Automatic Data Earnings Estimate
| ADP Stock | USD 243.07 3.27 1.33% |
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 2.78 with the future projection ranging from a low of 2.68 to a high of 2.92. 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
2.68 Lowest | Expected EPS | 2.92 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 2024 | Current EPS (TTM) | |
| 18 | 97.62% | 2.13 | 2.78 | 8.6 |
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 |
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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 | |||
|---|---|---|---|---|---|---|---|
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 | 25.4 B | 26.7 B | |
| Retained Earnings Total Equity | 25.4 B | 17.1 B | |
| Earnings Yield | 0.04 | 0.06 | |
| Price Earnings Ratio | 23.98 | 17.23 | |
| Price Earnings To Growth Ratio | 1.78 | 1.24 |
Automatic Data Investors Sentiment
The influence of Automatic Data's investor sentiment on the probability of its price appreciation or decline could be a good factor in your decision-making process regarding taking a position in Automatic. The overall investor sentiment generally increases the direction of a stock movement in a one-year investment horizon. However, the impact of investor sentiment on the entire stock market does not have solid backing from leading economists and market statisticians.
Investor biases related to Automatic Data's public news can be used to forecast risks associated with an investment in Automatic. The trend in average sentiment can be used to explain how an investor holding Automatic can time the market purely based on public headlines and social activities around Automatic Data Processing. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Automatic Data's market sentiment shows the aggregated news analyzed to detect positive and negative mentions from the text and comments. The data is normalized to provide daily scores for Automatic Data's and other traded tickers. The bigger the bubble, the more accurate is the estimated score. Higher bars for a given day show more participation in the average Automatic Data's news discussions. The higher the estimated score, the more favorable is the investor's outlook on Automatic Data.
Automatic Data Implied Volatility | 42.41 |
Automatic Data's implied volatility exposes the market's sentiment of Automatic Data Processing stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Automatic Data's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Automatic Data stock will not fluctuate a lot when Automatic Data's options are near their expiration.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Automatic Data in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Automatic Data's short interest history, or implied volatility extrapolated from Automatic Data options trading.
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 against Automatic Stock
| 0.45 | FC | Franklin Covey Financial Report 26th of June 2024 | 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.Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in Automatic Data Processing. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as signals in unemployment. Note that the Automatic Data Processing information on this page should be used as a complementary analysis to other Automatic Data's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Odds Of Bankruptcy module to get analysis of equity chance of financial distress in the next 2 years.
Complementary 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.
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Is Automatic Data's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Automatic Data. If investors know Automatic will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Automatic Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 0.092 | Dividend Share 5.15 | Earnings Share 8.6 | Revenue Per Share 45.09 | Quarterly Revenue Growth 0.063 |
The market value of Automatic Data Processing is measured differently than its book value, which is the value of Automatic that is recorded on the company's balance sheet. Investors also form their own opinion of Automatic Data's value that differs from its market value or its book value, called intrinsic value, which is Automatic Data's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Automatic Data's market value can be influenced by many factors that don't directly affect Automatic Data's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Automatic Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Automatic Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Automatic Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.