Is Automatic Data Stock a Good Investment?

Automatic Data Investment Advice

  ADP
To provide specific investment advice or recommendations on Automatic Data Processing stock, we recommend investors consider the following general factors when evaluating Automatic Data Processing. This will help you to make an informed decision on whether to include Automatic Data in one of your diversified portfolios:
  • Examine Automatic Data's financial health by looking at its balance sheet, income statement, and cash flow statement. Analyze key financial ratios, such as Price-to-Earnings (P/E), Price-to-Sales (P/S), and Price-to-Book (P/B), to determine whether the stock is fairly valued or over/undervalued.
  • Research Automatic Data's leadership team and their track record. Good management can help Automatic Data navigate difficult times and make strategic decisions that benefit shareholders and increases its net worth.
  • Consider the overall health of the Human Resource & Employment Services space and any emerging trends that could impact Automatic Data's business and its evolving consumer preferences.
  • Compare Automatic Data's performance and market position to its competitors. Analyze how Automatic Data is positioned in terms of product offerings, innovation, and market share.
  • Check if Automatic Data pays a dividend and its dividend yield and payout ratio.
  • Review what financial analysts are saying about Automatic Data's stock and their price targets. However, remember that analysts' opinions can vary, and their predictions may not always be accurate.
It's important to note that investing in Automatic Data Processing stock, carries risks, and you should carefully consider your investment goals and risk tolerance before making any investment decisions. Also, remember that it's important for investors to have a long-term perspective and a well-diversified portfolio to manage the impact of stock market volatility on their investments. Below is a detailed guide on how to decide if Automatic Data Processing is a good investment.
 
Sell
 
Buy
Strong Buy
Macroaxis provides advice on Automatic Data Processing to complement and cross-verify current analyst consensus on Automatic Data Processing. Our investment recommendation engine determines the company's potential to grow exclusively from the perspective of an investor's current risk tolerance and investing horizon. To make sure Automatic Data is not overpriced, please confirm all Automatic Data Processing fundamentals, including its price to sales, debt to equity, number of employees, as well as the relationship between the net income and short ratio . Given that Automatic Data Processing has a price to earning of 35.60 X, we suggest you to validate Automatic Data Processing market performance and probability of bankruptcy to ensure the company can sustain itself in the current economic cycle given your prevailing risk tolerance and investing horizon.

Market Performance

GoodDetails

Volatility

Very steadyDetails

Hype Condition

Low keyDetails

Current Valuation

Fairly ValuedDetails

Odds Of Distress

Very LowDetails

Economic Sensitivity

Follows the market closelyDetails

Investor Sentiment

AlarmedDetails

Analyst Consensus

BuyDetails

Financial Strenth (F Score)

HealthyDetails

Financial Leverage

Not RatedDetails

Reporting Quality (M-Score)

Possible ManipulatorDetails

Examine Automatic Data Stock

Researching Automatic Data's stock involves analyzing various aspects of the company and its industry to make an informed investment decision. The key areas to focus on are fundamentals, business model and competitive advantage. It is also important to analyze trends in revenue, net income, and cash flow, as well as key financial ratios, such as price-to-earnings (P/E), price-to-sales (P/S), and debt-to-equity (D/E). 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 2.69. Automatic Data Processing recorded earning per share (EPS) of 9.35. The entity last dividend was issued on the 13th of December 2024. The firm had 1139:1000 split on the 1st of October 2014.
To determine if Automatic Data is a good investment, evaluating the company's potential for future growth is also very important. This may include expanding into new markets, launching new products or services, or improving operational efficiency. Companies with strong growth prospects can be more attractive investments. This aspect of the research should be conducted in the context of the overall market and industry in which the company operates and should include an analysis of growth potential, competitive landscape, and any regulatory or economic factors that could impact the business. Some of the essential points regarding Automatic Data's research are outlined below:
Automatic Data Processing has 3.8 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.
Over 84.0% of Automatic Data shares are held by institutions such as insurance companies
On 1st of October 2024 Automatic Data paid $ 1.4 per share dividend to its current shareholders
Latest headline from finance.yahoo.com: Workday forecasts fourth-quarter subscription revenue below estimates as client spending weakens

