Post-Earnings Drift Screener Excel: PEAD Anomaly Tracker for the Q1 2026 Reporting Season

A post-earnings drift (PEAD) screener in Excel ranks recent reporters by EPS surprise size, then checks whether each stock is already moving in the direction of the surprise. Post-earnings announcement drift is the documented tendency, first reported by Ball and Brown in 1968, for stocks with large earnings beats or misses to keep drifting that way for weeks after the report. The free template in this post scores 20 Q1 2026 reporters with =EARNINGSESTIMATES_EARNINGSSURPRISE_PERCENTEPSSURPRISE_CURRENT_VALUE("AAPL") for surprise, =ChangePercentMTD("AAPL") for drift, and RSI and 50-day SMA filters for momentum. It is educational, not investment advice.

See it in actionMarketXLS video

The full MarketXLS demo

Watch full demoBook a demo

Try it in your own spreadsheet

Get the free MarketXLS sample workbook (.xlsx).

Email address

Download free workbook

No account needed. MarketXLS live data requires a paid plan. Preview workbook

Explore more videos +

IntroductionHistorical DataOptions DataUse-cases

Q1 2026 PEAD Snapshot: Where the Drift Has Started

Below is a post-earnings drift screener Excel snapshot of selected Q1 2026 reporters as of May 8, 2026. The Surprise % column is the headline EPS beat or miss versus consensus, and the MTD Drift column is the month-to-date return that has accumulated since the report (the empirical drift the PEAD literature is built on).

Two things stand out. First, the big positive surprises (Amazon, Alphabet, Meta, Broadcom, Nvidia) are all printing month-to-date drift in the same direction as the surprise, which is the textbook PEAD pattern. Second, the largest negative surprises (Tesla, Intel, Boeing) are also drifting in the direction of the miss, and those drifts are happening from already-weakened technical setups (RSI in the 28 to 35 range). That combination of fundamentals plus momentum is exactly what a post-earnings drift screener Excel workbook is supposed to surface.

Download the templates:

• - Pre-filled Q1 2026 PEAD snapshot with formula references
• - Live-updating formulas, rebuilds itself when you add tickers

What Is the Post-Earnings Announcement Drift (PEAD)?

PEAD is one of the most studied anomalies in equity research. The original Ball and Brown finding from 1968, refined repeatedly through Bernard and Thomas in the 1980s and 1990s and revisited many times since, says the same thing: stocks that beat or miss consensus EPS by a wide margin tend to continue drifting in the direction of the surprise for several weeks after the report. The drift is statistically significant, it is asymmetric across deciles of surprise size, and it has survived in some form across decades of market structure changes.

Why does it persist? The leading explanations are:

• Slow analyst revisions. Sell-side estimates anchor on the prior consensus and update piecemeal as analysts publish notes through the post-earnings window. Each upgrade nudges the price.
• Institutional flow. Index inclusions, rebalances, and active manager rotations take days or weeks to react to a single quarter's print.
• Behavioral underreaction. Headlines about a "beat" land in retail flows immediately, but the structural revision in expectations diffuses more slowly.
• Liquidity and risk capacity. Short-side liquidity around large negative surprises is genuinely harder to source quickly, so misses bleed in.

PEAD does not promise outsized returns on every name. It says the expected drift in the direction of the surprise is positive on average, and bigger when the surprise size is bigger. That is exactly the kind of effect a post-earnings drift screener Excel template is designed to capture: rank by surprise size, confirm with realized drift, and pick the cleanest setups.

What This Post-Earnings Drift Screener Excel Tracks

The downloadable post-earnings drift screener Excel workbook contains six sheets:

1. How To Use - tutorial covering each sheet, what every input does, and the MarketXLS formulas required
2. Main Dashboard - the screener: 20 Q1 2026 reporters ranked by surprise, drift, and a composite PEAD score
3. Scenario Analysis - what historical drift looks like across seven surprise buckets, with a hypothetical P/L calculator
4. Strategy and Entry Rules - educational entry/stop/exit framework with momentum filters
5. Portfolio Allocation - sizing across the top conviction names with risk per name controls
6. Sector Correlation - average surprise and drift by sector to see where the cleanest reads are

Yellow cells are inputs you can edit (minimum surprise threshold, RSI gates, portfolio size, max position weight, holding period). Everything else recalculates from those inputs and from the MarketXLS formulas the template sheet pulls.

