Automatic Data Total Debt vs. Return On Equity
| ADPR34 Stock | BRL 76.56 3.32 4.53% |
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 Return On Equity vs. Total Debt 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 rated below average in total debt category among its peers. It also is rated below average in return on equity category among its peers . The ratio of Total Debt to Return On Equity for Automatic Data Processing is about 3,814,942,529 . 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.Automatic Total Debt vs. Competition
Automatic Data Processing is rated below average in total debt category among its peers. Total debt of Staffing & Employment Services industry is presently estimated at about 45.91 Billion. Automatic Data holds roughly 2.99 Billion in total debt claiming about 7% of equities listed under Staffing & Employment Services industry.
Automatic Return On Equity vs. Total Debt
Total Debt refers to the amount of long term interest-bearing liabilities that a company carries on its balance sheet. That may include bonds sold to the public, notes written to banks or capital leases. Typically, debt can help a company magnify its earnings, but the burden of interest and principal payments will eventually prevent the firm from borrow excessively.
Automatic Data |
| = | 2.99 B |
In most industries, total debt may also include the current portion of long-term debt. Since debt terms vary widely from one company to another, simply comparing outstanding debt obligations between different companies may not be adequate. It is usually meant to compare total debt amounts between companies that operate within the same sector.
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 |
| = | 0.78 |
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 rated below average in return on equity 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.
Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. The company was founded in 1949 and is headquartered in Roseland, New Jersey. AUTOMATIC DTDRN operates under Staffing Employment Services classification in Brazil and is traded on Sao Paolo Stock Exchange. It employs 58000 people.
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 Preferred Stock ETFs Thematic Idea Now
Preferred Stock ETFs
ETF themes focus on helping investors to gain exposure to a broad range of assets, diversify, and lower overall costs. The Preferred Stock ETFs theme has 16 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 Preferred Stock ETFs Theme or any other thematic opportunities.
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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. You can also try the Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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.