Automatic Data Profitability Analysis
| ADP Stock | USD 244.08 0.23 0.09% |
Net Income | First Reported 1989-03-31 | Previous Quarter 859.4 M | Current Value 878.4 M | Quarterly Volatility 221.4 M |
| 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 Asset vs. Return On Equity Fundamental Analysis
Comparative valuation techniques use various fundamental indicators to help in determining Automatic Data's current stock value. Our valuation model uses many indicators to compare Automatic Data value to that of its competitors to determine the firm's financial worth. Automatic Data Processing is number one stock in return on equity category among related companies. It is rated third in return on asset category among related companies reporting about 0.05 of Return On Asset per Return On Equity. The ratio of Return On Equity to Return On Asset for Automatic Data Processing is roughly 18.30 . At this time, Automatic Data's Return On Equity is relatively stable compared to the past year.Comparative valuation analysis is a catch-all model that can be used if you cannot value Automatic Data by discounting back its dividends or cash flows. This model doesn't attempt to find an intrinsic value for Automatic Data's Stock. Still, instead, it compares the stock's price multiples to a benchmark or nearest competition to determine if the stock is relatively undervalued or overvalued. The reason why the comparable model can be used in almost all circumstances is due to the vast number of multiples that can be utilized, such as the price-to-earnings (P/E), price-to-book (P/B), price-to-sales (P/S), price-to-cash flow (P/CF), and many others. The P/E ratio is the most commonly used of these ratios because it focuses on the Automatic Data's earnings, one of the primary drivers of an investment's value.Automatic Return On Asset vs. Return On Equity
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.
Return on Asset or ROA shows how effective is the management of the company in generating income from utilizing all of the assets at their disposal. It is a useful ratio to evaluate the performance of different departments of a company as well as to understand management performance over time.
Automatic Data |
| = | 0.0532 |
Return on Asset measures overall efficiency of a company in generating profits from its total assets. It is expressed as the percentage of profits earned per dollar of Asset. A low ROA typically means that a company is asset-intensive and therefore will needs more money to continue generating revenue in the future.
Automatic Return On Asset Comparison
Automatic Data is currently under evaluation in return on asset category among related companies.
Automatic Data Profitability Projections
The most important aspect of a successful company is its ability to generate a profit. For investors in Automatic Data, profitability is also one of the essential criteria for including it into their portfolios because, without profit, Automatic Data will eventually generate negative long term returns. The profitability progress is the general direction of Automatic Data's change in net profit over the period of time. It can combine multiple indicators of Automatic Data, where stable trends show no significant progress. An accelerating trend is seen as positive, while a decreasing one is unfavorable. A rising trend means that profits are rising, and operational efficiency may be rising as well. A decreasing trend is a sign of poor performance and may indicate upcoming losses.
| Last Reported | Projected for Next Year | ||
| Accumulated Other Comprehensive Income | -2.1 B | -2 B | |
| Operating Income | 5.1 B | 5.4 B | |
| Income Before Tax | 5.1 B | 5.4 B | |
| Total Other Income Expense Net | 39.1 M | 29.1 M | |
| Net Income | 3.9 B | 4.1 B | |
| Income Tax Expense | 1.2 B | 1.2 B | |
| Net Income Applicable To Common Shares | 3.9 B | 4.1 B | |
| Net Income From Continuing Ops | 3.9 B | 2.1 B | |
| Non Operating Income Net Other | 165.2 M | 173.4 M | |
| Net Interest Income | 816 M | 856.8 M | |
| Interest Income | 1.1 B | 1.2 B | |
| Change To Netincome | 335.6 M | 211.1 M | |
| Net Income Per Share | 7.42 | 7.79 | |
| Income Quality | 1.42 | 1.47 | |
| Net Income Per E B T | 0.69 | 0.56 |
Automatic Profitability Driver Comparison
Profitability drivers are factors that can directly affect your investment outlook on Automatic Data. Investors often realize that things won't turn out the way they predict. There are maybe way too many unforeseen events and contingencies during the holding period of Automatic Data position where the market behavior may be hard to predict, tax policy changes, gold or oil price hikes, calamities change, and many others. The question is, are you prepared for these unexpected events? Although some of these situations are obviously beyond your control, you can still follow the important profit indicators to know where you should focus on when things like this occur. Below are some of the Automatic Data's important profitability drivers and their relationship over time.
Automatic Data Profitability Trends
Automatic Data profitability trend refers to the progression of profit or loss within a business. An upward trend means that Automatic Data's profit has generally increased over time, and a downward profitability trend means profits are declining. Recognizing problems early in profitability trends allows investors to address revenue and cost issues in advance. Investors and analysts usually monitor three types of profitability trends: gross, operating, and net. Gross profit is the difference between revenue and costs of goods sold. Operating profit is Automatic Data's gross profit minus its overhead. After you account for other unusual revenue, expenses, and costs, you get net profit. Gross profit trends are often a good indicator of future profitability. If you have high gross profit margins, you have a better chance to cover overhead and make money.
Automatic Data Profitability Drivers Correlations
One of the toughest challenges investors face today is learning how to quickly synthesize and read into endless financial statements and information provided by the company, SEC reporting, and various external parties. Understanding the correlation between Automatic Data different financial indicators related to revenue and profit generation helps investors identify and prioritize their investing strategies towards Automatic Data in a much-optimized way. Analyzing correlations between profit drivers that are directly associated with dollar figures is the most effective way to break down Automatic Data's future profitability.
Click cells to compare fundamentals
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 Industrials ETFs Thematic Idea Now
Industrials ETFs
ETF themes focus on helping investors to gain exposure to a broad range of assets, diversify, and lower overall costs. The Industrials ETFs theme has 38 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 Industrials ETFs 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 Stocks Directory module to find actively traded stocks across global markets.
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.