Building the Post-Earnings Drift Screener in Excel

Here are the live MarketXLS formulas the template uses. Every formula has been verified against the MarketXLS function reference before being included.

Identity and Pricing

=Name("AAPL")                 → Company name
=Sector("AAPL")               → Sector classification
=Industry("AAPL")             → Industry classification
=Last("AAPL")                 → Current price
=MarketCapitalization("AAPL") → Market cap (filter for liquidity)

Formula documentation: Name, Sector, Industry, Last, MarketCapitalization

Earnings Surprise Block (the core PEAD inputs)

=EARNINGSESTIMATES_EARNINGSSURPRISE_EPSESTIMATE_CURRENT_VALUE("AAPL")
    → Consensus EPS estimate going into the report

=EARNINGSESTIMATES_EARNINGSSURPRISE_EPSACTUAL_CURRENT_VALUE("AAPL")
    → Actual reported EPS

=EARNINGSESTIMATES_EARNINGSSURPRISE_PERCENTEPSSURPRISE_CURRENT_VALUE("AAPL")
    → % EPS surprise (the PEAD trigger)

Formula documentation: EARNINGSESTIMATES_EARNINGSSURPRISE_EPSESTIMATE_CURRENT_VALUE, EARNINGSESTIMATES_EARNINGSSURPRISE_EPSACTUAL_CURRENT_VALUE, EARNINGSESTIMATES_EARNINGSSURPRISE_PERCENTEPSSURPRISE_CURRENT_VALUE

These three formulas make the surprise calculation auditable. You see the estimate, the actual, and the published surprise. They update automatically as the dataset advances through reporting season.

Drift Confirmation

=ChangePercentMTD("AAPL")  → Month-to-date return (proxy for realized drift)
=Last("AAPL")              → Today's price
=FiftyTwoWeekHigh("AAPL")  → 52-week high
=FiftyTwoWeekLow("AAPL")   → 52-week low

Formula documentation: ChangePercentMTD, Last, FiftyTwoWeekHigh, FiftyTwoWeekLow

Month-to-date return is the simplest way to confirm a stock is drifting in the same direction as the surprise. If a name beat by 10% but is flat or down on the month, the drift is not happening and the setup is weaker.

Momentum Filter

=RSI("AAPL")                          → 14-day Relative Strength Index
=SimpleMovingAverage("AAPL", 50)      → 50-day SMA
=Beta("AAPL")                         → Stock beta vs market

Formula documentation: RSI, SimpleMovingAverage, Beta

The PEAD literature shows the drift is much cleaner when momentum is in the same direction as the surprise. The Excel screener uses RSI greater than 55 plus price above the 50-day SMA for longs, and the inverse for shorts.

Quality and Liquidity Filters

=AverageDailyVolume("AAPL")   → Liquidity floor
=NumberOfAnalysts("AAPL")     → Coverage breadth
=GrossMargin("AAPL")          → Quality check
=OperatingMargin("AAPL")      → Quality check

Formula documentation: AverageDailyVolume, NumberOfAnalysts, GrossMargin, OperatingMargin

The screener filters out names with thin coverage or low daily volume. PEAD is most reliable in the deeply-covered, liquid universe because that is where the surprise truly is news to the marginal analyst.

The PEAD Score: One Number to Rank the Watchlist

The Main Dashboard ranks each ticker by a simple PEAD score:

PEAD Score = 0.6 * Surprise % + 0.4 * MTD Drift %

This blend rewards both the size of the surprise and the realized drift confirmation. A name like Amazon with +15.5% surprise and +7.9% drift scores +12.5. A name like Apple with +3.0% surprise and +2.1% drift scores +2.6. The sign of the score sets the direction (positive = long candidate, negative = short candidate), and the absolute value sets the conviction.

The Action column then layers on the momentum filter:

=IF(AND(L{r}="LONG", J{r}>=$B$6, H{r}>0), "BUY",
 IF(AND(L{r}="SHORT", J{r}<=$B$7, H{r}<0), "SELL", "WAIT"))

This formula reads: if the direction is LONG and the RSI is above the configured threshold and the drift is already positive, mark the name as BUY. If the direction is SHORT and RSI is below the short threshold and drift is already negative, mark it as SELL. Otherwise, WAIT. Everything is configurable from the yellow input cells, so you can tighten or loosen the filters depending on how aggressive you want the screen.

