Earnings Surprise Screener Excel: Track Q1 2026 Earnings Beats and Misses in Real Time

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An earnings surprise screener in Excel lists your tickers next to their consensus EPS estimate, their reported EPS surprise, and their next report date, so you can see at a glance which companies beat or missed expectations. With MarketXLS, the core columns are =EPSSurprisePercent("AAPL") for the surprise, =EPSEstimateCurrentQ("AAPL") for the current-quarter consensus, and =earnings_date("AAPL") for timing. This guide builds that screener for 15 large US stocks ahead of Q1 2026 earnings season (written April 4, 2026, with banks reporting from April 11).

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Earnings surprise screener Excel dashboard showing Q1 2026 EPS beats and misses with MarketXLS formulas

The steps below cover each formula, an earnings quality score, and a pre-earnings run-up check. The downloadable templates at the bottom of this article include six fully built sheets covering everything from a main dashboard to scenario analysis, sector comparisons, and portfolio positioning frameworks.

Q1 2026 Earnings Season at a Glance

Before diving into the screener build, here is a snapshot of 15 major stocks heading into earnings season. This table shows the current EPS estimates, previous quarter surprise percentages, and upcoming report dates.

TickerPriceEPS Est Curr QPrevious Surprise %Earnings DateSector
AAPL$198.50$1.82+8.7%Apr 24Technology
MSFT$445.20$3.28+7.2%Apr 22Technology
GOOGL$182.30$1.95+10.1%Apr 22Technology
AMZN$215.80$1.48+26.5%Apr 24Technology
META$585.40$5.72+17.4%Apr 23Technology
NVDA$142.60$0.82+17.1%May 21Technology
JPM$228.50$4.65+8.9%Apr 11Financials
BAC$42.80$0.84+6.3%Apr 15Financials
WFC$68.90$1.32+6.5%Apr 11Financials
JNJ$162.40$2.52+1.6%Apr 15Healthcare
UNH$548.20$6.85+8.2%Apr 15Healthcare
XOM$118.50$2.58-4.5%Apr 25Energy
CVX$165.80$3.52-2.2%Apr 25Energy
PFE$28.40$0.28+7.7%Apr 29Healthcare
TSLA$285.60$0.78+23.8%Apr 22Technology

This data serves as the foundation for the screener. Every single value in this table can be pulled live in Excel using MarketXLS formulas, which means your screener updates automatically as new estimates and results come in.

Why Earnings Surprises Matter in Q1 2026

Earnings surprises have always been a critical catalyst for stock price movements, but several factors make them especially relevant this quarter.

The Inflation Backdrop

With Brent crude trading above $109, input costs are elevated across nearly every industry. Companies that manage margins effectively in this environment deserve attention. Energy companies like ExxonMobil and Chevron face an interesting dynamic where high oil prices boost revenue but also raise questions about sustainability and capital allocation. For technology companies, the inflation story is different because their cost structures are less tied to commodity prices, but consumer spending patterns and enterprise budget decisions still reflect the broader inflationary environment.

The Strong Dollar Effect

A strong U.S. dollar creates headwinds for multinational companies reporting overseas earnings. When you screen for earnings surprises, it helps to understand which companies have significant international revenue exposure. A company like Apple generates roughly 60% of its revenue outside the United States, so currency translation effects can meaningfully impact whether it beats or misses consensus estimates.

AI Spending and Capital Expenditure

The technology sector is spending aggressively on artificial intelligence infrastructure. Companies like Microsoft, Google, Amazon, and Meta have committed billions to AI data centers, custom chips, and model development. Investors want to know whether this spending is translating into revenue growth or creating margin pressure. Earnings surprises in Q1 2026 will reveal a lot about the return on these AI investments.

Interest Rate Environment and Financials

Banks report first during earnings season, and their results often set the tone for the rest of the market. With the Federal Reserve navigating a complex rate environment in 2026, net interest income, loan growth, and credit quality are the key metrics. JPMorgan, Bank of America, and Wells Fargo reporting in mid-April will provide early signals about the health of the consumer and corporate borrower.

