Expected Move Calculator

The expected move is the price range that option prices imply for a stock by a given expiry. The one-standard-deviation (1σ) move is price × implied volatility × √(days ÷ 365). This expected move calculator works from implied volatility, from the at-the-money straddle, or from two expiries around an earnings date, and shows the 1σ and 2σ ranges, the lognormal range, the probability of ending inside each range and a day-by-day and week-by-week breakdown.

Everything runs in your browser. Nothing you type is saved or sent. Implied volatility is the market’s estimate of future movement, not a forecast or a guarantee.

How to use the expected move calculator

1. Pick a method. Use Implied volatility when your platform shows the IV of an expiry. Use ATM straddle price when you can see the at-the-money call and put. Use Earnings move to separate the announcement day from normal days.
2. Enter the price and the inputs from the option chain. Use mid prices (between bid and ask) for the straddle and the IV of the expiry you care about.
3. Choose calendar or trading days. Keep 365 with calendar days to expiry. Switch to 252 only if you also count trading days. Mixing them gives a wrong move.
4. Read the ranges. The 1σ range is price ± move. The lognormal range is the same move measured in percentage terms, so it is wider above the price than below. The probability column shows how often the price would end inside each range if the IV were exactly right.

Expected move formulas

Volatility is a standard deviation. The Options Industry Council describes it as “the annualized standard deviation of a stock’s daily price changes” and says implied volatility “is a measure of how much the marketplace expects the asset price to move based on the price of the option.” Multiplying an annual standard deviation by √t scales it to the time left, because variance grows in line with time.

365 or 252 days?

Both are in use, and the result barely changes if the day count and the IV match. What matters is not to mix them.

• Calendar days, 365. The Cboe Volatility Index methodology measures time to expiry in minutes and divides by the “Number of minutes in a 365-day year (365 x 1,440 = 525,600)”. Most option chains quote IV on this calendar basis.
• Trading days, 252. For a one-day move, many desks divide by √252. In a Cboe note on the 2024 US election, a 35% annualized forward volatility for one day was turned into a daily standard deviation of about ±2.2%. That matches 35% ÷ √252 = 2.20%; dividing by √365 would give 1.83%.

Example: IV 32%, price 150. Thirty calendar days on a 365 basis gives a 1σ move of 13.76. The same period counted as 21 trading days on a 252 basis gives 13.86, almost the same. Typing 30 calendar days with the 252 basis gives 16.56, about 20% too large.

Straddle vs expected move: 0.8, 0.85 and 1.0

Many sites say “the straddle is the expected move”. That is true in one specific sense. With the strike at the current price, no rates and no dividends, Black–Scholes gives an ATM straddle of about S × σ√t × √(2/π) ≈ 0.798 × the 1σ move. Brenner and Subrahmanyam (1988) published the matching call approximation, call ≈ 0.4 × S × σ√t. And 0.798 × σ is exactly the average absolute move of a normal distribution. So the straddle price is the market’s average absolute move, while the 1σ move is about 25% larger (straddle ÷ 0.798).

The “85% of the straddle” rule is a convention, not a derived result. Tastylive teaches it as “calculating 85% of the value of the front month at the money (ATM) straddle” and does not say where the number comes from. In the same model, 0.85 × straddle equals about 0.68σ, so it marks the range the price stays inside about half the time, not 68% of the time:

Computed in Python with the standard normal distribution; lognormal results for short expiries are almost identical. Real straddles also price skew, dividends, rates and early exercise, so the observed ratio drifts from 0.798. The calculator’s straddle tab inverts the exact model formula instead of using 0.798.

Earnings move: the term-structure method

An expiry that includes an earnings date carries two kinds of variance: normal daily movement and one large jump on the announcement day. Total variance (IV² × time) adds up, so two expiries after the same event give two equations:

This is the term-structure estimator of Dubinsky and Johannes, later published with Kaeck and Seeger in The Review of Financial Studies (2019). Cboe describes the same idea in plain terms: “a comparison between near-term volatility and longer-dated volatility results in the expected standard deviation” for the day after earnings. The method assumes the ex-event volatility is the same in both expiries. If the front-month IV is not above the back-month IV, there is no event premium to extract and the calculator says so.

After the release, the jump variance drops out of every expiry. The OIC notes that implied volatility “typically increases steadily” into the announcement and that options “tend to reprice quickly” once the uncertainty is replaced with more certainty. That drop is the IV crush.

