Where to Find Historical Earnings Implied vs Realized Move Data

A per-ticker track record of how each earnings move was priced versus how it actually moved, available from Alphanume.

Every earnings season the same question comes up: is this name's straddle expensive or cheap relative to how it usually moves? Answering it properly means knowing, for each past report, what the options market implied and what the stock actually did. That history is tedious to assemble, because you have to capture the pre-earnings straddle at the right moment and match it to the realized move after the report.

Alphanume maintains that history as the Earnings Implied vs Realized dataset.

What the dataset is

This dataset is a per-ticker track record of how each earnings move was priced (using the pre-earnings at-the-money straddle) versus how it actually moved (the realized return). It carries running, point-in-time statistics: an over-pricing or under-pricing hit rate, the trailing average implied move, the trailing average realized move, and the average over-under. It is updated daily at end of day and fixed once the post-earnings session resolves.

Key fields

• ticker, date, time (before market open or after market close)
• straddle, implied_move_pct, implied_move_dollars, atm_iv
• realized_return_pct, realized_abs_move_pct, over_under_pct, move_ratio, overpriced
• eps_estimated, eps_actual
• running stats: n_events_to_date, hit_rate_to_date, avg_implied_move_to_date, avg_realized_abs_to_date, avg_over_under_to_date

What you can do with it

• Answer whether a given ticker tends to over-price or under-price its earnings.
• Rank names by straddle tendency ahead of earnings season.
• Quantify the implied-versus-realized edge for volatility selling or buying.
• Backtest earnings strategies on a clean, point-in-time history.

How to access it

The dataset is on the free tier as a rolling 30-day delayed window. Query a single name's full history:

curl "https://api.alphanume.com/v1/earnings-move-history?ticker=AAPL&api_key=alp_your_key"

Grab a free Alphanume API key, read the API documentation, or explore it on Alphanume to browse the data.

Why the running statistics matter

A single earnings reaction tells you almost nothing. What you want is the track record: across many reports, did this name's pre-earnings straddle tend to over-price or under-price the actual move? That requires capturing the straddle at the right moment before each report and matching it to the realized move after, then maintaining running statistics that only ever reflect events known to date.

Alphanume keeps that history per ticker, including the to-date hit rate, average implied move, average realized move, and average over-under. Because those running figures are point-in-time and fixed once the post-earnings session resolves, you can build an earnings strategy on them without accidentally training on the very events you are trying to predict.

Frequently asked questions

What does this dataset track?

For each earnings event, what the options market implied (via the pre-earnings at-the-money straddle) versus what the stock actually moved. It carries running statistics like the over-pricing hit rate and trailing average moves.

How is the implied move measured?

From the pre-earnings at-the-money straddle, expressed as implied_move_pct and implied_move_dollars, with the at-the-money implied volatility in atm_iv.

When does a record become final?

It is updated daily at end of day and fixed once the post-earnings session resolves, so the realized move and the over-under are locked in after the reaction.

Does it include EPS data?

Yes. Each event carries eps_estimated and eps_actual alongside the move and pricing fields.

Is it free to use?

Yes, on the free tier as a rolling 30-day delayed window. Pro raises the rate limit to 600 requests per minute.