Automatic Data Processing Stock Analysis

ADP Stock  USD 242.64  4.62  1.94%   
Automatic Data Processing is fairly valued with Real Value of 251.37 and Target Price of 259.93. The main objective of Automatic Data stock analysis is to determine its intrinsic value, which is an estimate of what Automatic Data Processing is worth, separate from its market price. There are two main types of Automatic Data's stock analysis: fundamental analysis and technical analysis.
The Automatic Data stock is traded in the USA on NASDAQ Exchange, with the market opening at 09:30:00 and closing at 16:00:00 every Mon,Tue,Wed,Thu,Fri except for officially observed holidays in the USA. Automatic Data is usually not traded on Dr . Martin Luther King Jr 's Birthday, Washington 's Birthday, Good Friday, Memorial Day, Juneteenth Holiday, Independence Day, Labour Day, Thanksgiving Day, Christmas Day, New Year 's Day. Automatic Stock trading window is adjusted to America/New York timezone.
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 closely tied with the direction of predictive economic indicators such as signals in unemployment.

Automatic Stock Analysis Notes

About 84.0% of the company shares are held by institutions such as insurance companies. The company has Price/Earnings To Growth (PEG) ratio of 2.66. Automatic Data Processing recorded earning per share (EPS) of 8.95. The entity last dividend was issued on the 14th of June 2024. The firm had 1139:1000 split on the 1st of October 2014. Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. The company was founded in 1949 and is headquartered in Roseland, New Jersey. Automatic Data operates under Staffing Employment Services classification in the United States and is traded on NASDAQ Exchange. It employs 60000 people. For more info on Automatic Data Processing please contact Carlos Rodriguez at 973 974 5000 or go to

Automatic Data Quarterly Total Revenue

5.25 Billion

Automatic Data Processing Investment Alerts

Automatic Data Processing has 3.34 B in debt with debt to equity (D/E) ratio of 1.4, which is OK given its current industry classification. Automatic Data Processing has a current ratio of 0.95, suggesting that it has not enough short term capital to pay financial commitments when the payables are due. Note however, debt could still be an excellent tool for Automatic to invest in growth at high rates of return.
Automatic Data has a strong financial position based on the latest SEC filings
Over 84.0% of Automatic Data shares are held by institutions such as insurance companies
On 1st of July 2024 Automatic Data paid $ 1.4 per share dividend to its current shareholders
Latest headline from TriNet Moves 4.2 percent Higher Will This Strength Last

Automatic Data Processing Upcoming and Recent Events

31st of January 2024
Upcoming Quarterly Report
24th of April 2024
Next Financial Report
31st of December 2023
Next Fiscal Quarter End
24th of July 2024
Next Fiscal Year End
30th of September 2023
Last Quarter Report
30th of June 2023
Last Financial Announcement

Automatic Largest EPS Surprises

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.
Fiscal Date
Estimated EPS
Reported EPS
View All Earnings Estimates

Automatic Data Environmental, Social, and Governance (ESG) Scores

Automatic Data's ESG score is a quantitative measure that evaluates Automatic Data's performance and commitment regarding environmental, social, and governance (ESG) factors. These scores are becoming increasingly crucial in investment decision-making processes, providing insights into non-financial aspects of Automatic Data's operations that may have significant financial implications and affect Automatic Data's stock price as well as guide investors towards more socially responsible investments.

Automatic Stock Institutional Investors

Institutional investors include commercial and private banks, credit unions, insurance companies, pension funds, hedge funds, endowments, and mutual funds. Operating companies that invest excess capital in these types of assets may also be included in the term and may influence corporate governance by exercising voting rights in their investments.
Bank Of America Corp2024-03-31
4.8 M
State Farm Mutual Automobile Ins Co2024-03-31
3.7 M
Amvescap Plc.2024-03-31
3.7 M
Ameriprise Financial Inc2024-03-31
3.6 M
Capital Research Global Investors2024-03-31
3.6 M
Legal & General Group Plc2024-03-31
3.4 M
Fmr Inc2024-03-31
3.2 M
2.9 M
Nordea Investment Mgmt Bank Demark A/s2024-03-31
2.7 M
Vanguard Group Inc2024-03-31
39.8 M
Blackrock Inc2024-03-31
33.8 M
Note, although Automatic Data's institutional investors appear to be way more sophisticated than retail investors, it remains unclear if professional active investment managers can reliably enhance risk-adjusted returns by an amount that exceeds fees and expenses.

Automatic Market Capitalization

The company currently falls under 'Large-Cap' category with a total capitalization of 97.42 B.

