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Altman Z Score is one of the simplest fundamental models to determine how likely your company is to fail. The module uses available fundamental data of a given equity to approximate the Altman Z score. Altman Z Score is determined by evaluating five fundamental price points available from the company's current public disclosure documents. 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 board of governors.
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..
Current Automatic Data Z Score | | | | 16.8 |
Most of Automatic Data's fundamental indicators, such as Z Score, 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.
| First Factor | = | 1.2 * ( | Working Capital | / | Total Assets ) |
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| Second Factor | = | 1.4 * ( | Retained Earnings | / | Total Assets ) |
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| Thrid Factor | = | 3.3 * ( | EBITAD | / | Total Assets ) |
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| Fouth Factor | = | 0.6 * ( | Market Value of Equity | / | Total Liabilities ) |
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| Fifth Factor | = | 0.99 * ( | Revenue | / | Total Assets ) |
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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.
In accordance with the company's disclosures, Automatic Data Processing has a Z Score of 16.8. This is 312.78% higher than that of the Industrials sector and 141.38% higher than that of the
Business Services industry. The z score for all Germany stocks is 92.66% lower than that of the firm.
Automatic Z Score Peer Comparison
Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Automatic Data's direct or indirect competition against its Z Score to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Automatic Data could also be used in its relative valuation, which is a method of valuing Automatic Data by comparing valuation metrics of similar companies.
Automatic Data is rated
below average in z score category among its peers.
Automatic Fundamentals
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.
Currently Active Assets on Macroaxis
Additional Information and Resources on Investing in Automatic Stock
When determining whether Automatic Data Processing is a good investment, qualitative aspects like company
management, corporate governance, and ethical practices play a significant role. A
comparison with peer companies also provides context and helps to understand if Automatic Stock is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Automatic Data Processing Stock.
Highlighted below are key reports to facilitate an investment decision about Automatic Data Processing Stock: 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 board of governors.
You can also try the
Funds Screener module to find actively-traded funds from around the world traded on over 30 global exchanges.
Please note, there is a significant difference between Automatic Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Automatic Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Automatic Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.