Automatic Data Earnings Estimate
| ADP Stock | USD 291.76 2.75 0.95% |
Automatic Data Revenue Breakdown by Earning Segment
By analyzing Automatic Data's earnings estimates, investors can diagnose different trends across Automatic Data's analyst sentiment over time as well as compare current estimates against different timeframes. At this time, Automatic Data's Gross Profit is relatively stable compared to the past year. As of 03/17/2025, Gross Profit Margin is likely to grow to 0.55, while Pretax Profit Margin is likely to drop 0.16.
Automatic |
Automatic Data Earnings Estimation Breakdown
The calculation of Automatic Data's earning per share is based on the data from the past 12 consecutive months, used for reporting the company's financial figures. The next projected EPS of Automatic Data is estimated to be 3.04 with the future projection ranging from a low of 2.8 to a high of 3.02. Please be aware that this consensus of annual earnings estimates for Automatic Data Processing is based on EPS before non-recurring items and includes expenses related to employee stock options.Last Reported EPS
2.80 Lowest | Expected EPS | 3.02 Highest |
Automatic Data Earnings Projection Consensus
Suppose the current estimates of Automatic Data's value are higher than the current market price of the Automatic Data stock. In this case, investors may conclude that Automatic Data is overpriced and will exhibit bullish sentiment. On the other hand, if the present value is lower than the stock price, analysts may conclude that the market undervalues the equity. These scenarios may suggest that the market is not as efficient as it should be at the estimation time, and Automatic Data's stock will quickly adjusts to the new information provided by the consensus estimate.
| Number of Analysts | Historical Accuracy | Last Reported EPS | Estimated EPS for 31st of March 2025 | Current EPS (TTM) | |
| 18 | 97.41% | 2.35 | 3.04 | 9.6 |
Automatic Data Earnings History
Earnings estimate consensus by Automatic Data Processing analysts from Wall Street is used by the market to judge Automatic Data's stock performance. Investors also use these earnings estimates to evaluate and project the stock performance into the future in order to make their investment decisions. However, we recommend analyzing not only Automatic Data's upcoming profit reports and earnings-per-share forecasts but also comparing them to our different valuation methods.Automatic Data Quarterly Gross Profit |
|
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Automatic Data's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Automatic Data Earnings per Share Projection vs Actual
Actual Earning per Share of Automatic Data refers to what the company shows during its earnings calls or quarterly reports. The Expected EPS is what analysts covering Automatic Data Processing predict the company's earnings will be in the future. The higher the earnings per share of Automatic Data, the better is its profitability. While calculating the Earning per Share, we use the weighted ratio, as the number of shares outstanding can change over time.Automatic Data Estimated Months Earnings per Share
For an investor who is primarily interested in generating an income out of investing in entities such as Automatic Data, the EPS ratio can tell if the company is intending to increase its current dividend. Although EPS is an essential tool for investors, it should not be used in isolation. EPS of Automatic Data should always be considered in relation to other companies to make a more educated investment decision.Automatic Quarterly Analyst Estimates and Surprise Metrics
Earnings surprises can significantly impact Automatic Data's stock price both in the short term and over time. Negative earnings surprises usually result in a price decline. However, it has been seen that positive earnings surprises lead to an immediate rise in a stock's price and a gradual increase over time. This is why we often hear news about some companies beating earning projections. Financial analysts spend a large amount of time predicting earnings per share (EPS) along with other important future indicators. Many analysts use forecasting models, management guidance, and additional fundamental information to derive an EPS estimate.
