Last March I bought a Fed decision contract at 67 cents. The market was pricing a 67% chance of a rate hold, and I thought it was closer to 80%. I sized up, the Fed held, and the contract settled at $1.00. That 33 cent move wasn't luck. It was the math working exactly as expected. Understanding the math behind Kalshi pricing is the difference between gambling and trading with an edge.
Every Kalshi contract is a binary bet. It settles at $1.00 if the event happens, $0.00 if it doesn't. That's it. No complicated payoff structures, no Greeks to worry about, no theta decay in the traditional sense.
The price you see is what the market collectively believes about probability. A contract trading at $0.45 means the crowd thinks there's roughly a 45% chance the event occurs. Buy at 45 cents, win a dollar if you're right, lose 45 cents if you're wrong.
This simplicity is why I gravitated toward prediction markets after years on a futures desk. Equity index futures have basis, roll costs, and correlation dynamics that make edge hard to isolate. Here, the question is clean: is this probability correct or not?
The basic formula is almost embarrassingly simple:
Implied Probability = Contract Price × 100
A contract at $0.72 implies 72% probability. A contract at $0.08 implies 8% probability. You can do this math in your head while staring at the order book.
But here's where people get sloppy. The price you see isn't always the price you get. You need to account for:
The math behind Kalshi pricing only matters if you can identify when the market is wrong. This is where most people fool themselves.
Here's my process:
Step 1: Form your own probability estimate before looking at the market. This is critical. If you look at the price first, you'll anchor to it. I keep a spreadsheet where I write down my estimate, then check Kalshi. The difference is my perceived edge.
Step 2: Calculate your expected value.
Expected Value = (Your Probability × Potential Win) minus ((1 minus Your Probability) × Potential Loss)
Say a contract is trading at $0.40, and you think the true probability is 55%. If you buy at 40 cents:
Positive expected value. That's a trade worth considering.
Step 3: Ask yourself why you're smarter than the market. This is the hard part. The other side of your trade isn't stupid. What do you know that they don't? Sometimes I have a real informational edge (I follow certain data releases closely). Sometimes I realize I'm just pattern-matching to noise. The second case, I don't trade.
New traders get confused when they see Yes at $0.54 and No at $0.48. Shouldn't those add to $1.00?
Not quite. You're looking at different sides of the order book. The Yes price is the ask (what you pay to buy Yes). The No price is also the ask (what you pay to buy No). The spread in between is where market makers live.
If you want to check market efficiency, compare the Yes bid to (1 minus the No ask), or vice versa. In liquid markets like Fed decision contracts on Kalshi, this spread is usually tight. In thinner markets, it can get wide enough to matter.
Let me walk through how I approached a CPI print last year.
The market for whether year-over-year CPI would come in above 3.0% was trading at $0.35. I pulled the Cleveland Fed's inflation nowcast, looked at recent trends in shelter and energy, and estimated 45% odds of an above-3.0% print.
My edge calculation:
That's a meaningful gap. I bought at 35 cents. CPI came in at 3.1%, contract settled at $1.00, and I collected 65 cents per contract minus fees.
I share trades like this in the Telegram channel I run when I think the setup is interesting enough to discuss publicly.
After a year on Kalshi, I've made most of the dumb mistakes. Here are the ones that cost me money:
Implied probability is the market's collective estimate of an event's likelihood, expressed through the contract price. On Kalshi, a contract trading at $0.70 implies a 70% probability the event happens. This price emerges from buyers and sellers agreeing on terms. It's not a guarantee of accuracy, just the crowd's best guess at any given moment.
Multiply your estimated probability of winning by the potential payout, then subtract your estimated probability of losing multiplied by the potential loss. If the result is positive, you have positive expected value. A positive EV trade isn't guaranteed to win, but over many trades, positive EV bets should generate profits. The hard part is estimating your true probability accurately.
Markets can be temporarily inefficient due to low liquidity, slow information flow, or emotional trading around news events. Sometimes what looks like mispricing is actually the market knowing something you don't. I've been humbled enough times to approach "obvious" mispricings with skepticism. But genuine edge does exist, especially in niche markets with less attention.
No. The math is necessary but not sufficient. You also need accurate probability estimates, which require domain knowledge, good information sources, and honest self-assessment about what you actually know versus what you think you know. Most prediction market traders, myself included, have periods of overconfidence that the market eventually corrects.
Not financial advice. I trade my own money and you can lose yours. Do your own research.