Probability of ending inside the range

The calculator assumes the price at expiry is lognormal, as in Black–Scholes. The probability of ending above a price K is N(d₂), with d₂ = [ln(S ÷ K) + (r − σ²/2)t] ÷ (σ√t). The probability inside a range is N(d₂ at the lower bound) − N(d₂ at the upper bound). This is the risk-neutral probability, the one implied by option prices, not a real-world forecast.

For short expiries the ±1σ range holds about 68% and the ±2σ range about 95%. For long or very volatile expiries the numbers drift, because the lognormal curve is skewed: big rises are possible, falls stop at zero. The linear range then gets a lower bound below the true 1σ point, and at very high volatility it goes below zero. The lognormal range S·e^±σ√t avoids that.

r = 0. Computed with the calculator’s Python reference.

Worked examples

All three examples use a hypothetical stock “XYZ” at 150.00. The IVs and option prices are chosen for the arithmetic and are not market data.

1. From implied volatility (the default)

Hypothetical: XYZ at 150.00, IV 32%, 30 calendar days to expiry, 365-day basis, r = 0.

2. From the ATM straddle

Hypothetical: XYZ at 150.00, the 150 call costs 5.60 and the 150 put 5.40 (mid prices), so the straddle is 11.00, 30 days to expiry.

The straddle and the IV in example 1 agree: a 32% IV implies a model straddle of 10.98, and an 11.00 straddle implies an IV of 32.1%.

3. Earnings move from two expiries

Hypothetical: XYZ reports earnings in 3 days. The first expiry after the report is 9 days away with IV 62%; the next is 37 days away with IV 38%. 365-day basis.

The announcement day alone is priced like about 42 normal days of variance. This is what disappears from the front-month IV after the release.

Limits of these numbers

• IV is an estimate. Implied volatility reflects option prices today. It changes all the time and real moves often differ from it. It does not say which direction the price will go.
• Fat tails. Real returns have more large moves than the lognormal model allows. Moves outside 2σ happen more often than 4.6% of the time, especially around news.
• One volatility for every strike. The calculator ignores skew. Out-of-the-money puts usually trade at higher IV than calls, so the market’s downside tail is fatter than the chart shows.
• The straddle model is simplified. Strike = price, no rates, no dividends, European exercise. If the nearest strike is far from the price, the straddle is distorted.
• Earnings method assumptions. Both expiries must contain the same event, and ex-event volatility must be equal across them. Another event in only one expiry breaks the estimate.
• Day count. The 252 option treats every day you enter as a trading day. Holidays and weekends are not modelled separately.

FAQ

Related tools and templates

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• Black–Scholes calculator
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• Expected move spreadsheet
  The same formulas in Excel and Google Sheets, with a watchlist and an earnings log.
• Covered call calculator
  Return and break-even of selling a call against shares.
• Position size calculator
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• Risk reward calculator
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Sources

1. Options Industry Council, “Volatility & the Greeks”.
2. Options Industry Council, “The Crush Is Real”, July 2026.
3. Cboe Global Indices, “Cboe Volatility Index Mathematics Methodology” (PDF), section 3, time to expiration.
4. Cboe, “U.S. Election 2024: What the Options Data Says”, Cboe Insights.
5. Cboe, “What Options Data May Indicate About Mag 7 Earnings”, Cboe Insights, 30 July 2025.
6. Dubinsky, A., Johannes, M., Kaeck, A. and Seeger, N. J. (2019), “Option Pricing of Earnings Announcement Risks”, The Review of Financial Studies 32(2), 646–687.
7. Dubinsky, A. and Johannes, M., “Earnings Announcements and Equity Options”, working paper (PDF), Columbia Business School.
8. Brenner, M. and Subrahmanyam, M. G. (1988), “A Simple Formula to Compute the Implied Standard Deviation”, Financial Analysts Journal 44(5), 80–83.
9. tastylive, “Calculating Expected Move” (source of the 85% convention).

Web sources retrieved 13 Nov 2026.

Educational tool only, not financial or investment advice. Results come from the numbers you enter and the formulas above. Implied volatility is the market’s estimate of future movement, not a forecast or a guarantee: prices can and do move outside the ranges shown. Options can lose their full value quickly, and some option strategies can lose more than the premium. All example numbers are hypothetical.