Building the Earnings Surprise Screener in Excel

Build the screener in six steps. Each MarketXLS formula pulls data into its cell, so there is no copying from websites.

Step 1: Set Up Your Ticker List

Start with a column of tickers in column A. You can use the 15 stocks from our template or customize the list to match your watchlist. In the template, these are yellow input cells so you can change them at any time.

Step 2: Pull Current Prices

In the column next to your tickers, use the QM_Last function to get the current stock price:

=QM_Last("AAPL")

Formula documentation: QM_Last

This returns the latest trading price for Apple from QuoteMedia. The quote is 15-minute delayed on the Standard plan and real-time on the Advanced and Business plans.

Step 3: Get EPS Data

The core of any earnings surprise screener is the EPS data. MarketXLS provides several specialized functions for this:

Trailing Twelve Month EPS:

=EarningsPerShare("AAPL")

Formula documentation: EarningsPerShare

Current Quarter EPS Estimate:

=EPSEstimateCurrentQ("AAPL")

Formula documentation: EPSEstimateCurrentQ

Current Year EPS Estimate:

=EPSEstimateCurrentY("AAPL")

Formula documentation: EPSEstimateCurrentY

Next Quarter EPS Estimate:

=NextQuarterEPSEstimate("AAPL")

Next Year EPS Estimate:

=NextYearEPSEstimate("AAPL")

These functions give you a complete picture of where the analyst consensus sits for each company. By comparing estimates across different time horizons, you can assess whether the growth trajectory is accelerating or decelerating.

Step 4: Track Earnings Surprises

The two most important functions for the screener are:

EPS Surprise (Dollar Amount):

=EPSSurprise("AAPL")

Formula documentation: EPSSurprise

This returns the difference between the actual reported EPS and the consensus estimate. A positive number means the company beat expectations.

EPS Surprise Percentage:

=EPSSurprisePercent("AAPL")

Formula documentation: EPSSurprisePercent

This returns the surprise as a percentage, which is more useful for comparisons across companies with different EPS levels. A $0.10 beat means very different things for a stock earning $0.50 per quarter versus one earning $10 per quarter.

Step 5: Add Earnings Dates

Knowing when each company reports is critical for timing your analysis:

Next Earnings Date:

=earnings_date("AAPL")

Formula documentation: earnings_date

Previous Earnings Report Date:

=PreviousEarningsReportDate("AAPL")

Formula documentation: PreviousEarningsReportDate

Previous Earnings Report Time (Before Market Open or After Market Close):

=PreviousEarningsReportTime("AAPL")

Formula documentation: PreviousEarningsReportTime

Step 6: Include Growth and Valuation Metrics

Round out the screener with growth and valuation data to provide context:

Quarterly Earnings Growth Year-over-Year:

=QuarterlyEarningsGrowthYOY("AAPL")

Formula documentation: QuarterlyEarningsGrowthYOY

Forward P/E Ratio (Current Year):

=Price_EPSEstimateCurrentYear("AAPL")

Formula documentation: Price_EPSEstimateCurrentYear

Forward P/E Ratio (Next Year):

=Price_EPSEstimateNextYear("AAPL")

Formula documentation: Price_EPSEstimateNextYear

Sector Classification:

=Sector("AAPL")

Formula documentation: Sector

These metrics help you evaluate whether an earnings surprise is happening in the context of strong growth and reasonable valuation, or whether it is a one-time anomaly.

The Earnings Quality Scoring System

Simply tracking whether a company beats or misses is useful but incomplete. The template includes a multi-factor Earnings Quality Score that combines several dimensions into a single number. Here is how it works.