Automatic Data Quarterly Liabilities And Stockholders Equity

49.51 Billion

Automatic Data uses earnings reports to provide investors with an update of all three financial statements, including the income statement, the balance sheet, and the cash flow statement. Therefore, it is also crucial when considering investing in Automatic Data Processing. Every quarterly earnings report provides investors with an overview of sales, expenses, and net income for the most recent period. It also may provide a comparison to Automatic Data's previous reporting period. The quarterly earnings reports are usually disseminated to the public via Form 10-Q, which is a legal document filed with the Securities and Exchange Commission every quarter.
31st of January 2024
Upcoming Quarterly Report
View
24th of April 2024
Next Financial Report
View
31st of December 2023
Next Fiscal Quarter End
View
24th of July 2024
Next Fiscal Year End
View
30th of September 2023
Last Quarter Report
View
30th of June 2023
Last Financial Announcement
View
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. Below are the table of largest EPS Surprises Automatic Data's investors have experienced.
Reported
Fiscal Date
Estimated EPS
Reported EPS
Surprise
2003-10-17
2003-09-300.290.320.0310 
2009-11-04
2009-09-300.50.560.0612 
2018-01-31
2017-12-310.90.990.0910 
2016-11-02
2016-09-300.760.860.113 
2021-10-27
2021-09-301.491.650.1610 
2019-01-30
2018-12-311.181.340.1613 
2020-07-29
2020-06-300.961.140.1818 
2021-01-27
2020-12-311.291.520.2317 

Know Automatic Data's Top Institutional Investors

Have you ever been surprised when a price of an equity instrument such as Automatic Data is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Automatic Data Processing backward and forwards among themselves. Automatic Data's institutional investor refers to the entity that pools money to purchase Automatic Data's securities or originate loans. 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.
Shares
Northern Trust Corp2024-09-30
5.3 M
Capital Research Global Investors2024-09-30
4.8 M
Ameriprise Financial Inc2024-06-30
4.1 M
Amvescap Plc.2024-06-30
M
State Farm Mutual Automobile Ins Co2024-09-30
3.7 M
Legal & General Group Plc2024-06-30
3.5 M
Ubs Asset Mgmt Americas Inc2024-09-30
3.2 M
Deutsche Bank Ag2024-06-30
2.9 M
Ninety One Uk Limited2024-09-30
2.6 M
Vanguard Group Inc2024-09-30
40.5 M
Blackrock Inc2024-06-30
34.1 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 Data's market capitalization trends

The company currently falls under 'Mega-Cap' category with a total capitalization of 125.48 B.

Market Cap

60.61 Billion

Automatic Data's profitablity analysis

Last ReportedProjected for Next Year
Return On Tangible Assets 0.07  0.10 
Return On Capital Employed 0.54  0.56 
Return On Assets 0.07  0.08 
Return On Equity 0.83  0.87 
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 0.26 %, which entails that for every 100 dollars of revenue, it generated $0.26 of operating income.
Determining Automatic Data's profitability involves analyzing its financial statements and using various financial metrics to determine if Automatic Data is a good buy. For example, gross profit margin measures Automatic Data's profitability after accounting for the cost of goods sold, while net profit margin measures profitability after accounting for all expenses. Other important metrics include return on assets, return on equity, and free cash flow. By reviewing multiple sources and metrics, you can gain a complete picture of Automatic Data's profitability and make more informed investment decisions.

Evaluate Automatic Data's management efficiency

Automatic Data Processing has Return on Asset of 0.0654 % which means that on every $100 spent on assets, it made $0.0654 of profit. This is way below average. In the same way, it shows a return on shareholders' equity (ROE) of 0.8726 %, implying that it generated $0.8726 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 11/28/2024, Return On Tangible Assets is likely to grow to 0.1. Also, Return On Capital Employed is likely to grow to 0.56. At this time, Automatic Data's Total Current Liabilities is relatively stable compared to the past year. As of 11/28/2024, Liabilities And Stockholders Equity is likely to grow to about 57.1 B, while Non Current Liabilities Other is likely to drop slightly above 926.2 M.
Last ReportedProjected for Next Year
Book Value Per Share 11.08  6.13 
Tangible Book Value Per Share 2.09  2.61 
Enterprise Value Over EBITDA 16.82  9.73 
Price Book Value Ratio 21.28  22.34 
Enterprise Value Multiple 16.82  9.73 
Price Fair Value 21.28  22.34 
Enterprise Value58.1 B61 B
Management at Automatic Data Processing focuses on leveraging technology and optimizing operations. We evaluate the impact of these focuses on the company's financial health and stock performance.
Dividend Yield
0.0202
Forward Dividend Yield
0.0202
Forward Dividend Rate
6.16
Beta
0.795

Basic technical analysis of Automatic Stock

As of the 28th of November, Automatic Data shows the Mean Deviation of 0.6901, risk adjusted performance of 0.1587, and Downside Deviation of 0.7616. 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's 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's Outstanding Corporate 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.

