Building an earnings options dashboard: implied move and history
Written and reviewed by ConvexValue · Updated July 25, 2026
Earnings is the one scheduled event that reliably shows up in an option chain. The expiration covering the date carries visibly more implied volatility than the one before it, and the size of that step is the market’s price for the print.
A useful earnings dashboard has two halves: what is priced in now, and what previous prints actually did.
Reading the implied move
The near-dated at-the-money straddle can provide a quick estimate. In cvforge, sum the call and put fair market value (FMV) estimates, so:
estimated implied move ≈ (ATM call FMV + ATM put FMV) ÷ spot
FMV is Massive’s proprietary valuation estimate. cvforge does not provide option bids, asks, midpoint, quote sizes, NBBO, or last trades, so this result is not the cost of an executable straddle and must be labeled as estimated. You can also derive an expected move from the supplied implied volatility.
Check which expiration you are using. The implied move belongs to a specific expiration, and the first one after the announcement is the one that contains the event. An expiration a week later includes the event plus a week of ordinary drift, which is a larger number describing something different.
The wings add direction. When put implied volatility sits well above call implied volatility for the event expiration, the chain is charging more for a disappointment than for a beat — a statement about where risk premium is concentrated, not a prediction.
The part that surprises people
Implied volatility rises into a print and collapses immediately after it. That collapse happens whether the stock moves or not, and it is a large part of what happens to an option’s value the next morning.
The practical consequence: a long option position can be directionally right about an earnings result and still lose money, because the uncertainty it paid for has been resolved. Any dashboard that shows only the implied move, without noting what happens to volatility afterwards, is telling half the story.
Comparing implied with realised
The second half of the dashboard needs history: for each previous print, what did the chain price beforehand and what did the stock actually do?
Pairing them is what turns a price into a comparison — is the market currently asking more or less than this name has typically delivered? A chain that consistently prices more than the realised move means option sellers were paid for the risk over that sample.
Two cautions, both about sample size:
- A dozen earnings dates is twelve observations, and one outlier drags any average. Read the spread of outcomes rather than the mean.
- “This name usually moves X% on earnings” is a description of a short history, not a property of the company. Business mix, size and coverage all change.
Earnings is precisely where small-sample reasoning is least reliable, and also where it is most tempting.
Fundamentals alongside
Actuals against estimates, prior periods and the news around them come from the FMP packages included on every data plan. They arrive on the provider’s schedule, so the newest quarter can briefly lag the company’s own release — check the dates before drawing a conclusion from a comparison.
Historical earnings reactions and the price path afterwards need historical price data; studying what a specific option position did through a print needs the Research plan’s end-of-day options aggregates.
Fields you need
implied_volatility, strike_price, expiration_date, underlying_price,
fair_market_value and day_volume from the options snapshot, plus estimates and
statements from FMP.
Watch it built
- What NFLX options price in before earnings
- INTC implied move plus a history of beats and misses
- How TSLA has historically moved after earnings
- IBM earnings dashboard: results against expectations
More in the earnings dashboards section, and see implied probability and expected move for the general method.
This is research and education, not investment advice.