Alfred Lin

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’re launching the Citizen Debt Forecast (CDF): a real-time projection of our national debt powered by people’s beliefs aggregated by prediction markets. The national debt just crossed $40 trillion. And it’s accelerating fast. It took hundreds of years to accumulate the first $20 trillion and 18 years for the next $20 trillion. For FY 2026, the government made $5.6T and spent $7.4T creating a $1.9T deficit (5.9% of GDP). Here’s the breakdown of spend: • $4.4T (60%) in mandatory across Social Security, Medicare, Medicaid, SNAP, etc. • $1.9T (26%) in discretionary across Defense, Education, Transportation, Police, etc. • $1T (15%) in Net Interest The debt feeds on itself. A bigger debt stock means a bigger interest bill. If the economy and government revenues don't grow fast enough, more borrowing is needed to finance the existing debt - creating a vicious cycle of growing interest payments and debt. The debt impacts every American: higher interest rates flow straight to borrowing costs from mortgages to credit cards. So when does the debt get dangerous? There is no precise number and it’s more about the trajectory. Things turn bad when debt keeps growing faster than the economy and investors start demanding substantially higher rates to lend to the government. The government has a few (bad) options to pay down the debt: • raise taxes (less money for Americans), • cut spending (fewer services), • print money (inflation), or • default (trust erosion). We could also grow our way out of it, but it requires GDP growth we haven't seen in decades, sustained for decades. So how do we know if we're making progress? Our current projections of the debt come from a handful of institutions: the Congressional Budget Office (CBO), the OMB, the CRFB, and the Penn Wharton Budget Model. The CBO is the default: they forecast debt-to-GDP 30 years out and set the number everyone else anchors to. These are excellent models, built by serious people. But they share a limitation: they're centralized. Each produces a single projection, shaped by one institution's assumptions, and updated only a few times a year. When the facts change, the forecast waits for the next release. Prediction markets offer something different. They match buyers and sellers, and aggregate beliefs across millions of people through an open, competitive bidding process. If traders think the market is wrong, they profit from correcting the price, so new information is incorporated in real time. The market produces a continuously updated forecast that can aggregate information no single committee possesses. One of my favorite Druckenmiller quotes from his op-ed last week summarizes this perfectly: "Markets aggregate information no committee possesses, and prices are how that information reaches decision makers." The Citizen Debt Forecast (CDF) is powered by free and open markets. It is a 10-year projection of the debt-to-GDP ratio, built from three forward curves – inflation, real GDP, and Fed funds – generated from Kalshi markets and layered on top of the CBO's fiscal baseline. It aggregates the views of thousands of traders into a single, easy-to-read picture of where the debt ratio is headed. We display the CDF next to the CBO forecast, allowing you to compare the two paths. We also made it interactive, so you can enter your own assumptions to compare with the citizen’s forecast and the CBO’s. You can even select from some pre-built scenarios: goldilocks, stagflation, sovereign default, and more. Many in Congress, on both sides of the aisle, are concerned about the debt. People and institutions already use prediction markets to track elections, geopolitics, and rates. Debt forecasts were harder to read, so we built a dashboard that puts them in one place. I hope this becomes a go-to market-based projection to complement committee-based forecasts and serve as an additional data point for the general public and policymakers. The debt is one of the greatest challenges facing America. My door is always open to anyone working on solving it. kalshi.com/gdp-scenarios