Learn · 36 minutes
Understand the market before you trade it
Five short modules covering how prices become probabilities, where value actually comes from, and how to keep a losing run from becoming a ruinous one. No account needed.
Start at the beginning
Written for somebody who has never placed a trade. Read in order — each module assumes the one before it.
A price is a probability
A contract that pays $1 if something happens will trade near 63¢ when the market thinks it is about 63% likely. That is the whole translation, and once you can read it in both directions every market on every venue becomes legible.
Takeaway Cents in, percent out. 63¢ means "about 63 times in 100".
Where value comes from
Value is not a market you think will resolve YES. It is a market where your probability is meaningfully different from the price, and where you can say why. Without the "why", a gap is far more likely to be your error than the market’s.
Takeaway An edge you cannot explain is usually a mistake you have not found.
Being right vs being calibrated
Anyone can forecast the obvious and boast about a win rate. The question that matters is whether the things you call 70% happen about 70% of the time — including the 30% that do not. Calibration is the only score that cannot be farmed.
Takeaway Track how often your 70s land. A perfect record means you only bet on certainties.
Sizing, limits and ruin
Your maximum loss on a contract is what you paid for it, which makes prediction markets easier to reason about than leveraged instruments. It does not make them safe: enough small certain losses still end an account. Size positions so that being wrong five times in a row is survivable.
Takeaway Decide your daily loss limit before you need one, not during.
How beginners lose money
Trading the news after it is priced. Confusing a strong opinion with an edge. Adding to a losing position to "average down" on an event that has already changed. Treating a 90¢ contract as free money — it is nine dollars risked to make one.
Takeaway The expensive mistakes are behavioural, not analytical.
Now see it applied
The predictions page shows the same reasoning against real markets: a probability, the argument for it, and the thing most likely to make it wrong.