Automatic Profitablity

The company has Net Profit Margin of 0.2 %, which implies that it may need a different competitive strategy as even a very small decline in it revenue may erase profits and result in a net loss. This is way below average. In the same way, it shows Net Operating Margin of 0.3 %, which entails that for every 100 dollars of revenue, it generated $0.3 of operating income.
Last ReportedProjected for Next Year
Return On Tangible Assets 0.08  0.10 
Return On Capital Employed 0.49  0.52 
Return On Assets 0.08  0.08 
Return On Equity 0.88  0.92 

Management Efficiency

Automatic Data Processing has Return on Asset of 0.0496 % which means that on every $100 spent on assets, it made $0.0496 of profit. This is way below average. In the same way, it shows a return on shareholders' equity (ROE) of 0.8892 %, implying that it generated $0.8892 on every 100 dollars invested. Automatic Data's management efficiency ratios could be used to measure how well Automatic Data manages its routine affairs as well as how well it operates its assets and liabilities. As of 07/16/2024, Return On Tangible Assets is likely to grow to 0.1. Also, Return On Capital Employed is likely to grow to 0.52. At this time, Automatic Data's Total Current Liabilities is relatively stable compared to the past year. As of 07/16/2024, Liabilities And Stockholders Equity is likely to grow to about 61.5 B, while Non Current Liabilities Total is likely to drop slightly above 4.8 B.
Last ReportedProjected for Next Year
Book Value Per Share 7.63  6.06 
Tangible Book Value Per Share(0.38)(0.36)
Enterprise Value Over EBITDA 15.78  9.76 
Price Book Value Ratio 23.32  24.49 
Enterprise Value Multiple 15.78  9.76 
Price Fair Value 23.32  24.49 
Enterprise Value58.1 B61 B
The analysis of Automatic Data's management efficiency is an essential part of evaluating and assessing the financial and operational performance of the entity. It is also vital to analyze Automatic Data's future growth prospects and the overall market conditions to determine the value and potential of its stock. The analysis involves studying a range of financial metrics such as revenue, earnings, profit margins, cash flow, debt, market share, and external factors such as economic trends, industry outlook, competition, and government regulations. The goal of Automatic Stock analysis is to determine whether it is undervalued, fairly valued, or overvalued and to make informed investment decisions.
Dividend Yield
Operating Margin
Profit Margin
Forward Dividend Yield

Technical Drivers

As of the 16th of July 2024, Automatic Data shows the Risk Adjusted Performance of (0.03), mean deviation of 0.7685, and Standard Deviation of 1.05. Automatic Data Processing technical analysis gives you the methodology to make use of historical prices and volume patterns to determine a pattern that approximates the direction of the firm's future prices.

Automatic Data Processing Price Movement Analysis

Execute Study
The output start index for this execution was nine with a total number of output elements of fifty-two. The Bollinger Bands is very popular indicator that was developed by John Bollinger. It consist of three lines. Automatic Data middle band is a simple moving average of its typical price. The upper and lower bands are (N) standard deviations above and below the middle band. The bands widen and narrow when the volatility of the price is higher or lower, respectively. The upper and lower bands can also be interpreted as price targets for Automatic Data Processing. When the price bounces off of the lower band and crosses the middle band, then the upper band becomes the price target.

Automatic Data Processing Insider Trading Activities

Some recent studies suggest that insider trading raises the cost of capital for securities issuers and decreases overall economic growth. Trading by specific Automatic Data insiders, such as employees or executives, is commonly permitted as long as it does not rely on Automatic Data's material information that is not in the public domain. Local jurisdictions usually require such trading to be reported in order to monitor insider transactions. In many U.S. states, trading conducted by corporate officers, key employees, directors, or significant shareholders must be reported to the regulator or publicly disclosed, usually within a few business days of the trade. In these cases Automatic Data insiders are required to file a Form 4 with the U.S. Securities and Exchange Commission (SEC) when buying or selling shares of their own companies.

Automatic Data Outstanding Bonds

Automatic Data issues bonds to finance its operations. Corporate bonds make up one of the largest components of the U.S. bond market, which is considered the world's largest securities market. Automatic Data Processing uses the proceeds from bond sales for a wide variety of purposes, including financing ongoing mergers and acquisitions, buying new equipment, investing in research and development, buying back their own stock, paying dividends to shareholders, and even refinancing existing debt. Most Automatic bonds can be classified according to their maturity, which is the date when Automatic Data Processing has to pay back the principal to investors. Maturities can be short-term, medium-term, or long-term (more than ten years). Longer-term bonds usually offer higher interest rates but may entail additional risks.