Scenario Analysis: How Drift Stacks Up by Surprise Bucket

The Scenario Analysis sheet groups reporters into seven surprise buckets. The figures below are illustrative assumptions for the calculator, not measured backtest results or a forecast:

The illustrative pattern mirrors what the PEAD literature describes: the clearest signal is at the extremes. Small beats and small misses are within the noise band. Strong beats and strong misses are where the historical drift and hit rate both meaningfully exceed a coin flip. The takeaway for a post-earnings drift screener Excel workflow is to focus your attention on the tail buckets and ignore the middle of the surprise distribution.

The Approach: Educational PEAD Strategy Framework

This section is educational only and is not investment advice. You should always do your own work, factor in your own risk tolerance, and consult a licensed advisor before acting on anything you read in a market analysis post.

The Strategy and Entry Rules sheet codifies a simple seven-step process for working a post-earnings drift screener Excel template:

1. Universe. Limit the watchlist to companies that reported in the last 21 trading days and have more than five covering analysts.
2. Surprise gate. Require an absolute EPS surprise of 5% or more (configurable in the dashboard).
3. Drift confirmation. The MTD return must agree with the surprise sign. Beat plus rally for longs, miss plus selloff for shorts.
4. Momentum filter. Long candidates need RSI greater than 55 and price above the 50-day SMA. Short candidates need RSI less than 45 and price below the 50-day SMA.
5. Liquidity floor. Average daily volume must be at least one million shares. Skip thin names.
6. Position sizing. Risk no more than 1% of portfolio capital per name, with a configurable max weight per position.
7. Time stop. Hold approximately 45 trading days unless the surprise sign reverses (a guidance cut, for example) or the RSI breaks the entry filter.

The framework is deliberately simple. The framework relies on patience and disciplined exits rather than complex signals.

Sector Correlation: Where the Q1 2026 Drift Lives

The Sector Correlation sheet aggregates the watchlist by sector. For Q1 2026, the cleanest aggregate reads land in Communication Services and Technology (large-cap AI and cloud names beating and drifting positively), while Industrials and Healthcare are the messier reads (mixed surprises with weak follow-through). Consumer Discretionary is bifurcated: Amazon and Home Depot are positive PEAD setups, while Tesla is the most extreme negative setup in the entire universe.

This sector view is useful for two reasons. First, it tells you where the broad-based momentum is and where you may want to overweight your stock picks. Second, it warns you when a single sector is generating most of the noise, which means PEAD signals inside that sector should be discounted.

How To Use the Post-Earnings Drift Screener Excel Template

When you open the template file with the MarketXLS Excel add-in installed and signed in, the workflow is:

1. Edit the input cells on the Main Dashboard. Set the minimum absolute surprise threshold, the RSI thresholds, your portfolio size, and your max weight per position.
2. Add or remove tickers from the screener. The sample template ships with 20 Q1 2026 names. You can paste your own watchlist into the Ticker column and the formulas will pull every other field automatically.
3. Wait for formulas to resolve. First open of the template can take 10 to 30 seconds while MarketXLS pulls live values.
4. Sort by PEAD Score to see the top long and short candidates.
5. Open the Scenario Analysis sheet to size your conviction against the historical drift averages for the surprise bucket each name lives in.
6. Use the Portfolio Allocation sheet to translate conviction into target weights and dollar allocations.
7. Use the Sector Correlation sheet to sanity-check whether the longs and shorts are diversified across sectors or stacked into one corner of the market.

The whole point is to put the entire PEAD workflow on a single page so that during a fast-moving reporting season you can rank, confirm, and size without flipping between four tools.

