in the US. And commodity derivatives are now our fastest-growing product. Markets started with grain and metals, expanded into rates, indices, and other financial assets, and are now expanding into information itself, pricing not just assets but outcomes about the future. Prediction markets ask questions with defined resolution: What will GDP be this quarter? Who will win tonight? Perps ask continuous questions, with no expiration: Where is gold going? Prediction markets, traditional futures, and perps are built on the same idea: match buyers and sellers, let them compete in an open market, and discover a price. Traders bring different information and beliefs, and that competition produces a price the rest of us can use as a signal. It’s part of a centuries long evolution toward markets as a general-purpose technology for pricing and managing uncertainty. Prediction markets are one frontier of this evolution. Commodity perps are another.

Ahead of today’s US Open final, we took out full-page ads in The Wall Street Journal, The New York Times, and The Washington Post. The idea is simple: competition makes things better. Five-time US Open champion Pete Sampras didn’t become a legend competing alone. He needed someone on the other side of the net. Someone who saw the point differently. Who challenged every shot. Who made him earn every win. At 17, Sampras made his US Open debut and lost in the first round. Two years later, he beat Ivan Lendl, John McEnroe, and Andre Agassi to become the youngest men’s US Open champion ever. In 1992, he returned to the final and lost to Stefan Edberg. The loss made Sampras “obsessed with being the best.” He trained harder and won the US Open again the next year. At each step along the way, the competition got better, and Sampras had to get better with it. That’s what open competition does. It exposes weaknesses, rewards what works, and forces everyone to keep improving. Over time, the best rise to the top, and the level of the entire game gets better. But that only works when competition is truly open. Anyone can compete. Everyone plays by the same rules. Everyone can see the score and how the game is being played. And no one gets punished for being too successful. The strongest financial markets are built on the same principles of competition. Anyone can participate. Everyone trades under the same rules. Prices and activity are transparent for everyone to see. And no one is limited simply because they’re too successful. On a financial exchange, people bring different information, beliefs, and views of what something is worth, then put money behind those views. That competition drives price discovery. When traders are right, they’re rewarded with more resources to put behind their views. Positions get bigger. The stakes get higher. Better information is rewarded, worse information is punished, and thousands of competing views are distilled into a single market price. That price is useful to everyone, not just the people trading. It becomes a real-time signal of what the market collectively believes, helping us better understand what is happening and what is likely to happen next. Competition breeds legends. And better market prices.

Yesterday Kalshi priced the Wisconsin Democratic Primary at 95–5. The 5% candidate won. Before the "prediction markets got it wrong" headlines roll in: a 5% probability doesn't mean it won't happen. It means it should happen 1 in 20 times. If 5% candidates never won, the markets would be broken. The Washington Post analyzed prediction market calibration on hundreds of primary races — here's what they found:

Today, we launched GPU compute forward curves derived from our prediction market prices. Forward curves are now available on Nvidia B200. H200, and A100 chips. Forward curves track implied future prices. They are how mature commodity markets form expectations, allocate capital, and manage risk. Energy, interest rates/SOFR, FX, metals, and agricultural markets all rely on market-implied forward prices. Despite becoming one of the key inputs in the global economy, compute has lacked that market-derived infrastructure. Compute right now is where oil was before NYMEX — traded only via OTC deals, just like oil used to trade OTC between producers and refiners. As compute becomes as fundamental to the economy as energy, the industry will need a similar derivative market to promote efficient price discovery. Prediction markets are uniquely suited to this problem. Compute is not one uniform commodity and spans many chips, grades, tenors, locations, and contract structures. A live prediction market can aggregate those dispersed views into transparent prices that reflect market expectations for different maturities. The opportunity is big. Hyperscalers are spending over $700B on compute this year and the market is expected to grow to $7-10T by 2030. If this market behaves like traditional commodity markets, a liquid derivative market could be 10-20x bigger than the underlying spot market. Compute is still not uniform enough, but this is a step towards standardization as forward curves will help us see the rise and fall of different model prices and how they correlate. The forward curve is a first step. Up next: futures and perps.

