Options Chart

Probability Distribution

Statistics

What the market believes will happen at expiry

The Probability Distribution shows the market's consensus view of where a stock will be at expiry, derived from current implied volatility and time remaining. This is literally what options are priced on — not a prediction, but the statistical distribution baked into every single contract you trade. The wider the curve, the more uncertainty the market is pricing in.

Implied Volatility Baked Into Every Price

The probability curve is the market's bet slip. It doesn't predict the future, it shows you what everyone is collectively paying for right now.

Every option price implicitly encodes a probability distribution. When you buy a call, you are buying a claim on a specific slice of that distribution — all outcomes above the strike. The premium you pay is the market's consensus estimate of the probability-weighted expected value of that slice. The probability distribution chart simply makes that implied distribution visible in one curve.

The curve is derived from a lognormal model using current IV and days to expiry. It is not a forecast — it is a market price. If the market is mispricing fear or greed, the distribution will reflect that mispricing. That is precisely why skilled options traders look for discrepancies between the implied distribution and their own view of likely outcomes.

The 1σ rule

Roughly 68% of all outcomes are expected to fall within one standard deviation of current price by expiry. This defines the "expected move" — the range the market has priced into options. Selling premium outside this range (iron condors, short strangles) is a bet that the realized move will be smaller than implied.

Why the Curve Is Not Symmetric

A true lognormal distribution is slightly right-skewed — stocks can only fall to zero but can theoretically rise without limit. In practice, markets add an additional left skew through IV skew: OTM puts are priced with higher implied volatility than equivalent calls, fattening the left tail of the distribution. This reflects the observed reality that markets crash faster than they rally.

During earnings or major events, the distribution widens dramatically as IV spikes. After the event resolves, IV collapses and the curve narrows — this is the IV crush that destroys premium buyers who bought options into events and held through them.

Using It for Strategy Selection

The probability distribution is your strategy sizing tool. Short premium strategies (selling spreads, iron condors) work best when the curve is wide and you expect realized volatility to come in lower. Long premium strategies (debit spreads, calendars) work best when the curve is narrow and you expect an outsized move. Before entering any strategy, overlay your expected price target against the distribution — if your target is already a 2σ move, you need to be compensated accordingly.

How to read it

1
Start here Peak of the curve

Most likely price at expiry — usually very close to current price

2
Width of the curve

Uncertainty — wider = higher IV = more expensive options = bigger expected move

3
1σ lines (dashed)

The zone where ~68% of outcomes fall — iron condor and short strangle targets belong here

Key takeaway Curve skewed left or right

Market is pricing asymmetric risk — more fear in one direction