Implied Volatility: A Price, Not a Forecast
Implied volatility is the expected movement that a pricing model must assume in order to produce the option's current market price. It is therefore a price expressed in the units of a forecast, and it is set by supply and demand rather than by any prediction coming true.
The curves on this page are shape-accurate illustrations rather than quotes for any real contract. They are correct about behaviour and are not a forecast of anything.
How it works
An option pricing model takes several inputs — price, strike, time, rates and expected volatility — and produces a value. Four of those are known. Volatility is not.
So the calculation is run backwards. Take the price the option is actually trading at, and solve for the volatility figure that would produce it. That figure is the implied volatility.
Which means it is a price with the units of a forecast. It is set by what people are paying, not by anything about the future, and calling it “the market’s expectation” is a description of who set it rather than evidence that they were right.
The event cycle
Before a scheduled event, implied volatility rises. Earnings, a rate decision, a trial result — anything with a known date and an unknown outcome makes a large move more likely, and options get more expensive.
The moment the result is known, it collapses. The uncertainty that justified the price has been resolved, and the premium falls whichever way the news went. That collapse is what traders mean by “vol crush,” and it is the most reliable event in the options calendar.
Which produces the standard beginner experience. Buy calls before earnings, be right about the direction, and lose money — because the fall in implied volatility took more than the move gave. The share was up and the option was down, and nothing about that is unusual.
It is separate from theta and works alongside it. Time decay removes value on a schedule; a fall in implied volatility removes value in one step. A position can suffer both at once, which is what the week after earnings looks like.
In practice: reading the number
A raw figure means very little. Thirty percent is low on one instrument and high on another. What matters is where it sits against that instrument’s own history — which is what percentile-style measures exist to express.
It feeds every other number. Delta, gamma and theta are all computed with it as an input, so a change in implied volatility changes the whole profile of a position without price moving at all.
Cheap options in a quiet market are usually cheap for a reason. Low implied volatility reflects a market that has not been moving, and buying options because they are inexpensive is buying the market’s assessment that nothing is likely to happen.
What implied volatility is not
It is not a forecast. It is what people paid. Forecasts can be wrong; a price cannot be, because it is not a claim about anything.
It is not directional. It rises when large moves are expected in either direction, so a high figure says nothing about which way.
It is not the same as realised volatility. How much the instrument actually moved is a separate, measurable quantity, and the two differ persistently.
And it is not comparable across instruments. A number that is extreme for one asset is ordinary for another, which is why the raw figure is close to useless without its own context.
When it fails
The core error is treating it as information about the future. It is information about what options cost today, and the market setting it is no better informed than any other market.
The second is buying options into a known event. The premium already contains the expected move, so the position needs a move larger than the one everybody is expecting — which is a much harder bar than being right about direction.
A third is selling volatility because it looks high without asking why. It is frequently high because something genuinely uncertain is about to happen, and the seller is being paid for a real risk rather than a mispricing.
A fourth is ignoring the transaction costs around it. Option spreads widen when volatility rises, so trading it is most expensive exactly when it is most interesting — on top of the 2% of a typical bar the underlying costs.
And a fifth is assuming the crush is a free trade. Selling into an event to capture the collapse means being short the move itself, which is the one thing the elevated premium was pricing.
A sixth is comparing today’s figure to a number remembered from a different regime. Volatility clusters: quiet periods follow quiet periods and turbulent ones follow turbulent ones. A level that was extreme last year can be unremarkable this year, and the comparison has to be against recent history rather than against a figure that felt normal once.
Nothing here says the number is useless. It is the single most informative thing on an option chain, because it converts a price into something comparable across strikes and dates. What it does not do is tell you what will happen — and separating those two claims is most of what it takes to use options without being surprised by them.
The original data
7 of the 24,971 videos measured for this site cover implied volatility, at a median of 1,551 views — a small supply and a very low median for the single concept that explains most of the confusion beginners have about options.
The practical test before any option trade is one question. Is this contract expensive or cheap against its own recent history, and is there a reason for that. If there is a known event, the answer is already in the price, and being right about the news is not the same as being paid for it.
Related
Vega is what a change in this number is worth to a position. Options expiry is the other clock running alongside it. And call options is where the “right and still lost” experience usually happens.
The first time I bought calls into an earnings release I was right about the direction and lost money anyway. Nobody had told me the price already contained the expectation of a move, and that the expectation would be removed the moment the result was known.
— Michael Whitman
This page is educational, not financial advice. Test every idea on your own charts before risking money.