One of the oldest anomalies in finance says prices keep moving in the direction of an earnings surprise for weeks after the report. We fixed it into a precise rule and ran it on five years of S&P 500 data. The drift is there, it is concentrated in the strongest beats, and it is real but modest once the easy assumptions are stripped out.
When a company reports earnings that beat expectations, the price jumps on the day. The question that has occupied researchers since the 1960s is what happens next. The finding, repeated across decades and markets, is that the price keeps drifting in the direction of the surprise for weeks afterwards, as if the market digests the news slowly rather than all at once. This note takes that claim, post-earnings announcement drift, and tests it on a broad sample of S&P 500 companies over the last five years, with no curve-fitting and no fabricated numbers.
The easy read: the drift is famous and robust, so buying every positive surprise must be a reliable way to make money.
Our reading: the effect is real but small, it lives mostly in the extreme positive surprises, and it is measured here before costs and on todays index. As a standalone trade the after-cost margin is thin. Its value is as one disciplined, diversified tilt among several, which is exactly how the literature frames it.
Nothing here is a forecast about any single company. The exercise is to take a claim that is easy to assert, fix it into a precise rule, run it on real reported earnings and real prices, and report what actually held.
The original observation is one of the oldest in empirical finance. Ball and Brown (1968) showed that the market does not fully impound an earnings surprise on the announcement day. Bernard and Thomas (1989) sharpened it into the form traders still use: rank companies by how far their reported earnings beat or missed expectations, and the gap between the best and worst groups keeps widening for up to a quarter afterwards. More recent work, including Kaczmarek and Zaremba (2025), finds the effect persists in modern data once it is measured carefully.
The usual explanation is behavioural. Information diffuses slowly: not everyone updates on the day, attention is limited, and large institutions accumulate or distribute gradually through the following weeks to avoid moving the price against themselves. The result is a stock that keeps drifting in the direction of its surprise while the news is digested. Whether the cause is slow attention or a risk premium for holding through the uncertainty, the pattern in the data is consistent.
A surprise is information. If the market priced it instantly, there would be a jump and then noise. Instead there is a jump and then a drift, and the drift is what a patient investor can try to harvest.
For every quarterly report in the sample we computed the surprise as reported earnings per share minus the consensus estimate, scaled by the size of the estimate, and sorted all events into five quintiles from the most negative to the most positive. We then skipped the announcement day entirely and measured each stock's cumulative return from the next trading day out to sixty trading days, subtracting the return of the S&P 500 over the identical window so the result is market-adjusted. The long-short portfolio holds the top quintile and shorts the bottom, equally weighted, with positions overlapping as new reports arrive.
The sample is the current S&P 500 constituent set with daily price coverage from mid-2021, which introduces survivorship: companies that left the index are not in it. Windows overlap, positions are equally weighted, and no trading costs, slippage or financing are deducted. This is an honest event study of the effect, not a live trading record. Each of these choices tends to flatter the result, and we read the numbers with that in mind.
The clearest way to see the effect is to average the path of every stock after its report, grouped by surprise. The most positive surprises climb steadily; the most negative drift sideways to slightly down. The two lines pull apart over the full sixty days, which is the signature of drift rather than an instant repricing.
Averaging the sixty-day outcome by quintile makes the concentration plain. Only the most positive surprises produce a clearly positive market-adjusted return. The middle and lower groups are flat to negative, and the monotonic ranking that the textbook version promises is only really visible at the extreme. In practice this means the tradeable signal is the strong beat, not the full ranking.
Assembling the events into a single market-neutral book, long the top quintile and short the bottom with overlapping holds, gives a portfolio that compounds steadily over the five years with no large equity-market exposure. Growth of one unit reaches about 1.59, with an annualised Sharpe ratio near 1.28 before costs. A long-only version that simply holds the top quintile does almost as well, consistent with the long side carrying the effect.
Post-earnings drift survives the test. Companies that strongly beat expectations keep outperforming the market for weeks, the effect is steady enough to build a market-neutral portfolio around, and the Sharpe ratio is respectable. The honest qualifications are equally clear: the strength is in the long side, the short side has faded, and the headline numbers are gross of the costs that this kind of high-turnover strategy would actually pay.
The market does not ignore good news. It just takes its time.
This document has been prepared by Iron Hall Capital for informational and educational purposes. Its content does not constitute personalised investment advice, a recommendation to buy or sell financial instruments, a public offering, or a solicitation to subscribe to any financial product. The opinions and readings reflect Iron Hall Capital's judgement at the date of publication, are based on data considered reliable but not independently audited, and may be revised without notice.
The results shown are from historical simulations on past data. Backtested performance is hypothetical, is computed with the benefit of hindsight, does not reflect trading costs, financing, taxes, slippage or the market impact of real execution, and is not a reliable indicator of future results. Where a data series was not available, an equivalent real series has been substituted and labelled as such in the text. Where a method ignores costs or makes a simplifying assumption, this is stated. Markets can move sharply and without warning.
The author and Iron Hall Capital may hold, have held, or come to hold positions in the instruments referenced. Any reproduction, in whole or in part, requires written authorisation.
Iron Hall Capital · A private investment office · June 2026