Expected Move Calculator

Earnings announcements are the single most common use case for expected move calculations. Before every earnings report, the options market prices in a specific move size — and the stock either stays within that range or breaks out of it. Your strategy depends on which side of that bet you want to take.

How to read the earnings expected move:

• Look at the at-the-money straddle price for the nearest expiration after earnings. This is the market's best estimate of the total expected move (in dollars).
• Alternatively, use the IV of the front-month options in this calculator to compute the expected move over the number of days until earnings.
• Compare the implied expected move to the stock's historical average earnings move. If the stock typically moves 5% on earnings but IV implies 8%, the options are expensive relative to history.

Strategies based on expected move:

• Selling inside the expected move — Iron condors or short straddles with strikes within the expected range. You profit if the actual move is smaller than what IV implied. This wins roughly 68-85% of the time but has unlimited risk on straddles.
• Buying outside the expected move — Long strangles with strikes beyond the 1σ range. You need a bigger-than-expected move to profit. Lower win rate but asymmetric upside on blowout earnings.
• Directional plays — If you have conviction on direction, the expected move helps you choose realistic target strikes and size the position appropriately.

Important caveat: After earnings, IV collapses (called IV crush). Even if you correctly predict the direction, buying options into earnings means fighting vega decay. Many profitable earnings trades are structured as spreads to reduce IV crush exposure.

The sigma levels refer to standard deviations from the mean of a normal distribution. Each level represents a different confidence interval for where the stock price might land at the end of the period.

The three standard levels:

• 1σ (68.3% probability) — There is a roughly 68% chance the stock will be within one expected move of the current price. This is the standard "expected move" that traders reference. About 1 in 3 times, the stock will move beyond this range.
• 2σ (95.4% probability) — The stock will be within two expected moves about 95% of the time. Moves beyond 2σ happen roughly 1 in 20 times. This is the range most iron condor and strangle sellers target — setting their short strikes at or beyond 2σ gives a high probability of profit.
• 3σ (99.7% probability) — Moves beyond three standard deviations are extremely rare in a normal distribution (3 in 1,000). In practice, however, stocks experience 3σ moves more often than the model predicts because of fat tails and gap risk.

Practical application for strike selection:

• Selling options with strikes at 1σ gives you higher premium but only ~68% probability of keeping it all — the stock breaches one side about one-third of the time.
• Selling at 2σ collects less premium but gives you ~95% probability of profit. This is the sweet spot for many income strategies.
• The tradeoff is always between credit received and probability of success. Wider ranges mean higher win rates but lower per-trade income.

Remember that these probabilities assume a log-normal distribution. Real markets exhibit skewness (bigger down moves than up moves) and kurtosis (more extreme moves than a bell curve predicts). Use sigma levels as a guide, not a guarantee.

Both the expected move (from IV) and the implied move (from straddle pricing) estimate the same thing — how much the market expects a stock to move. But they calculate it differently and can give slightly different numbers.

Expected move from IV (this calculator):

• Uses the annualized implied volatility from the options chain
• Formula: Price × IV × √(Days/365)
• Gives a one-standard-deviation (68%) range
• Works at any time horizon and does not depend on a specific strike or option price

Implied move from straddle:

• Uses the actual dollar price of the at-the-money straddle (call + put at the same strike)
• The straddle price itself is the implied move — the market is saying the stock needs to move at least that far for the straddle buyer to break even
• More commonly used for near-term events like earnings because it gives a concrete dollar amount
• A quick approximation: Implied move ≈ Straddle price × 0.85 (accounting for the fact that the straddle includes time value beyond just the expected move)

When they diverge: The two approaches give similar results when IV is relatively flat across strikes and the option pricing is efficient. They may diverge when there is significant skew, when the ATM strike does not match the current stock price closely, or when the term structure of IV is steep (near-dated IV much higher than far-dated).

For earnings trades, the straddle-based approach is more popular because it directly answers: "How much does the stock need to move for me to profit buying this straddle?" For general volatility analysis and strike selection over various time horizons, the IV-based expected move (this calculator) is more flexible.

The square root of time in the expected move formula is a direct consequence of how random walks and Brownian motion work. It is one of the most important mathematical relationships in finance, and understanding it helps you correctly scale expected moves across different time horizons.

The intuition:

If a stock has independent daily returns, the variance (not standard deviation) of those returns adds up linearly over time. Over N days, the total variance is N times the daily variance. Since standard deviation is the square root of variance, the standard deviation over N days is √N times the daily standard deviation.

Practical implications:

• Doubling the time does not double the expected move. A 30-day expected move is not twice the 15-day expected move. It is √2 ≈ 1.41 times as large. Volatility grows slower than linearly.
• The first few days matter most. Going from 1 day to 7 days (√7 ≈ 2.65x increase in expected move) adds far more risk than going from 30 days to 36 days (√36/√30 ≈ 1.10x). This is why short-term options experience time decay (theta) that accelerates as expiration approaches.
• Weekend effect: Some traders debate whether to use calendar days (365) or trading days (252) in the denominator. Calendar days are the convention because IV is typically quoted on a calendar-day basis, but the choice affects the result. This calculator lets you toggle between both.

