Automatic Data Book Value Per Share vs. Operating Margin
| 0HJI Stock | 296.94 2.82 0.94% |
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 Processing Operating Margin vs. Book Value Per Share 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 book value per share category among its peers. It also is number one stock in operating margin category among its peers reporting about 0.02 of Operating Margin per Book Value Per Share. The ratio of Book Value Per Share to Operating Margin for Automatic Data Processing is roughly 49.52 . 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 Operating Margin vs. Book Value Per Share
Book Value per Share (B/S) can be calculated by subtracting liabilities from assets, and then dividing it by the total number of currently outstanding shares. It indicates the level of safety associated with each common share after removing the effects of liabilities. In other words, a shareholder can use this ratio to see how much he or she can sell the stake in the company in the event of a liquidation.
Automatic Data |
| = | 13.12 X |
The naive approach to look at Book Value per Share is to compare it to current stock price. If Book Value per Share is higher than the currently traded stock price, the company can be considered undervalued. However, investors must be aware that conventional calculation of Book Value does not include intangible assets such as goodwill, intellectual property, trademarks or brands and may not be an appropriate measure for many firms.
Operating Margin shows how much operating income a company makes on each dollar of sales. It is one of the profitability indicators which helps analysts to understand whether the firm is successful or not making money from everyday operations.
Automatic Data |
| = | 0.26 % |
A good Operating Margin is required for a company to be able to pay for its fixed costs or payout its debt, which implies that the higher the margin, the better. This ratio is most effective in evaluating the earning potential of a company over time when comparing it against a firm's competitors.
Automatic Operating Margin Comparison
Automatic Data is currently under evaluation in operating 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 | 4.5 B | 3.2 B | |
| Income Before Tax | 4.9 B | 3.2 B | |
| Total Other Income Expense Net | 337.9 M | 354.8 M | |
| Net Income | 3.8 B | 2.5 B | |
| Income Tax Expense | 1.1 B | 829.4 M | |
| Interest Income | 11.7 M | 13.2 M | |
| Net Income Applicable To Common Shares | 3.9 B | 2.7 B | |
| Change To Netincome | 172.9 M | 207.6 M |
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?
Run Large Cap ETFs Thematic Idea Now
Large Cap ETFs
ETF themes focus on helping investors to gain exposure to a broad range of assets, diversify, and lower overall costs. The Large Cap ETFs theme has 686 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 Large Cap ETFs Theme or any other thematic opportunities.
| View All Next | Launch |
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.