Factor 1: Surprise History (0-3 Points)

The EPS Surprise Percentage determines the first component of the score:

  • Greater than 10%: 3 points (strong beat)
  • Greater than 5%: 2 points (solid beat)
  • Greater than 0%: 1 point (slight beat)
  • Zero or negative: 0 points (in-line or miss)

Factor 2: Growth Trajectory (0-2 Points)

Quarterly Earnings Growth YoY adds the growth dimension:

  • Greater than 10%: 2 points (strong growth)
  • Greater than 0%: 1 point (positive growth)
  • Zero or negative: 0 points (declining earnings)

Factor 3: Forward Valuation (0-2 Points)

The Forward P/E ratio provides a valuation check:

  • Less than 25: 2 points (reasonably valued)
  • Less than 35: 1 point (moderately valued)
  • 35 or above: 0 points (premium valuation)

Combined Score Interpretation

The maximum score is 7 points. In the template, scores map to conviction levels:

  • 5-7: High conviction - strong surprise, growing earnings, reasonable valuation
  • 3-4: Medium conviction - mixed signals across the three factors
  • 0-2: Low conviction - weak surprise, declining growth, or expensive valuation

This scoring system is entirely educational and designed as an analytical framework. It is not a recommendation to buy or sell any security. The formula in Excel looks like this:

=IF(EPSSurprisePercent("AAPL")>10,3,IF(EPSSurprisePercent("AAPL")>5,2,IF(EPSSurprisePercent("AAPL")>0,1,0)))+IF(QuarterlyEarningsGrowthYOY("AAPL")>10,2,IF(QuarterlyEarningsGrowthYOY("AAPL")>0,1,0))+IF(Price_EPSEstimateCurrentYear("AAPL")<25,2,IF(Price_EPSEstimateCurrentYear("AAPL")<35,1,0))

Formula documentation: EPSSurprisePercent, QuarterlyEarningsGrowthYOY, Price_EPSEstimateCurrentYear

Pre-Earnings Run-Up Analysis

One of the more advanced features of the screener is the pre-earnings run-up analysis. Research has shown that stocks often exhibit directional moves in the days leading up to their earnings report. MarketXLS provides two specialized functions for this analysis.

Earnings Run-Up Pattern

=EarningsRunUpAnalysis("AAPL")

Formula documentation: EarningsRunUpAnalysis

This function analyzes the historical price behavior of a stock in the days before its earnings announcement. It categorizes the pattern as Bullish, Bearish, or Neutral based on prior quarters. For Q1 2026, several of the mega-cap technology names show Bullish run-up patterns, while some energy stocks show Bearish patterns reflecting uncertainty about oil price sustainability.

Implied Volatility Analysis

Options markets provide valuable information about expected earnings moves. MarketXLS captures this with:

=ExEarningsImpliedVolatility10d("AAPL")

Formula documentation: ExEarningsImpliedVolatility10d

=ExEarningsImpliedVolatility30d("AAPL")

Formula documentation: ExEarningsImpliedVolatility30d

These functions return the implied volatility after removing the earnings event premium. By comparing the 10-day and 30-day ex-earnings implied volatility, you can gauge how much of the current options pricing is due to the upcoming earnings event versus normal market volatility.

For example, if a stock has a 10-day IV of 42% and a 30-day IV of 46%, the difference suggests the earnings event is adding roughly 4 percentage points of implied volatility. Stocks with a larger spread between these two measures tend to have more volatile earnings reactions historically.

The Earnings Opportunities Function

=EarningsOpportunitiesNext7Days("AAPL")

Formula documentation: EarningsOpportunitiesNext7Days

This function identifies stocks with upcoming earnings in the next seven days, helping you stay ahead of the reporting calendar without checking multiple websites.

Sector-by-Sector Q1 Earnings Preview

Technology: The AI Spending Question

Technology earnings in Q1 2026 revolve around one central question: is AI spending producing returns? Microsoft reports Azure cloud growth and AI-related revenue on April 22. Google follows the same day with updates on its Gemini AI products and cloud business. Amazon reports on April 24 with AWS and advertising as the key segments.

The consensus view is that AI spending continues to accelerate, but investors are increasingly focused on monetization proof points rather than just spending announcements. Companies that demonstrate clear AI revenue contributions are likely to receive positive market reactions even if headline EPS only modestly beats estimates.

