Most executives who have heard of Kalshi or Polymarket file them under gambling and move on. That is a mistake, and it is a cheap one to fix. A prediction market is a public, continuously updated probability for an event, paid for by people who lose money when they are wrong. You do not need an account, a position, or a view on whether the whole thing is a good idea. You need to know how to read the price and where to put it in your plan. Chapter 3 of the book argues that market-implied probability is a checkable input to a scenario set. This is the practical version of that argument.
Price is probability
A contract that pays one dollar if the Fed raises rates in December and nothing if it does not will trade somewhere between zero and a dollar. If it trades at 86 cents, the market is saying there is roughly an 86% chance of that outcome. That is the whole mechanism. The price is not a forecast from an analyst with a reputation to protect; it is the clearing point between people who think the event is more likely than the price and people who think it is less. It moves the moment new information arrives, in public, with a timestamp.
Compare that to the rate assumption in your 2027 plan. It was written once, by one person, in September, and it has no timestamp on when it was last defended. The market’s number is not necessarily right. It is current, and it is honest about being a probability rather than a point.
What the Fed market says right now
As of November 11, with the Fed funds ceiling at 4.00% after the September 17 hike, Kalshi prices a December hike at about 97%. Break it down and the 25 basis point move sits near 86%, a larger move near 11%, and a hold near 4%. The direction is no longer the open question. The size is. January 2027 is the genuine split: about 52% for another hike against about 45% for a hold.
That pair of numbers is more useful than any single forecast you could buy, because it tells you where the uncertainty actually lives. December is nearly settled. January is a coin flip. A plan that treats both months the same way is ignoring free information. We keep the live version of these markets on the market layer, and the monthly read on what the markets and the macro series together are saying is in the Signal Layer.
How to attach a market to a scenario
Every scenario in an active set should carry an indicator set: what you would expect to see if this world were converging. A prediction market is the cleanest possible indicator, because it already is a probability. Take your scenario set and for each one ask whether there is a market whose resolution would confirm or kill it. Rate scenarios map to Fed decision markets. Policy scenarios map to legislation and election markets. Some macro and company-specific events are listed too, and more arrive every month.
Then write the market’s current price next to the scenario, with the date. Not as the scenario’s probability. As the crowd’s current read on one of its load-bearing conditions. A scenario called “Rates Hold Through Q1” now carries a note that says the December hike market was at 97% on November 11 and the January hike market at 52%. The team can still hold that scenario in the set. It cannot hold it without knowing the crowd is on the other side of one of its conditions.
At the monthly Convergence Review, the market price becomes one of the inputs that moves a scenario between converging, holding, and collapsing. A market that has gone from 60% to 95% on a condition your scenario needs is evidence of convergence. A market that has fallen through 20% is evidence of collapse. Neither is proof. Both are better than the opinion of whoever talks loudest in the room.
What the price cannot tell you
Three caveats, and they matter. Liquidity. A market with thin volume can be moved by one trader and will show wider gaps between the bid and the ask. The Fed decision markets are deep. A market on a niche regulatory event may not be, and a price in a thin market is a weak signal, not a strong one. Check the volume before you write the number down.
Resolution.Every contract has fine print that defines exactly what counts. A market on “a recession in 2027” resolves on some specific definition, by some specific source, on some specific date, and that definition may not be the one your plan cares about. Read the rules before you map a market to a scenario. A mismatch between the contract’s resolution and your scenario’s condition is the most common way this goes wrong.
Coverage.The events that matter most to a regional distributor or a midstream operator are not on any exchange and never will be. Markets cover the shared macro conditions underneath your plan. They do not cover your customer’s renewal decision. Use them for what they price and build the internal signal layer for the rest.
The move: check your plan against the market
This takes under an hour and you can do it this week. Open your 2027 plan and find every assumption that maps to a listed market. Rates almost always. Sometimes inflation prints, policy outcomes, an election. For each, write three columns: what the plan assumes, what the market prices today, and the gap. Then ask one question of each gap: if the market is right and we are wrong, which commitment in this plan becomes a mistake?
That question is the bridge from Scan to Stake. A plan assuming flat rates with a hiring wave and a facility lease behind it has a different exposure than a plan assuming flat rates with a marketing budget behind it. The first set of commitments is hard to reverse, and the Stake Sizing Matrix says those are the ones to stage or hedge when the market disagrees with you. The second set can ride. The budget stress test walks the full version of this.
Why this is not betting
You are not taking a position. You are reading a public price the same way you read a bond yield or a futures curve, both of which are also markets where people bet on the future and both of which have been standard planning inputs for decades. The difference is that prediction markets price the discrete events that scenarios are built on, in plain language, with a resolution date. The firm that reads them is not speculating. It is refusing to ignore a number that its competitors can also see.
The longer argument, that the volume flowing through these markets is the public proof that continuously priced foresight beats the static kind, is in the prediction-markets essay. The method for turning a live price into a sized commitment, from Scan through Steer, is in the book.