Standardized Unexpected Earnings (SUE)

Standardized Unexpected Earnings is a measure of how surprising a company's reported earnings were, expressed in standard deviations rather than raw dollars or percentages. It scales the earnings surprise by how volatile that company's surprises usually are, so a beat can be judged as large or small relative to the firm's own history. SUE is the classic quantitative signal behind the post-earnings-announcement drift anomaly.

Why standardize

A raw earnings surprise, actual minus expected, is hard to compare across companies. A $0.05 beat is enormous for a stable utility whose earnings barely move and trivial for a volatile tech company that routinely swings by dollars. Dividing the surprise by the standard deviation of past surprises puts every company on the same scale: SUE answers "how many standard deviations away from expected was this result?" A SUE of 3 means a beat three times larger than the company's typical surprise, genuinely unusual, while a SUE of 0.2 is noise.

The formula

SUE = (Actual EPS - Expected EPS) / Standard Deviation of Past Surprises

Expected EPS is usually the analyst consensus or a time-series forecast. The denominator is the standard deviation of the company's historical earnings surprises.

Worked example

A company reports EPS of $1.20 against a consensus of $1.00, a $0.20 surprise. Over the prior several years, the standard deviation of its earnings surprises has been $0.08.

SUE = ($1.20 - $1.00) / $0.08 = 2.5

A SUE of 2.5 means the beat was 2.5 standard deviations above what the company typically delivers, a strong, statistically meaningful surprise. Compare that to a company that beat by the same $0.20 but whose surprise standard deviation is $0.40:

SUE = $0.20 / $0.40 = 0.5

Same dollar beat, but a SUE of only 0.5, well within normal noise. The standardization reveals that the first beat is the real signal.

The link to post-earnings drift

Researchers found that stocks with high positive SUE tend to keep outperforming for weeks after the report, and stocks with very negative SUE keep underperforming, a pattern called post-earnings-announcement drift. The market appears to underreact to genuine earnings surprises, so the information gets priced in gradually rather than instantly. Ranking stocks by SUE and tilting toward the highest deciles has been one of the more durable quantitative signals in equity research, though it has weakened as it became widely known and trading costs eat into the edge for smaller names.

How to use it

SUE turns a messy earnings-surprise number into a comparable, rankable score. Systematic investors sort the universe by SUE each earnings season and overweight the strongest positive surprises. For a discretionary investor, SUE is a reminder to weigh a beat against the company's own volatility: a headline beat means little from a firm that always beats, while a large SUE from a normally predictable company is a signal worth investigating.