Common Mistakes With PEAD Screens

A post-earnings drift screener Excel workbook is only as good as the discipline behind it. Common pitfalls:

• Over-fitting the surprise gate. A 5% absolute surprise threshold is a reasonable starting point. Setting the threshold too high (say 20%) leaves you with two or three names per quarter and no statistical breadth.
• Ignoring guidance. EPS surprise is the headline number, but a guidance cut or raise often dominates the post-print reaction. The screener does not capture guidance directly; you should read the press release for any name you are about to size.
• Forcing PEAD into illiquid names. The drift is most reliable in the deep, liquid, well-covered universe. The screener has a volume filter for a reason.
• Holding past the drift window. PEAD historically plays out over 30 to 60 trading days. Beyond that, the signal decays and the next quarter starts to dominate. The template suggests a 45-day time stop.
• Treating PEAD as a market-timing tool. It is not. It is a relative-momentum overlay on top of fundamental events. Macro headwinds (Fed surprises, recessions, geopolitics) can flatten the entire setup quickly.

Why Build It in Excel With MarketXLS

There are dedicated screener products that surface earnings surprises. The reason you might still want a post-earnings drift screener Excel workbook of your own is control:

• You decide which surprise definition you trust.
• You decide which momentum filter to layer on.
• You decide what counts as a quality name (margin floor, analyst breadth, liquidity).
• You decide how to size and how to exit.

MarketXLS supplies the live data layer (price, surprise, drift, momentum, fundamentals) so you do not have to maintain a fragile data feed. You supply the strategy logic. The whole thing lives in one workbook you can audit, version, and extend. If you are an advisor or self-directed investor, that combination is hard to replicate inside a hosted product.

For more on the underlying data and formulas, see the MarketXLS Excel functions reference and the MarketXLS earnings analysis features. If you want to extend the workbook into options structures around earnings reports, the iron condor strategy guide and the implied volatility screener walkthrough are useful starting points.

Frequently Asked Questions

What is a post-earnings drift screener Excel template used for?

A post-earnings drift screener Excel template is used to systematically rank reporters by their EPS surprise size and confirm whether the stock is already drifting in the direction of the surprise. The output is a short, ranked list of PEAD candidates for further research.

How is post-earnings announcement drift (PEAD) defined?

PEAD is the empirical pattern that stocks beating consensus EPS tend to continue rising for several weeks after the report, and stocks missing consensus EPS tend to continue falling. It has been documented in academic literature since 1968 and is one of the most persistent equity-market anomalies on record.

Which MarketXLS formulas power the screener?

The core formulas are =EARNINGSESTIMATES_EARNINGSSURPRISE_PERCENTEPSSURPRISE_CURRENT_VALUE("TICKER") for the surprise size, =ChangePercentMTD("TICKER") for realized drift, =RSI("TICKER") for momentum, =SimpleMovingAverage("TICKER", 50) for the trend filter, and =Last("TICKER") for current price. The downloadable template embeds all of them.

How long does the post-earnings drift typically last?

The classical PEAD literature finds the drift extends approximately 30 to 60 trading days after the report, with most of the movement clustered in the first three to four weeks. The template suggests a 45-day time stop as a reasonable middle of that range.

Does PEAD work in every market environment?

PEAD is a relative-momentum overlay, not a market-timing strategy. It tends to weaken when macro shocks dominate the tape (FOMC surprises, recessions, geopolitical events) because in those environments idiosyncratic earnings news gets overwhelmed by systematic flow. Always combine the screener output with your read on the broader market.

Can I use this template with my own watchlist?

Yes. The template is built around a flexible Ticker column. Paste any list of US-listed equities into the screener and the MarketXLS formulas will pull surprise, drift, momentum, and quality data automatically. The PEAD score, direction, and action columns recalculate based on the input thresholds you set in the yellow cells.

The Bottom Line

The post-earnings drift screener Excel workbook in this post turns a well-known equity-market anomaly into a repeatable, auditable workflow. You set the surprise threshold, the momentum filters, and the position-sizing rules. MarketXLS supplies the live data through =EARNINGSESTIMATES_EARNINGSSURPRISE_* formulas, =ChangePercentMTD, =RSI, and the rest of the formula stack. The output is a short, ranked list of PEAD candidates that you can pair with your own fundamental and macro work.

The Q1 2026 reporting season is mostly behind us, and the same workflow applies to every future season: download the template, plug in your watchlist, and let the screener do the ranking work. The names in the table are examples of how the formulas behave, not recommendations.

To learn more about MarketXLS and how it can power your equity research and Excel-based analysis, visit marketxls.com or book a demo.

Educational content only. Past drift averages do not predict future returns. Nothing in this post is investment advice.