Option Probability Calculator

Calculate the probability of your option expiring in-the-money, out-of-the-money, or reaching a target price by expiration.

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Written by Michael Torres, CFA
Senior Financial Analyst
JW
Fact-checked by Dr. James Wilson, PhD
Options Strategy Researcher
Advanced OptionsFact-Checked

Input Values

$

Current underlying price.

$

Option strike price.

days

Calendar days until expiration.

%

Annualized IV.

Select call or put.

$

Custom price target for probability.

Results

Probability of Expiring ITM
0.00%
Probability of Expiring OTM
0.00%
Probability of Reaching Target0.00%
Expected Move (1 StdDev)$0.00
68% Confidence Range0
95% Confidence Range0
Results update automatically as you change input values.

What Is Option Probability?

Option probability calculations estimate the likelihood that an option will expire in-the-money or that a stock will reach a specific price by expiration. These probabilities are derived from implied volatility and assume a log-normal distribution of stock returns (the same assumption underlying the Black-Scholes model). While not exact predictions, they provide a data-driven framework for assessing the odds of different outcomes.

Understanding probabilities is essential for options traders because it allows them to evaluate whether the premium they are paying (or receiving) is fair relative to the odds. A call option with a 25% probability of expiring ITM should cost less than one with a 60% probability. Professional options traders think in terms of probabilities and expected values rather than simple directional bets.

i
Probability ≈ Delta

For a quick probability estimate, use the option's Delta. A call with Delta of 0.30 has approximately a 30% probability of expiring ITM. A put with Delta of -0.40 has approximately a 40% probability. This approximation works well for near-term options.

Probability Formulas

Probability ITM (Call)
P(ITM) = N(d2) where d2 = [ln(S/K) + (r - sigma^2/2) × T] / [sigma × sqrt(T)]
Where:
N(d2) = Cumulative normal distribution at d2 (risk-neutral probability)
S = Current stock price
K = Strike price
sigma = Implied volatility
Expected Move
Expected Move = S × IV × sqrt(DTE / 365)
Where:
Expected Move = One standard deviation expected price change
68% range = Stock has 68% chance of staying within ± expected move
95% range = Stock has 95% chance of staying within ± 2 × expected move
Probability Calculation
Given
Stock Price
$100
Strike Price
$105 (call)
DTE
30 days
IV
30%
Calculation Steps
  1. 1Expected move = $100 × 0.30 × sqrt(30/365) = $8.60
  2. 268% range: $91.40 to $108.60
  3. 395% range: $82.80 to $117.20
  4. 4d2 = [ln(100/105) + (0.05 - 0.045) × 0.0822] / [0.30 × 0.2867]
  5. 5d2 = [-0.04879 + 0.000411] / 0.08601 = -0.563
  6. 6P(ITM) = N(-0.563) = 28.7%
  7. 7P(OTM) = 1 - 28.7% = 71.3%
  8. 8P(reaching $110) = N(d2 at $110) ≈ 15.2%
Result
This $105 call has a 28.7% chance of expiring ITM and a 71.3% chance of expiring worthless. The stock has only a 15.2% chance of reaching $110 by expiration.
Probability by Delta (Approximate)
DeltaProb ITMProb OTMTypical Use
0.8585%15%Deep ITM stock replacement
0.7070%30%Conservative directional trade
0.5050%50%ATM, maximum uncertainty
0.3030%70%Moderate OTM, income selling
0.1616%84%1 std dev OTM, iron condor wings
0.055%95%Far OTM, very low probability

Using Probabilities in Trading

1
Assess Option Pricing Fairness
Compare the probability of profit to the potential return. A trade with 30% probability should offer at least 3:1 return to have a positive expected value.
2
Size Positions by Probability
Lower-probability trades should be sized smaller. If a trade has only a 20% chance of success, risk no more than 1-2% of your portfolio.
3
Use Expected Value Framework
Expected value = (Probability of Win × Win Amount) - (Probability of Loss × Loss Amount). Only take trades with positive expected value.
4
Combine Probabilities Across Positions
Your portfolio's probability of a profitable month depends on the combined probabilities of all positions. Diversification across uncorrelated trades improves consistency.
  • Probability calculations assume log-normal distribution (may underestimate tail events)
  • Real-world probabilities differ from risk-neutral probabilities used in pricing
  • Higher IV increases the expected move and widens probability ranges
  • Probability does not account for direction, only magnitude
  • Market events (earnings, Fed) can cause moves far beyond expected ranges
~
Expected Move Before Earnings

To estimate the expected earnings move, look at the ATM straddle price for the nearest post-earnings expiration. Divide by the stock price. If the $100 stock ATM straddle costs $7, the market expects about a 7% move. Compare this to the stock's average historical earnings move to assess if the market is overestimating or underestimating the move.

!
Probabilities Are Not Certainties

Option probabilities assume normal market conditions. Black swan events, earnings surprises, geopolitical shocks, and other unexpected events can cause moves far beyond what probabilities suggest. A 95% probability of staying in a range still means a 5% chance of breaking out, and those 5% events can be catastrophic for short option positions.

Frequently Asked Questions

Option probabilities are reasonably accurate under normal market conditions but tend to underestimate the frequency of extreme moves (fat tails). Studies show that actual moves exceed the implied expected move about 30-35% of the time, slightly more than the 32% predicted by normal distribution assumptions. Despite this limitation, probabilities provide a useful framework for comparative analysis.

Sources & References

  • U.S. Securities and Exchange Commission (SEC) - Investor Education
  • Options Clearing Corporation (OCC) - Options Education
  • Chicago Board Options Exchange (CBOE) - Options Strategies
  • Hull, J.C. "Options, Futures, and Other Derivatives" (11th Edition, 2021)

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