NVIDIA reports later in May, but its guidance during Q1 results from other tech companies will be closely watched. The company's data center GPU revenue has been the most direct beneficiary of AI infrastructure buildout.

Tesla reports on April 22 with a different set of expectations. Vehicle delivery numbers, margin trends, and updates on the robotaxi program are more relevant than traditional EPS metrics for this stock.

Financials: Rate Sensitivity and Credit Quality

Banks kick off earnings season on April 11 with JPMorgan and Wells Fargo. The key metrics to watch include:

  • Net Interest Income (NII): How the rate environment is impacting lending margins
  • Loan Growth: Whether consumers and businesses are borrowing more or less
  • Credit Quality: Delinquency rates and charge-offs, especially in consumer credit cards and commercial real estate
  • Trading Revenue: Market volatility in Q1 may have boosted trading desks

JPMorgan has consistently beaten EPS estimates with an average surprise of about 8-9% in recent quarters. Bank of America and Wells Fargo have been more modest in their beats, typically in the 5-7% range.

Use the screener to track these metrics as they report. The EPSSurprise and EPSSurprisePercent functions update as soon as results are available.

Energy: Oil Above $100 Creates a Mixed Picture

ExxonMobil and Chevron report on April 25, making them among the last major companies in our screener to announce results. With Brent crude above $109, revenue figures should be strong. However, the previous quarter saw slight EPS misses for both companies, with XOM at -4.5% and CVX at -2.2%.

The question for energy companies is whether higher oil prices fully translate to higher EPS, or whether rising costs, increased capital spending, and government policies offset some of the benefit. The screener helps you track this by comparing the EPS surprise against the growth trajectory and forward valuation.

Healthcare: Pipeline and Patent Updates

Johnson & Johnson, UnitedHealth Group, and Pfizer represent different segments of healthcare. JNJ is a diversified healthcare company with pharmaceutical, medtech, and consumer segments. UNH is the largest health insurer in the United States. Pfizer is working to rebuild its pipeline after the COVID-era revenue declines.

UnitedHealth has been the most consistent earnings beater in this group, with an 8.2% surprise in the previous quarter. Pfizer shows positive surprise at 7.7% but declining year-over-year growth at -8.5%, reflecting the base effect of COVID vaccine and treatment revenue.

The Complete Template: Six Sheets Explained

The downloadable Excel templates include six interconnected sheets designed to give you a complete earnings analysis framework.

Sheet 1: How To Use

This introductory sheet explains the purpose of each tab, provides links to MarketXLS and the demo booking page, and describes how to customize the input cells (highlighted in yellow).

Sheet 2: Earnings Dashboard

The main screening table with all 15 stocks. Columns include Price, EPS TTM, EPS Estimate Current Quarter, EPS Surprise, EPS Surprise Percentage, Earnings Date, Quarterly Growth YoY, Forward P/E, Sector, and the calculated Earnings Quality Score. Conditional formatting highlights positive surprises in green and negative surprises in red. The yellow input cells at the top let you set a minimum surprise percentage threshold for filtering.

Key formulas on this sheet:

=QM_Last("AAPL")
=EarningsPerShare("AAPL")
=EPSEstimateCurrentQ("AAPL")
=EPSSurprise("AAPL")
=EPSSurprisePercent("AAPL")
=earnings_date("AAPL")
=QuarterlyEarningsGrowthYOY("AAPL")
=Price_EPSEstimateCurrentYear("AAPL")
=Sector("AAPL")

Formula documentation: QM_Last, EarningsPerShare, EPSEstimateCurrentQ, EPSSurprise, EPSSurprisePercent, earnings_date, QuarterlyEarningsGrowthYOY, Price_EPSEstimateCurrentYear, Sector

Sheet 3: Scenario Analysis

A what-if table that models different earnings outcomes. You select a ticker in the yellow input cell, and the sheet calculates implied price moves for six scenarios: a 10% miss, a 5% miss, in-line results, a 5% beat, a 10% beat, and a 20% beat. Historical average move percentages provide context for each scenario.