Understand Automatic Data's technical and predictive indicators

Using predictive indicators to make investment decisions involves analyzing Automatic Data's various financial and market-based factors to help forecast future trends and identify investment opportunities. Select the indicators that are most relevant to your investment strategy. Each indicator has its own strengths and weaknesses, so it's essential to combine multiple indicators to get a more comprehensive view of the market and reduce the risk of making poor decisions based on limited data.

Consider Automatic Data's intraday 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

8K
12th of November 2024
Report filed with the SEC to announce major events that shareholders should know about
ViewVerify
F4
7th of November 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
ViewVerify
10Q
1st of November 2024
Quarterly performance report mandated by Securities and Exchange Commission (SEC), to be filed by publicly traded corporations
ViewVerify
19th of September 2024
Other Reports
ViewVerify
Automatic Data time-series forecasting models is one of many Automatic Data's stock analysis techniques aimed to predict 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.

Automatic Stock media impact

Far too much social signal, news, headlines, and media speculation about Automatic Data that are available to investors today. That information is available publicly through Automatic media outlets and privately through word of mouth or via Automatic internal channels. However, regardless of the origin, that massive amount of Automatic data is challenging to quantify into actionable patterns, especially for investors that are not very sophisticated with ever-evolving tools and techniques used in the investment management field.
A primary focus of Automatic Data news analysis is to determine if its current price reflects all relevant headlines and social signals impacting the current market conditions. A news analyst typically looks at the history of Automatic Data relative headlines and hype rather than examining external drivers such as technical or fundamental data. It is believed that price action tends to repeat itself due to investors' collective, patterned thinking related to Automatic Data's headlines and news coverage data. This data is often completely overlooked or insufficiently analyzed for actionable insights to drive Automatic Data alpha.

Automatic Data Sentiment by Major News Outlets

Investor sentiment, mood or attitude towards Automatic Data can have a significant impact on its stock price or the market as a whole. This sentiment can be positive or negative, and various factors, such as economic indicators, news events, or market trends, can influence it. When investor sentiment is positive, investors are more likely to buy stocks, increasing demand and increasing the stock price. Positive investor sentiment can be driven by good news about the company or the broader market, such as solid earnings reports or positive economic data.
Note that negative investor sentiment can cause investors to sell stocks, leading to a decrease in demand and a drop in the stock price. Negative sentiment can be driven by factors such as poor earnings reports, negative news about the company or industry, or broader economic concerns. It's important to note that investor sentiment is just one of many factors that can affect stock prices. Other factors, such as company performance, industry trends, and global economic conditions, can also play a significant role in determining the value of a stock.

Automatic Data Processing Historical Investor Sentiment

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 and other traded tickers. The bigger the bubble, the more accurate the estimated score. Higher bars for a given day show more participation in the average Automatic Data news discussions. The higher the estimate score, the more favorable the investor's outlook on Automatic Data.

Automatic Data Corporate Management

M HeronManaging OperationsProfile
Jonathan LehbergerCorporate OfficerProfile
David KwonChief VPProfile
Don McGuireChief OfficerProfile
Max LiGlobal OfficerProfile

Already Invested in Automatic Data Processing?

The danger of trading Automatic Data Processing is mainly related to its market volatility and Company specific events. As an investor, you must understand the concept of risk-adjusted return before you start trading. The most common way to measure the risk of Automatic Data is by using the Sharpe ratio. The ratio expresses how much excess return you acquire for the extra volatility you endure for holding a more risker asset than Automatic Data. The Sharpe ratio is calculated by using standard deviation and excess return to determine reward per unit of risk. To understand how volatile Automatic Data Processing is, you must compare it to a benchmark. Traditionally, the risk-free rate of return is the rate of return on the shortest-dated U.S. Treasury, such as a 3-year bond.

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.