Guide · July 25, 2026

Implied probability and expected move, read straight from the chain

Written and reviewed by ConvexValue · Updated July 25, 2026

An option chain carries implied volatility and valuation estimates across strikes and expirations. Those inputs can be used to derive a risk-neutral probability distribution over where the underlying could be on a given date — which is why questions like “what are the odds this closes below 700 by the 22nd?” have a market-derived answer rather than an opinion.

cvforge’s current per-contract valuation field is Massive fair market value (FMV). It does not provide option bids, asks, midpoint, quote sizes, NBBO, or last trades. FMV is a proprietary estimate, not an executable quote.

This guide covers what those numbers are, how to derive them from the fields in a snapshot, and the two mistakes that make them misleading.

Expected move

The standard approximation using implied volatility is:

expected move ≈ spot × ATM implied volatility × √(days ÷ 365)

You can also sum the call and put FMV estimates near the money to form an FMV-based straddle estimate. That is a model-derived comparison, not the cost at which the straddle can be bought or sold. It must be labeled as estimated.

The square root matters more than anything else here. A 30-day expected move is not five times a weekly one — uncertainty accumulates with the square root of time, not linearly, which is why probability cones are cone-shaped.

Probability cones and standard deviations

A cone takes the expected move and draws it forward. The one-standard-deviation band covers roughly two thirds of the implied distribution; two standard deviations covers most of the remainder.

Two cautions worth stating every time a cone is drawn:

  • The bands come from implied volatility, so they inherit a lognormal assumption that equity returns do not actually satisfy. Real return distributions have fatter tails, which means the outer band understates how often extreme outcomes happen.
  • A one-standard-deviation range is not a forecast range. Roughly one session in three finishes outside it. Clean lines on a chart make a much stronger visual claim than the statistics support.

Risk-neutral is not predictive

This is the point that matters most. Probabilities derived from option-implied inputs are risk-neutral: they embed the premium participants charge for carrying risk, not just their view of the odds.

In equities that premium is heavily asymmetric. Downside protection is persistently more expensive than equivalent upside, so implied downside probabilities sit above what a purely statistical estimate would give. When a chain says there is a 20% chance of a fall to some level, the correct reading is “the market charges as if there were a 20% chance”, which is a statement about pricing rather than prediction.

That is also what makes the comparison against realised outcomes interesting: run it over a long enough window and the gap between implied and realised is the volatility risk premium, visible as a pattern rather than a theory.

Where expirations bite

Expected move is only defined against a specific expiration. Quoting a “30-day” figure when the nearest expirations are 23 and 37 days out involves interpolation, so it helps to see which real expirations bracket your horizon — that tells you how much of the number is measured and how much is inferred.

Near an earnings date the term structure develops a step: the expiration covering the event prices materially more movement than the one before it, and that step is the market’s price for the event.

Fields you need

implied_volatility, delta, strike_price, expiration_date, underlying_price and fair_market_value from the options snapshot. All are available on the free data tier — none of this requires historical options data unless you want to score cones against what actually happened.

Watch it built

Every one of these was built live from a single sentence:

The full set is in the implied probability and expected move section of the demo library.

This is research and education, not investment advice.