Automatic Data Processing Stock Z Score
| ADP Stock | USD 296.58 4.82 1.65% |
Automatic | Z Score |
Automatic Data Processing Company Z Score Analysis
Automatic Data's Z-Score is a simple linear, multi-factor model that measures the financial health and economic stability of a company. The score is used to predict the probability of a firm going into bankruptcy within next 24 months or two fiscal years from the day stated on the accounting statements used to calculate it. The model uses five fundamental business ratios that are weighted according to algorithm of Professor Edward Altman who developed it in the late 1960s at New York University..
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Automatic Z Score 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 Z Score. 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.
Click cells to compare fundamentals
To calculate a Z-Score, one would need to know a company's current working capital, its total assets and liabilities, and the amount of its latest earnings as well as earnings before interest and tax. Z-Scores can be used to compare the odds of bankruptcy of companies in a similar line of business or firms operating in the same industry. Companies with Z-Scores above 3.1 are generally considered to be stable and healthy with a low probability of bankruptcy. Scores that fall between 1.8 and 3.1 lie in a so-called 'grey area,' with scores of less than 1 indicating the highest probability of distress. Z Score is a used widely measure by financial auditors, accountants, money managers, loan processors, wealth advisers, and day traders. In the last 25 years, many financial models that utilize z-scores proved it to be successful as a predictor of corporate bankruptcy.
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In accordance with the company's disclosures, Automatic Data Processing has a Z Score of 0.0. This is 100.0% lower than that of the Software sector and about the same as Information Technology (which currently averages 0.0) industry. The z score for all United States stocks is 100.0% higher than that of the company.
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 Data Institutional Holders
Institutional Holdings refers to the ownership stake in Automatic Data that is held by large financial organizations, pension funds or endowments. Institutions may purchase large blocks of Automatic Data's outstanding shares and can exert considerable influence upon its management. Institutional holders may also work to push the share price higher once they own the stock. Extensive social media coverage, TV shows, articles in high-profile magazines, and presentations at investor conferences help move the stock higher, increasing Automatic Data's value.| Shares | Wellington Management Company Llp | 2024-12-31 | 5.7 M | Fundsmith Llp | 2024-12-31 | 5 M | Amvescap Plc. | 2024-12-31 | 3.9 M | Ameriprise Financial Inc | 2024-12-31 | 3.8 M | Ubs Asset Mgmt Americas Inc | 2024-12-31 | 3.8 M | State Farm Mutual Automobile Ins Co | 2024-12-31 | 3.7 M | Amundi | 2024-12-31 | 3.1 M | Legal & General Group Plc | 2024-12-31 | 2.7 M | Deutsche Bank Ag | 2024-12-31 | 2.6 M | Vanguard Group Inc | 2024-12-31 | 40.7 M | Blackrock Inc | 2024-12-31 | 36.4 M |
Automatic Fundamentals
| Return On Equity | 0.84 | ||||
| Return On Asset | 0.0546 | ||||
| Profit Margin | 0.20 % | ||||
| Operating Margin | 0.26 % | ||||
| Current Valuation | 120.78 B | ||||
| Shares Outstanding | 406.87 M | ||||
| Shares Owned By Insiders | 0.13 % | ||||
| Shares Owned By Institutions | 84.72 % | ||||
| Number Of Shares Shorted | 6.63 M | ||||
| Price To Earning | 35.60 X | ||||
| Price To Book | 23.38 X | ||||
| Price To Sales | 5.96 X | ||||
| Revenue | 19.2 B | ||||
| Gross Profit | 9.6 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 | 12.48 X | ||||
| Cash Flow From Operations | 4.16 B | ||||
| Short Ratio | 3.75 X | ||||
| Earnings Per Share | 9.60 X | ||||
| Price To Earnings To Growth | 3.11 X | ||||
| Target Price | 309.41 | ||||
| Number Of Employees | 64 K | ||||
| Beta | 0.78 | ||||
| Market Capitalization | 118.71 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 | 5.74 |
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 against Automatic Stock
| 0.69 | WK | Workiva | PairCorr |
| 0.67 | DJCO | Daily Journal Corp | PairCorr |
| 0.54 | VERB | VERB TECHNOLOGY PANY | PairCorr |
| 0.43 | VTSI | VirTra Inc | PairCorr |
| 0.43 | EGAN | eGain | 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.