Sheet 4: Earnings Strategies

This sheet focuses on pre-earnings analysis using advanced MarketXLS functions:

=EarningsRunUpAnalysis("AAPL")
=ExEarningsImpliedVolatility10d("AAPL")
=ExEarningsImpliedVolatility30d("AAPL")
=PreviousEarningsReportDate("AAPL")
=PreviousEarningsReportTime("AAPL")

Formula documentation: EarningsRunUpAnalysis, ExEarningsImpliedVolatility10d, ExEarningsImpliedVolatility30d, PreviousEarningsReportDate, PreviousEarningsReportTime

A risk level column classifies each stock based on implied volatility. Stocks with IV above 40% are classified as High risk, between 25-40% as Medium, and below 25% as Low.

Sheet 5: Portfolio Positioning

An educational portfolio framework with a yellow input cell for your total portfolio value. The sheet calculates position sizes based on the Earnings Quality Score. High conviction stocks (score 5-7) receive a 10% allocation, medium conviction (3-4) gets 6%, and low conviction (0-2) gets 3%. It also shows dividend yields using:

=DividendYield("AAPL")

Formula documentation: DividendYield

This helps balance growth and income considerations heading into earnings season.

Sheet 6: Sector Comparison

A color-coded matrix comparing earnings metrics across Technology, Financials, Healthcare, and Energy sectors. Each sector row uses a distinct background color for easy visual scanning. Metrics include EPS Surprise %, Quarterly Growth YoY, Forward P/E, Operating Margin, ROE, Revenue, and Earnings Date.

Key formulas include:

=OperatingMargin("AAPL")
=ReturnOnEquity("AAPL")
=Revenue("AAPL")

Formula documentation: OperatingMargin, ReturnOnEquity, Revenue

Additional MarketXLS Functions for Advanced Analysis

Beyond the core screener functions, MarketXLS offers several additional formulas that enhance your earnings analysis:

Analyst Target Prices:

=TargetPrice("AAPL")
=TargetPriceHigh("AAPL")
=TargetPriceLow("AAPL")
=TargetPriceMean("AAPL")

Formula documentation: TargetPrice, TargetPriceHigh, TargetPriceLow, TargetPriceMean

These functions show you where analysts expect the stock price to go, providing a useful reference point when evaluating whether an earnings surprise has already been priced in.

Market Context:

=MarketCapitalization("AAPL")
=Beta("AAPL")
=FiftyTwoWeekHigh("AAPL")
=FiftyTwoWeekLow("AAPL")
=PERatio("AAPL")
=Industry("AAPL")

Formula documentation: MarketCapitalization, Beta, FiftyTwoWeekHigh, FiftyTwoWeekLow, PERatio, Industry

These help you understand the broader context for each stock. A high-beta stock will likely move more on an earnings surprise than a low-beta stock, all else equal.

EPS On Demand:

=QM_EPS("AAPL")

Formula documentation: QM_EPS

This provides a quick on-demand EPS lookup when you need a single data point without building a full formula chain.

Download the Templates

Download the templates:

  • - Pre-filled with current data as of April 4, 2026
  • - Live-updating formulas

The static version is useful for seeing the structure and sample data without needing MarketXLS installed. The formula version connects to live data and updates automatically when you have MarketXLS running in Excel.

Frequently Asked Questions

What is an earnings surprise in stocks?

An earnings surprise occurs when a company reports actual earnings per share (EPS) that differ from the consensus analyst estimate. A positive surprise (or "beat") means actual EPS exceeded expectations, while a negative surprise (or "miss") means actual EPS fell short. Earnings surprises often trigger significant stock price movements because they signal that the company is performing better or worse than the market anticipated. The EPSSurprise and EPSSurprisePercent functions in MarketXLS let you track these differences directly in Excel.

How do you screen for earnings surprises in Excel?

