Automatic Data Processing Stock Last Dividend Paid
| ADP Stock | USD 306.93 0.01 0% |
Automatic Data Processing fundamentals help investors to digest information that contributes to Automatic Data's financial success or failures. It also enables traders to predict the movement of Automatic Stock. The fundamental analysis module provides a way to measure Automatic Data's intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Automatic Data stock.
Automatic | Last Dividend Paid |
Automatic Data Processing Company Last Dividend Paid Analysis
Automatic Data's Last Dividend Paid refers to dividend per share(DPS) paid to the shareholder the last time dividends were issued by a company. In its conventional sense, dividends refer to the distribution of some of a company's net earnings or capital gains decided by the board of directors.
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Last Dividend | = | Last Profit Distribution AmountTotal Shares |
Current Automatic Data Last Dividend Paid | 5.6 |
Most of Automatic Data's fundamental indicators, such as Last Dividend Paid, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, Automatic Data Processing is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.
Automatic Last Dividend Paid Driver Correlations
Understanding the fundamental principles of building solid financial models for Automatic Data is extremely important. It helps to project a fair market value of Automatic Stock properly, considering its historical fundamentals such as Last Dividend Paid. Since Automatic Data's main accounts across its financial reports are all linked and dependent on each other, it is essential to analyze all possible correlations between related accounts. However, instead of reviewing all of Automatic Data's historical financial statements, investors can examine the correlated drivers to determine its overall health. This can be effectively done using a conventional correlation matrix of Automatic Data's interrelated accounts and indicators.
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Many stable companies today pay out dividends to their shareholders in the form of the income distribution, but high-growth firms rarely offer dividends because all of their earnings are reinvested back to the business.
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Automatic Additional Paid In Capital
Additional Paid In Capital |
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Based on the recorded statements, Automatic Data Processing has a Last Dividend Paid of 5.6. This is much higher than that of the Software sector and significantly higher than that of the Information Technology industry. The last dividend paid for all United States stocks is notably lower than that of the firm.
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Automatic Data ESG Sustainability
Some studies have found that companies with high sustainability scores are getting higher valuations than competitors with lower social-engagement activities. While most ESG disclosures are voluntary and do not directly affect the long term financial condition, Automatic Data's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Automatic Data's managers, analysts, and investors.Environmental | Governance | Social |
Automatic Fundamentals
| Return On Equity | 0.87 | ||||
| Return On Asset | 0.0654 | ||||
| Profit Margin | 0.20 % | ||||
| Operating Margin | 0.26 % | ||||
| Current Valuation | 127.06 B | ||||
| Shares Outstanding | 407.46 M | ||||
| Shares Owned By Insiders | 0.12 % | ||||
| Shares Owned By Institutions | 84.40 % | ||||
| Number Of Shares Shorted | 5.21 M | ||||
| Price To Earning | 35.60 X | ||||
| Price To Book | 23.38 X | ||||
| Price To Sales | 6.41 X | ||||
| Revenue | 19.2 B | ||||
| Gross Profit | 8.51 B | ||||
| EBITDA | 5.8 B | ||||
| Net Income | 3.75 B | ||||
| Cash And Equivalents | 1.23 B | ||||
| Cash Per Share | 2.97 X | ||||
| Total Debt | 3.71 B | ||||
| Debt To Equity | 1.40 % | ||||
| Current Ratio | 0.97 X | ||||
| Book Value Per Share | 13.12 X | ||||
| Cash Flow From Operations | 4.16 B | ||||
| Short Ratio | 3.13 X | ||||
| Earnings Per Share | 9.36 X | ||||
| Price To Earnings To Growth | 2.69 X | ||||
| Target Price | 298.67 | ||||
| Number Of Employees | 64 K | ||||
| Beta | 0.8 | ||||
| Market Capitalization | 125.06 B | ||||
| Total Asset | 54.36 B | ||||
| Retained Earnings | 23.62 B | ||||
| Working Capital | 462.5 M | ||||
| Current Asset | 3.68 B | ||||
| Current Liabilities | 2 B | ||||
| Annual Yield | 0.02 % | ||||
| Five Year Return | 1.95 % | ||||
| Net Asset | 54.36 B | ||||
| Last Dividend Paid | 5.6 |
About Automatic Data Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Automatic Data Processing's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Automatic Data using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Automatic Data Processing based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
Please read more on our fundamental analysis page.
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
| 0.82 | DJCO | Daily Journal Corp | PairCorr |
| 0.8 | AI | C3 Ai Inc Earnings Call This Week | PairCorr |
| 0.95 | BL | Blackline | PairCorr |
| 0.69 | DT | Dynatrace Holdings LLC | PairCorr |
Moving against Automatic Stock
| 0.61 | VERB | VERB TECHNOLOGY PANY Tech Boost | PairCorr |
| 0.59 | VTEX | VTEX | PairCorr |
| 0.35 | DMAN | Innovativ Media Group | 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.