| Reported | Fiscal Date | Estimated EPS | Reported EPS | Surprise | |||
|---|---|---|---|---|---|---|---|
2025-01-29 | 2024-12-31 | 2.3 | 2.35 | 0.05 | 2 | ||
2024-10-30 | 2024-09-30 | 2.21 | 2.33 | 0.12 | 5 | ||
2024-07-31 | 2024-06-30 | 2.06 | 2.09 | 0.03 | 1 | ||
2024-05-01 | 2024-03-31 | 2.79 | 2.88 | 0.09 | 3 | ||
2024-01-31 | 2023-12-31 | 2.1 | 2.13 | 0.03 | 1 | ||
2023-10-25 | 2023-09-30 | 2.03 | 2.08 | 0.05 | 2 | ||
2023-07-26 | 2023-06-30 | 1.83 | 1.89 | 0.06 | 3 | ||
2023-04-26 | 2023-03-31 | 2.45 | 2.52 | 0.07 | 2 | ||
2023-01-25 | 2022-12-31 | 1.94 | 1.96 | 0.02 | 1 | ||
2022-10-26 | 2022-09-30 | 1.8 | 1.86 | 0.06 | 3 | ||
2022-07-27 | 2022-06-30 | 1.46 | 1.5 | 0.04 | 2 | ||
2022-04-27 | 2022-03-31 | 2.08 | 2.21 | 0.13 | 6 | ||
2022-01-26 | 2021-12-31 | 1.63 | 1.65 | 0.02 | 1 | ||
2021-10-27 | 2021-09-30 | 1.49 | 1.65 | 0.16 | 10 | ||
2021-07-28 | 2021-06-30 | 1.14 | 1.2 | 0.06 | 5 | ||
2021-04-28 | 2021-03-31 | 1.82 | 1.89 | 0.07 | 3 | ||
2021-01-27 | 2020-12-31 | 1.29 | 1.52 | 0.23 | 17 | ||
2020-10-28 | 2020-09-30 | 0.98 | 1.41 | 0.43 | 43 | ||
2020-07-29 | 2020-06-30 | 0.96 | 1.14 | 0.18 | 18 | ||
2020-04-29 | 2020-03-31 | 1.89 | 1.92 | 0.03 | 1 | ||
2020-01-29 | 2019-12-31 | 1.45 | 1.52 | 0.07 | 4 | ||
2019-10-30 | 2019-09-30 | 1.33 | 1.34 | 0.01 | 0 | ||
2019-07-31 | 2019-06-30 | 1.13 | 1.14 | 0.01 | 0 | ||
2019-05-01 | 2019-03-31 | 1.69 | 1.77 | 0.08 | 4 | ||
2019-01-30 | 2018-12-31 | 1.18 | 1.34 | 0.16 | 13 | ||
2018-10-31 | 2018-09-30 | 1.11 | 1.2 | 0.09 | 8 | ||
2018-08-01 | 2018-06-30 | 0.9 | 0.92 | 0.02 | 2 | ||
2018-05-02 | 2018-03-31 | 1.44 | 1.52 | 0.08 | 5 | ||
2018-01-31 | 2017-12-31 | 0.9 | 0.99 | 0.09 | 10 | ||
2017-11-02 | 2017-09-30 | 0.85 | 0.91 | 0.06 | 7 | ||
2017-07-27 | 2017-06-30 | 0.67 | 0.66 | -0.01 | 1 | ||
2017-05-03 | 2017-03-31 | 1.23 | 1.31 | 0.08 | 6 | ||
2017-02-01 | 2016-12-31 | 0.81 | 0.87 | 0.06 | 7 | ||
2016-11-02 | 2016-09-30 | 0.76 | 0.86 | 0.1 | 13 | ||
2016-07-28 | 2016-06-30 | 0.67 | 0.69 | 0.02 | 2 | ||
2016-04-28 | 2016-03-31 | 1.18 | 1.17 | -0.01 | 0 | ||
2016-02-03 | 2015-12-31 | 0.72 | 0.72 | 0.0 | 0 | ||
2015-10-28 | 2015-09-30 | 0.65 | 0.68 | 0.03 | 4 | ||
2015-07-30 | 2015-06-30 | 0.59 | 0.55 | -0.04 | 6 | ||
2015-04-30 | 2015-03-31 | 1.02 | 1.04 | 0.02 | 1 | ||
2015-02-04 | 2014-12-31 | 0.68 | 0.7 | 0.02 | 2 | ||
2014-10-29 | 2014-09-30 | 0.6 | 0.62 | 0.02 | 3 | ||
2014-07-31 | 2014-06-30 | 0.63 | 0.63 | 0.0 | 0 | ||
2014-04-30 | 2014-03-31 | 1.08 | 1.06 | -0.02 | 1 | ||
2014-02-05 | 2013-12-31 | 0.77 | 0.8 | 0.03 | 3 | ||
2013-10-30 | 2013-09-30 | 0.66 | 0.68 | 0.02 | 3 | ||
2013-08-01 | 2013-06-30 | 0.57 | 0.55 | -0.02 | 3 | ||
2013-05-03 | 2013-03-31 | 0.98 | 0.99 | 0.01 | 1 | ||
2013-02-05 | 2012-12-31 | 0.71 | 0.72 | 0.01 | 1 | ||
2012-11-01 | 2012-09-30 | 0.62 | 0.62 | 0.0 | 0 | ||
2012-08-01 | 2012-06-30 | 0.53 | 0.53 | 0.0 | 0 | ||
2012-05-01 | 2012-03-31 | 0.91 | 0.92 | 0.01 | 1 | ||
2012-01-25 | 2011-12-31 | 0.68 | 0.68 | 0.0 | 0 | ||
2011-10-26 | 2011-09-30 | 0.61 | 0.61 | 0.0 | 0 | ||
2011-07-28 | 2011-06-30 | 0.49 | 0.48 | -0.01 | 2 | ||
2011-05-02 | 2011-03-31 | 0.85 | 0.85 | 0.0 | 0 | ||