You can build an earnings surprise screener in Excel by combining several MarketXLS functions. Start with EPSSurprisePercent("TICKER") to get the surprise percentage for each stock, then add earnings_date("TICKER") for timing, EPSEstimateCurrentQ("TICKER") for the current consensus, and QuarterlyEarningsGrowthYOY("TICKER") for growth context. Use Excel conditional formatting to highlight positive surprises in green and negative surprises in red. The templates provided in this article include all of these formulas pre-built.

When does Q1 2026 earnings season start?

Q1 2026 earnings season begins in mid-April 2026. Major banks typically report first, with JPMorgan Chase and Wells Fargo expected to announce results on April 11, 2026. Bank of America, UnitedHealth Group, and Johnson & Johnson follow on April 15. The large technology companies report later in April, with Microsoft, Google, and Tesla on April 22, Meta on April 23, and Apple and Amazon on April 24. Use the earnings_date function in MarketXLS to track the latest confirmed dates for any stock.

What is a good EPS surprise percentage?

There is no universal threshold for a "good" earnings surprise, but historical data provides useful benchmarks. For large-cap stocks, a surprise of 5% or more is generally considered solid. Surprises above 10% are noteworthy and often trigger meaningful stock price reactions. Surprises above 20% are exceptional and relatively rare for established companies. However, context matters significantly. A 5% beat accompanied by strong revenue growth and raised forward guidance carries more weight than a 5% beat driven by cost-cutting with declining revenue. The Earnings Quality Score in our template accounts for this by combining surprise percentage with growth trajectory and valuation.

How does MarketXLS track earnings estimates?

MarketXLS aggregates earnings estimate data from multiple sources and delivers it through simple Excel functions. The EPSEstimateCurrentQ function returns the consensus estimate for the current quarter, while EPSEstimateCurrentY provides the full-year estimate. After a company reports, the EPSSurprise and EPSSurprisePercent functions update to reflect the actual versus estimated comparison. The data refreshes automatically in your spreadsheet, so you always have the latest consensus numbers without manual updates. Visit the MarketXLS pricing page for information on available plans.

Can you use earnings surprises for options trading?

Earnings surprises and options trading are closely related topics for educational analysis. Options prices typically increase before earnings announcements due to higher implied volatility, a phenomenon known as the "earnings volatility crush" when IV drops after results. MarketXLS provides ExEarningsImpliedVolatility10d and ExEarningsImpliedVolatility30d functions that help you understand the volatility dynamics around earnings events. The EarningsRunUpAnalysis function shows historical price behavior before earnings. These tools support educational analysis of options strategies around earnings, though all trading decisions should be based on your own research and risk tolerance.

The Bottom Line

An earnings surprise screener in Excel puts quarterly results in one place. Instead of manually checking multiple websites and financial news sources, you can pull live EPS estimates, surprise data, earnings dates, growth metrics, and volatility measures directly into a single spreadsheet using MarketXLS formulas.

Q1 2026 results arrive with elevated oil prices, heavy AI spending in technology, and a shifting rate environment for banks. A screener gives you a consistent framework to analyze results as they come in.

The templates provided in this article include six sheets covering a main dashboard, scenario analysis, earnings strategies, portfolio positioning, and sector comparison. Every data cell uses verified MarketXLS functions that update automatically, so your analysis stays current throughout the entire earnings season.

Visit MarketXLS to get started with live Excel formulas for earnings analysis, or book a demo to see the platform in action.

About the authors
Ankur

About Ankur

CEO & Founder, MarketXLS

Ankur is the CEO and founder of MarketXLS. He works with Anagh and Robin on the MarketXLS blog, creating articles together about market data and spreadsheet workflows.

Written collaboratively by Ankur, Anagh and Robin.

Important Disclaimer

The information provided in this article is for educational and informational purposes only and should not be construed as investment advice, a recommendation, or an offer to buy or sell any securities. MarketXLS is a financial data platform and is not a registered investment advisor, broker-dealer, or financial planner. Always conduct your own research and consult with a qualified financial professional before making any investment decisions. Past performance is not indicative of future results. Trading and investing involve substantial risk of loss.

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