Automatic Data Price To Book vs. Profit Margin
| ADP Stock | USD 302.23 4.67 1.57% |
| Current Value | Last Year | Change From Last Year | 10 Year Trend | ||||||
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| Gross Profit Margin | 0.55 | 0.4544 |
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| Net Profit Margin | 0.11 | 0.1954 |
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| Operating Profit Margin | 0.15 | 0.2592 |
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| Pretax Profit Margin | 0.16 | 0.2537 |
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| Return On Assets | 0.0804 | 0.069 |
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| Return On Equity | 0.87 | 0.8251 |
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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 |
Automatic Data's Revenue Breakdown by Earning Segment
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Is Application Software space 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 0.125 | Dividend Share 5.6 | Earnings Share 9.37 | Revenue Per Share 47.658 | Quarterly Revenue Growth 0.071 |
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 Profit Margin vs. Price To Book 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 price to book category among its peers. It also is number one stock in profit margin category among its peers fabricating about 0.01 of Profit Margin per Price To Book. The ratio of Price To Book to Profit Margin for Automatic Data Processing is roughly 114.95 . At this time, Automatic Data's Net Profit Margin is relatively stable compared to the past year. Comparative valuation analysis is a catch-all technique that is used if you cannot value Automatic Data by discounting back its dividends or cash flows. It compares the stock's price multiples to nearest competition to determine if the stock is relatively undervalued or overvalued.Automatic Profit Margin vs. Price To Book
Price to Book (P/B) ratio is used to relate a company book value to its current market price. A high P/B ratio indicates that investors expect executives to generate more returns on their investments from a given set of assets. Book value is the accounting value of assets minus liabilities.
Automatic Data |
| = | 22.67 X |
Price to Book ratio is mostly used in financial services industries where assets and liabilities are typically represented by dollars. Although low Price to Book ratio generally implies that the firm is undervalued, it is often a good indicator that the company may be in financial or managerial distress and should be investigated more carefully.
Profit Margin measures overall efficiency of a company and shows its ability to withstand competition as well as defend against adverse conditions such as rising costs, falling prices, decline in sales or management distress. Profit margin tells investors how well the company executes on its overall pricing strategies as well as how effective the company in controlling its costs.
Automatic Data |
| = | 0.20 % |
In a nutshell, Profit Margin indicator shows the amount of money the company makes from total sales or revenue. It can provide a good insight into companies in the same sector, as well as help to identify trends of a company from year to year.
Automatic Profit Margin Comparison
Automatic Data is currently under evaluation in profit margin category among its peers.
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 | -1.8 B | -1.7 B | |
| Operating Income | 5 B | 5.2 B | |
| Income Before Tax | 4.9 B | 5.1 B | |
| Total Other Income Expense Net | -104.9 M | -99.7 M | |
| Net Income | 3.8 B | 3.9 B | |
| Income Tax Expense | 1.1 B | 1.2 B | |
| Net Income Applicable To Common Shares | 3.9 B | 4.1 B | |
| Net Income From Continuing Ops | 3.8 B | 2.2 B | |
| Non Operating Income Net Other | 165.2 M | 173.4 M | |
| Net Interest Income | -120.1 M | -114.1 M | |
| Interest Income | 241.3 M | 253.9 M | |
| Change To Netincome | 335.6 M | 211.1 M | |
| Net Income Per Share | 9.14 | 9.59 | |
| Income Quality | 1.11 | 1.47 | |
| Net Income Per E B T | 0.77 | 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.
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?
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Funds or Etfs investing in commodities such as oil, gold, corn, soy, and agricultural goods. The Commodities Funds theme has 44 constituents at this time.
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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.