Example: A stock with 30% annual IV has a daily expected move of 30% × √(1/365) = 1.57%. Over one week (7 days), the expected move is 30% × √(7/365) = 4.16%. Notice this is √7 ≈ 2.65 times the daily number, not 7 times.

This square-root scaling is a core reason why longer-dated options are proportionally cheaper per day than shorter-dated ones — you get more time but the expected move does not increase proportionally.

The expected move calculation assumes stock returns follow a log-normal distribution (equivalently, that log returns are normally distributed). This is the same assumption underlying the Black-Scholes model. While it is a useful approximation, real markets deviate from this assumption in several important ways.

Key limitations:

• Fat tails (kurtosis) — Real stock returns have more extreme moves than a normal distribution predicts. A 3σ move should happen about 0.3% of the time, but in practice, large drops and surges occur far more often. Events like the March 2020 COVID crash involved daily moves that were 5-10 standard deviations — essentially impossible under a normal distribution.
• Negative skewness — Stock returns tend to be negatively skewed, meaning large down moves are more likely than equally large up moves. The expected move calculation treats both directions symmetrically, but in reality, crash risk is higher than melt-up risk.
• Volatility clustering — High- volatility days tend to be followed by more high-volatility days. The model assumes constant volatility over the period, but real markets go through calm and turbulent regimes.
• Gaps and jumps — Stocks can gap overnight on earnings, M&A announcements, or macro events. The continuous-time framework does not account for these discrete jumps.

What this means for your trading:

• The 1σ (68%) range is reasonably reliable for typical market conditions.
• The 2σ and 3σ ranges understate the true probability of extreme moves. Do not rely on the 95% or 99.7% figures as hard guarantees — tail risk is real.
• When selling options at extreme strikes (far OTM), the premium you collect may not adequately compensate for the fat-tail risk of a massive adverse move.

Despite these limitations, the expected move framework remains the industry standard because it is simple, intuitive, and "good enough" for most decision-making. Just treat the sigma boundaries as guidelines rather than guarantees.

The expected move is one of the most practical tools for deciding where to set your option strikes. Whether you are selling credit spreads, buying debit spreads, or trading naked options, the expected move gives you a probability-based framework for strike selection.

For premium sellers (credit spreads, iron condors, strangles):

• Short strikes at 1σ — You collect more premium but the stock breaches your strikes about one- third of the time. Best for high-conviction trades where you believe IV is overstating the actual move.
• Short strikes at 1.5σ — A balanced approach with roughly 87% probability of profit. Many income traders use this as their default.
• Short strikes at 2σ — About 95% probability of success. Premium is thinner, so you need wider wingspan or more contracts to make it worthwhile. Common for conservative income strategies.

For premium buyers (long calls, long puts, debit spreads):

• Buy strikes within the 1σ range for a reasonable probability of the option having intrinsic value at expiration.
• For directional bets, use the expected move to set realistic profit targets. If the expected move is $10, buying a call $15 OTM needs a move beyond 1.5σ — that's a lower-probability trade.
• For debit spreads, set the long leg ATM or slightly ITM, and the short leg near the expected move boundary to capture most of the likely range.

Quick framework:

• Calculate the expected move for your timeframe using this calculator.
• Overlay that range on the options chain. Strikes inside the range have a higher probability of being breached; strikes outside have a lower probability.
• Choose your strikes based on the probability that aligns with your risk tolerance and account size.

Always remember that the expected move is derived from IV, which itself is a market consensus. If you have a reason to believe the actual move will be larger or smaller than the consensus, that disagreement is your trading edge.

Because the expected move scales with the square root of time, not linearly, the relationship between holding period and risk is non-intuitive. Understanding this scaling has real implications for strategy selection and position management.

The time sensitivity table:

For a $150 stock at 30% IV, the expected move at different horizons illustrates the square-root effect:

• 1 day: ±$2.35 (1.6%)
• 7 days: ±$6.24 (4.2%) — not 7x the daily, but √7 ≈ 2.65x
• 30 days: ±$12.90 (8.6%)
• 90 days: ±$22.35 (14.9%) — only √3 ≈ 1.73x the 30-day number, not 3x

Why this matters for trading:

• Theta acceleration — Options lose time value faster as expiration approaches precisely because the remaining expected move shrinks non-linearly. Selling options with 30-45 DTE captures the steepest part of the theta curve.
• Rolling decisions — Rolling a 7-DTE short option to 30 DTE only adds √(30/7) ≈ 2.07x more expected move, but you get 23 more calendar days. This is why rolling often makes sense — you get proportionally more time than additional risk.
• Earnings timing — If earnings are in 2 days, the expected move is much smaller than if earnings are in 30 days. But the stock might gap the same amount either way. This mismatch is why short-dated options right before earnings carry outsized gamma risk relative to their expected move.
• Portfolio risk — A position with 90-day options does not have 3x the risk of a 30-day position — it has about 1.73x. This matters for margin calculations and portfolio risk management.

The time sensitivity table in this calculator lets you see these relationships at a glance, so you can choose the expiration that best balances your probability target with your premium and theta objectives.