2011-01-26 | 2010-12-31 | 0.61 | 0.62 | 0.01 | 1 | ||
2010-10-27 | 2010-09-30 | 0.53 | 0.56 | 0.03 | 5 | ||
2010-07-29 | 2010-06-30 | 0.42 | 0.42 | 0.0 | 0 | ||
2010-04-27 | 2010-03-31 | 0.78 | 0.79 | 0.01 | 1 | ||
2010-02-02 | 2009-12-31 | 0.57 | 0.6 | 0.03 | 5 | ||
2009-11-04 | 2009-09-30 | 0.5 | 0.56 | 0.06 | 12 | ||
2009-07-30 | 2009-06-30 | 0.45 | 0.45 | 0.0 | 0 | ||
2009-05-05 | 2009-03-31 | 0.8 | 0.8 | 0.0 | 0 | ||
2009-02-03 | 2008-12-31 | 0.56 | 0.59 | 0.03 | 5 | ||
2008-11-03 | 2008-09-30 | 0.5 | 0.54 | 0.04 | 8 | ||
2008-07-31 | 2008-06-30 | 0.41 | 0.42 | 0.01 | 2 | ||
2008-05-01 | 2008-03-31 | 0.75 | 0.77 | 0.02 | 2 | ||
2008-02-01 | 2007-12-31 | 0.53 | 0.55 | 0.02 | 3 | ||
2007-10-30 | 2007-09-30 | 0.43 | 0.45 | 0.02 | 4 | ||
2007-07-31 | 2007-06-30 | 0.36 | 0.35 | -0.01 | 2 | ||
2007-05-01 | 2007-03-31 | 0.63 | 0.65 | 0.02 | 3 | ||
2007-02-06 | 2006-12-31 | 0.51 | 0.51 | 0.0 | 0 | ||
2006-10-31 | 2006-09-30 | 0.43 | 0.43 | 0.0 | 0 | ||
2006-08-02 | 2006-06-30 | 0.46 | 0.44 | -0.02 | 4 | ||
2006-04-28 | 2006-03-31 | 0.62 | 0.61 | -0.01 | 1 | ||
2006-01-25 | 2005-12-31 | 0.45 | 0.44 | -0.01 | 2 | ||
2005-10-26 | 2005-09-30 | 0.35 | 0.35 | 0.0 | 0 | ||
2005-07-26 | 2005-06-30 | 0.44 | 0.44 | 0.0 | 0 | ||
2005-04-21 | 2005-03-31 | 0.57 | 0.57 | 0.0 | 0 | ||
2005-01-21 | 2004-12-31 | 0.42 | 0.42 | 0.0 | 0 | ||
2004-10-25 | 2004-09-30 | 0.33 | 0.35 | 0.02 | 6 | ||
2004-07-27 | 2004-06-30 | 0.35 | 0.36 | 0.01 | 2 | ||
2004-04-22 | 2004-03-31 | 0.5 | 0.5 | 0.0 | 0 | ||
2004-01-22 | 2003-12-31 | 0.37 | 0.38 | 0.01 | 2 | ||
2003-10-17 | 2003-09-30 | 0.29 | 0.32 | 0.03 | 10 | ||
2003-07-29 | 2003-06-30 | 0.38 | 0.36 | -0.02 | 5 | ||
2003-04-17 | 2003-03-31 | 0.52 | 0.54 | 0.02 | 3 | ||
2003-01-15 | 2002-12-31 | 0.43 | 0.43 | 0.0 | 0 | ||
2002-10-17 | 2002-09-30 | 0.34 | 0.34 | 0.0 | 0 | ||
2002-07-17 | 2002-06-30 | 0.47 | 0.46 | -0.01 | 2 | ||
2002-04-15 | 2002-03-31 | 0.55 | 0.56 | 0.01 | 1 | ||
2002-01-17 | 2001-12-31 | 0.41 | 0.42 | 0.01 | 2 | ||
2001-10-17 | 2001-09-30 | 0.32 | 0.31 | -0.01 | 3 | ||
2001-08-13 | 2001-06-30 | 0.41 | 0.4 | -0.01 | 2 | ||
2001-04-16 | 2001-03-31 | 0.48 | 0.49 | 0.01 | 2 | ||
2001-01-17 | 2000-12-31 | 0.36 | 0.36 | 0.0 | 0 | ||
2000-10-13 | 2000-09-30 | 0.27 | 0.27 | 0.0 | 0 | ||
2000-08-14 | 2000-06-30 | 0.35 | 0.35 | 0.0 | 0 | ||
2000-04-18 | 2000-03-31 | 0.41 | 0.42 | 0.01 | 2 | ||
2000-01-18 | 1999-12-31 | 0.32 | 0.31 | -0.01 | 3 | ||
1999-10-14 | 1999-09-30 | 0.23 | 0.23 | 0.0 | 0 | ||
1999-08-10 | 1999-06-30 | 0.33 | 0.3 | -0.03 | 9 | ||
1999-04-15 | 1999-03-31 | 0.35 | 0.37 | 0.02 | 5 | ||
1999-01-14 | 1998-12-31 | 0.28 | 0.27 | -0.01 | 3 | ||
1998-10-13 | 1998-09-30 | 0.2 | 0.2 | 0.0 | 0 | ||
1998-08-13 | 1998-06-30 | 0.27 | 0.27 | 0.0 | 0 | ||
1998-04-15 | 1998-03-31 | 0.32 | 0.31 | -0.01 | 3 | ||
1998-01-16 | 1997-12-31 | 0.25 | 0.25 | 0.0 | 0 | ||
1997-10-14 | 1997-09-30 | 0.19 | 0.18 | -0.01 | 5 | ||
1997-08-20 | 1997-06-30 | 0.24 | 0.24 | 0.0 | 0 | ||
1997-04-14 | 1997-03-31 | 0.29 | 0.28 | -0.01 | 3 | ||
1997-01-16 | 1996-12-31 | 0.22 | 0.22 | 0.0 | 0 | ||
