Automatic Data Cash per Share vs. Return On Equity
| ADP Stock | USD 246.84 0.53 0.22% |
Cash Per Share | First Reported 2010-12-31 | Previous Quarter 4.56 | Current Value 2.37 | Quarterly Volatility 2.64789286 |
| Current Value | Last Year | Change From Last Year | 10 Year Trend | ||||||
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| Gross Profit Margin | 0.55 | 0.48 |
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| Net Profit Margin | 0.11 | 0.18 |
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| Operating Profit Margin | 0.15 | 0.23 |
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| Pretax Profit Margin | 0.16 | 0.23 |
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| Return On Assets | 0.0806 | 0.077 |
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| Return On Equity | 0.92 | 0.88 |
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For Automatic Data profitability analysis, we use financial ratios and fundamental drivers that measure the ability of Automatic Data to generate income relative to revenue, assets, operating costs, and current equity. These fundamental indicators attest to how well Automatic Data Processing utilizes its assets to generate profit and value for its shareholders. The profitability module also shows relationships between Automatic Data's most relevant fundamental drivers. It provides multiple suggestions of what could affect the performance of Automatic Data Processing over time as well as its relative position and ranking within its peers.
Automatic |
Is Automatic Data's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Automatic Data. If investors know Automatic will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Automatic Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 0.092 | Dividend Share 5.15 | Earnings Share 8.59 | Revenue Per Share 45.09 | Quarterly Revenue Growth 0.063 |
The market value of Automatic Data Processing is measured differently than its book value, which is the value of Automatic that is recorded on the company's balance sheet. Investors also form their own opinion of Automatic Data's value that differs from its market value or its book value, called intrinsic value, which is Automatic Data's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Automatic Data's market value can be influenced by many factors that don't directly affect Automatic Data's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
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.
Automatic Data Processing Return On Equity vs. Cash per Share Fundamental Analysis
Automatic Return On Equity vs. Cash per Share
Automatic Data | = | null |
Return on Equity or ROE tells company stockholders how effectually their money is being utilized or reinvested. It is a useful ratio when analyzing company profitability or the management effectiveness given the capital invested by the shareholders. ROE shows how efficiently a company utilizes investments to generate income.
Automatic Data |
| = | 0.97 |
For most industries, Return on Equity between 10% and 30% are considered desirable to provide dividends to owners and have funds for the future growth of the company. Investors should be very careful using ROE as the only efficiency indicator because ROE can be high if a company is heavily leveraged.
Automatic Return On Equity Comparison
Automatic Data is currently under evaluation in return on equity category among related companies.
Use Automatic Data in pair-trading
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.Automatic Data Pair Trading
Automatic Data Processing Pair Trading Analysis
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.Use Investing Themes to Complement your Automatic Data position
In addition to having Automatic Data in your portfolios, you can quickly add positions using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your investment opportunity, you can then find an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility.Did You Try This Idea?
Run Israel Wall Street Thematic Idea Now
Israel Wall Street
Cross-sector collection of best publicly traded Israel entities that are expected to continue growing. The Israel Wall Street theme has 71 constituents at this time.
You can either use a buy-and-hold strategy to lock in the entire theme or actively trade it to take advantage of the short-term price volatility of individual constituents. Macroaxis can help you discover thousands of investment opportunities in different asset classes. In addition, you can partner with us for reliable portfolio optimization as you plan to utilize Israel Wall Street Theme or any other thematic opportunities.
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Check out Trending Equities. Note that the Automatic Data Processing information on this page should be used as a complementary analysis to other Automatic Data's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
Complementary 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.
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To fully project Automatic Data's future profitability, investors should examine all historical financial statements. These statements provide investors with a comprehensive snapshot of the financial position of Automatic Data Processing at a specified time, usually calculated after every quarter, six months, or one year. Three primary documents fall into the category of financial statements. These documents include Automatic Data's income statement, its balance sheet, and the statement of cash flows.