We’re funding a new Financial Trading category within NCPG to advance trader health & safety. While financial markets have different incentive structures than casinos and sportsbooks, there is still risk of irresponsible trading, whether it’s active stock trading, short-dated options, levered futures, crypto, or prediction markets. NCPG’s initiative will invest in education and awareness of our responsible trading resources - self assessments, risk management, account limits, and more. As retail participation in markets increase, we have a responsibility to balance free markets and individual responsibility with customer education and safety guardrails. We want to set a new standard for the industry and hope other retail financial platforms join us.

In 2021, Thomas Peterffy invited Tarek to his house and offered to buy Kalshi. At the time, Kalshi had practically no users, no volume, and zero name recognition. But Peterffy saw the vision. Tarek and Luana turned down a potential life-changing acquisition offer. They had deep respect for Peterffy, and the offer was serious money for what was a tiny startup. But the founders believed in Kalshi and were committed to giving it their all. As their trusted partner and supporter, I told them to follow their heart. Five years later, Kalshi and Interactive Brokers are business partners. These full-circle moments are truly special.

Kalshi is the only financial market where Main St. has an edge over Wall St. Gigi, Nicholas, Brandon, Joel, Heather, Paul, and Stephanie have all found their edge and mastered their own niche on Kalshi. Prediction markets are the people’s markets.

Leveraging FEC Data to screen campaign staff: Last week, NPR reported on several anonymous campaign staffers who claimed they had profited from trades they made on prediction markets which were placed ahead of polling drops for the campaigns they worked on. The reporting didn’t say which prediction market they traded on, but at Kalshi, campaign staff have always been prohibited from trading in election markets. All markets are subject to 24/7 surveillance on Kalshi, and we are conducting investigations and enforcement as usual. We also go beyond policing insider trading and try to preemptively block potential insiders from trading where possible. To that end, our team has ingested available data from the Federal Election Commission and is actively screening salaried federal campaign employees from trading on a campaign that they work for. This data helps us prevent or detect trading by campaign insiders. We plan to process similar data published at the state level where it’s available and block state campaign staff from trading on campaigns they’ve been associated with, too. Let me be abundantly clear: we police all kinds of insider trading and market manipulation at Kalshi. Congress is also considering a law specifically criminalizing campaign staff from trading on their own campaigns – but we aren’t waiting for additional legislation or regulation to take action on market integrity. If we find this type of activity on our platform, it will be referred to law enforcement and subject to exchange disciplinary action. I encourage all traders to heed the repeated warnings from companies like Kalshi, and from the CFTC and DOJ: engaging in insider or manipulative trading on federal exchanges can get you into serious trouble, and we are continuously working to prevent, detect, and punish it where we find it.

Kalshi x Madison Square Garden The world’s most famous arena. Where iconic games are played. Where legends perform. Where unforgettable moments happen. A new era for the city.

When I joined Kalshi back in 2020, the company had just received the regulatory designation it needed to act as a prediction market in the US (after years of work from @luanalopeslara and @mansourtarek_ ), but we still had to actually build the exchange. As an engineer, it felt like such a gift to be a part of that process: the whole team had such conviction in these markets. We dreamed of the day they would be hooked up to trading terminals and referenced by news anchors worldwide. I thought: “if we can just get the systems up and running, people will come.” When we processed our first trade, it felt amazing. But I was also hit with the reality that what we had was not enough: how could we scale to millions of markets a day? How could we support collateral return and margin on events? How do we make even low volume markets liquid? Unlike building a matching engine, these were (and some remain) open questions that hadn’t been solved by a financial exchange before. Thankfully, the team is composed of many of the most hardworking and passionate people I’ve ever met, so though tackling these problems has meant a lot of late nights, it’s never meant a late night alone (shout out to @_rainerds who has been my grinding buddy since the beginning). I'm so grateful to be working alongside each one of you. There is still so much left to do. If you’re interested in joining us, I’d love to chat!