1996-10-11 | 1996-09-30 | 0.17 | 0.16 | -0.01 | 5 | ||
1996-08-14 | 1996-06-30 | 0.21 | 0.21 | 0.0 | 0 | ||
1996-04-11 | 1996-03-31 | 0.25 | 0.25 | 0.0 | 0 |
About Automatic Data Earnings Estimate
The earnings estimate module is a useful tool to check what professional financial analysts are assuming about the future of Automatic Data earnings. We show available consensus EPS estimates for the upcoming years and quarters. Investors can also examine how these consensus opinions have evolved historically. We show current Automatic Data estimates, future projections, as well as estimates 1, 2, and three years ago. Investors can search for a specific entity to conduct investment planning and build diversified portfolios. Please note, earnings estimates provided by Macroaxis are the average expectations of expert analysts that we track. If a given stock such as Automatic Data fails to match professional earnings estimates, it usually performs purely. Wall Street refers to that as a 'negative surprise.' If a company 'beats' future estimates, it's usually called an 'upside surprise.'
Please read more on our stock advisor page.| Last Reported | Projected for Next Year | ||
| Retained Earnings | 27.2 B | 28.5 B | |
| Retained Earnings Total Equity | 25.4 B | 17.1 B | |
| Earnings Yield | 0.04 | 0.06 | |
| Price Earnings Ratio | 23.21 | 17.32 | |
| Price Earnings To Growth Ratio | 2.15 | 2.26 |
Pair Trading with Automatic Data
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Automatic Data position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Automatic Data will appreciate offsetting losses from the drop in the long position's value.Moving together with Automatic Stock
Moving against Automatic Stock
| 0.69 | WK | Workiva | PairCorr |
| 0.67 | DJCO | Daily Journal Corp | PairCorr |
| 0.54 | VERB | VERB TECHNOLOGY PANY | PairCorr |
| 0.43 | EGAN | eGain | PairCorr |
| 0.41 | BL | Blackline | PairCorr |
The ability to find closely correlated positions to Automatic Data could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Automatic Data when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Automatic Data - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Automatic Data Processing to buy it.
The correlation of Automatic Data is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Automatic Data moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Automatic Data Processing moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Automatic Data can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Additional Tools for Automatic Stock Analysis
When running Automatic Data's price analysis, check to measure Automatic Data's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Automatic Data is operating at the current time. Most of Automatic Data's value examination focuses on studying past and present price action to predict the probability of Automatic Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Automatic Data's price. Additionally, you may evaluate how the addition of Automatic Data to your portfolios can decrease your overall portfolio volatility.