Automatic Data Predictive Daily Indicators

Automatic Data intraday indicators are useful technical analysis tools used by many experienced traders. Just like the conventional technical analysis, daily indicators help intraday investors to analyze the price movement with the timing of Automatic Data stock daily movement. By combining multiple daily indicators into a single trading strategy, you can limit your risk while still earning strong returns on your managed positions.

Automatic Data Corporate Filings

2nd of July 2024
The report filed by a party regarding the acquisition or disposition of a company's common stock, as well as derivative securities such as options, warrants, and convertible securities
1st of July 2024
The report used by insiders such as officers, directors, and major shareholders (beneficial owners holding more than 10% of any class of the company's equity securities) to declare their ownership of a company's stock
28th of June 2024
Report filed with the SEC to announce major events that shareholders should know about
14th of June 2024
The report filed by a party regarding the acquisition or disposition of a company's common stock, as well as derivative securities such as options, warrants, and convertible securities
9th of May 2024
Report filed with the SEC to announce major events that shareholders should know about
2nd of May 2024
Quarterly performance report mandated by Securities and Exchange Commission (SEC), to be filed by publicly traded corporations
1st of May 2024
Report filed with the SEC to announce major events that shareholders should know about
5th of March 2024
The report filed by a party regarding the acquisition or disposition of a company's common stock, as well as derivative securities such as options, warrants, and convertible securities

Automatic Data Forecast Models

Automatic Data's time-series forecasting models are one of many Automatic Data's stock analysis techniques aimed at predicting future share value based on previously observed values. Time-series forecasting models ae widely used for non-stationary data. Non-stationary data are called the data whose statistical properties e.g. the mean and standard deviation are not constant over time but instead, these metrics vary over time. These non-stationary Automatic Data's historical data is usually called time-series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the market movement and maximize returns from investment trading.

About Automatic Stock Analysis

Stock analysis is the technique used by a trader or investor to examine and evaluate how Automatic Data prices is reacting to, or reflecting on a current market direction and economic conditions. It can be used to make informed decisions about market timing, and when buying or selling Automatic shares will generate the highest return on investment. We also built our stock analysis module to help investors to gain an insight into the world economy as a whole, the stock market, thematic ideas. a specific sector, or an individual Stock such as Automatic Data. By using and applying Automatic Stock analysis, traders can create a robust methodology for identifying Automatic entry and exit points for their positions.
Last ReportedProjected for Next Year
Pretax Profit Margin 0.23  0.16 
Operating Profit Margin 0.23  0.15 
Net Profit Margin 0.18  0.11 
Gross Profit Margin 0.48  0.55 

Current Automatic Analysis - Recommendations

We track the performance of the top 100 financial experts across various large and mid-size financial boutiques. Automatic analyst recommendations are determined by taking all analyst recommendations and averaging them as Strong Buy, Buy, Hold, Strong Sell or Sell. There is no one specific way to measure analysis performance other than comparing it to the past results via a very sophisticated attribution analysis. Automatic analyst consensus and target price projections should be used in combination with other traditional techniques such as stock price forecasting, technical analysis, earnings estimate, and various momentum models.
Target PriceAdvice# of Analysts
Automatic Data Processing current and past analyst recommendations published by a number of research institutions as well as average analyst consensus.
Most Automatic analysts issue ratings four times a year, at intervals of three months. Ratings are usually accompanied by a target price to helps potential investors understand Automatic stock's fair price compared to its market value. Analysts arrive at stock ratings after researching public financial statements of Automatic Data Processing, talking to its executives and customers, or listening to Automatic conference calls.
Automatic Analyst Advice Details

Automatic Stock Analysis Indicators

Automatic Data Processing stock analysis indicators help investors evaluate how Automatic Data stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing and determine when trading Automatic Data shares will generate the highest return on investment. By understating and applying Automatic Data stock analysis, traders can identify Automatic Data position entry and exit signals to maximize returns.
Begin Period Cash Flow22.8 B
Long Term DebtB
Common Stock Shares Outstanding415.7 M
Total Stockholder Equity3.5 B
Total Cashflows From Investing Activities-2.5 B
Tax ProvisionB
Quarterly Earnings Growth Y O Y0.147
Property Plant And Equipment Net1.1 B
Cash And Short Term Investments2.1 B
Cash2.1 B
Accounts Payable96.8 M
Net Debt1.3 B
50 Day M A244.0376
Total Current Liabilities42.8 B
Other Operating Expenses13.5 B
Non Current Assets Total8.8 B
Forward Price Earnings23.4742
Common Stock Total Equity63.9 M
Non Currrent Assets OtherB
Stock Based Compensation220.4 M

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.