Is Automatic Data Stock a Good Investment?
Automatic Data Investment Advice | ADP |
- 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 Application Software 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 Hold
Market Performance | Insignificant | Details | |
Volatility | Very steady | Details | |
Hype Condition | Stale | Details | |
Current Valuation | Overvalued | Details | |
Odds Of Distress | Low | Details | |
Economic Sensitivity | Slowly supersedes the market | Details | |
Investor Sentiment | Impartial | Details | |
Analyst Consensus | Not Available | Details | |
Financial Leverage | Not Rated | Details | |
Reporting Quality (M-Score) | Unavailable | Details |
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 85.0% of the company shares are held by institutions such as insurance companies. The company recorded earning per share (EPS) of 9.6. Automatic Data Processing last dividend was issued on the 14th of March 2025. The entity 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 3.71 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 85.0% of Automatic Data shares are held by institutions such as insurance companies |
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 |
Automatic Data's market capitalization trends
The company currently falls under 'Mega-Cap' category with a total capitalization of 127.03 B.Automatic Data's profitablity analysis
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.
Basic technical analysis of Automatic Stock
As of the 26th of February, Automatic Data shows the Mean Deviation of 0.6962, risk adjusted performance of 0.0417, and Downside Deviation of 0.9632. 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.
| AUTOMATIC DATA PROCESSING Corp BondUS053015AF05 | View | |
| AUTOMATIC DATA PROCESSING Corp BondUS053015AE30 | View | |
| AUTOMATIC DATA PROCESSING Corp BondUS053015AG87 | View | |
| MPLX LP 4125 Corp BondUS55336VAK61 | View |
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.
| Risk Adjusted Performance | 0.0417 | |||
| Market Risk Adjusted Performance | 0.0963 | |||
| Mean Deviation | 0.6962 | |||
| Semi Deviation | 0.8687 | |||
| Downside Deviation | 0.9632 | |||
| Coefficient Of Variation | 1835.6 | |||
| Standard Deviation | 0.8774 | |||
| Variance | 0.7699 | |||
| Information Ratio | 0.0374 | |||
| Jensen Alpha | 0.0356 | |||
| Total Risk Alpha | 0.0319 | |||
| Sortino Ratio | 0.0341 | |||
| Treynor Ratio | 0.0863 | |||
| Maximum Drawdown | 3.96 | |||
| Value At Risk | (1.73) | |||
| Potential Upside | 1.21 | |||
| Downside Variance | 0.9277 | |||
| Semi Variance | 0.7547 | |||
| Expected Short fall | (0.71) | |||
| Skewness | (0.67) | |||
| Kurtosis | 0.4063 |
| Risk Adjusted Performance | 0.0417 | |||
| Market Risk Adjusted Performance | 0.0963 | |||
| Mean Deviation | 0.6962 | |||
| Semi Deviation | 0.8687 | |||
| Downside Deviation | 0.9632 | |||
| Coefficient Of Variation | 1835.6 | |||
| Standard Deviation | 0.8774 | |||
| Variance | 0.7699 | |||
| Information Ratio | 0.0374 | |||
| Jensen Alpha | 0.0356 | |||
| Total Risk Alpha | 0.0319 | |||
| Sortino Ratio | 0.0341 | |||
| Treynor Ratio | 0.0863 | |||
| Maximum Drawdown | 3.96 | |||
| Value At Risk | (1.73) | |||
| Potential Upside | 1.21 | |||
| Downside Variance | 0.9277 | |||
| Semi Variance | 0.7547 | |||
| Expected Short fall | (0.71) | |||
| Skewness | (0.67) | |||
| Kurtosis | 0.4063 |
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 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 Corporate Management
| M Heron | Managing Operations | Profile | |
| Jonathan Lehberger | Corporate Officer | Profile | |
| Matthew CFA | Vice Relations | Profile | |
| David Kwon | Chief VP | Profile | |
| Joseph DeSilva | Executive Operations | Profile | |
| Don McGuire | Chief Officer | Profile |
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.