Automatic Data EBITDA vs. Shares Owned By Institutions

ADP Stock  EUR 291.10  1.65  0.56%   
Based on the key profitability measurements obtained from Automatic Data's financial statements, Automatic Data Processing may not be well positioned to generate adequate gross income at the moment. It has a very high risk of underperforming in December. Profitability indicators assess Automatic Data's ability to earn profits and add value for shareholders.
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.
  
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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 Shares Owned By Institutions vs. EBITDA 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 ebitda category among its peers. It also is number one stock in shares owned by institutions category among its peers . The ratio of EBITDA to Shares Owned By Institutions for Automatic Data Processing is about  52,581,840 . 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 Shares Owned By Institutions vs. EBITDA

EBITDA stands for earnings before interest, taxes, depreciation, and amortization. It is a measure of a company operating cash flow based on data from the company income statement and is a very good way to compare companies within industries or across different sectors. However, unlike Operating Cash Flow, EBITDA does not include the effects of changes in working capital.

Automatic Data

EBITDA

 = 

Revenue

-

Basic Expenses

 = 
4.4 B
In a nutshell, EBITDA is calculated by adding back each of the excluded items to the post-tax profit, and can be used to compare companies with very different capital structures.
Shares Owned by Institutions show the percentage of the outstanding shares of stock issued by a company that is currently owned by other institutions such as asset management firms, hedge funds, or investment banks. Many investors like investing in companies with a large percentage of the firm owned by institutions because they believe that larger firms such as banks, pension funds, and mutual funds, will invest when they think that good things are going to happen.

Automatic Data

Shares Held by Institutions

 = 

Funds and Banks

+

Firms

 = 
83.70 %
Since Institution investors conduct a lot of independent research they tend to be more involved and usually more knowledgeable about entities they invest as compared to amateur investors.

Automatic Shares Owned By Institutions Comparison

Automatic Data is currently under evaluation in shares owned by institutions 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 business process outsourcing services worldwide. The company was founded in 1949 and is headquartered in Roseland, New Jersey. AUTOM DATA is traded on Frankfurt Stock Exchange in Germany.

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.
Pair CorrelationCorrelation Matching

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 Social Domain Thematic Idea Now

Social Domain
Social Domain Theme
New or established large and mid-sized companies that are involved in the social media industry, including entities that provide web-based or mobile media applications and services across across large segment of population in multiple geographical areas. The Social Domain theme has 39 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 Social Domain 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:
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You can also try the Funds Screener module to find actively-traded funds from around the world traded on over 30 global exchanges.
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.
Potential Automatic Data investors and stakeholders can use historical trends found within financial statements to determine how well the company is positioned for the future. Although Automatic Data investors may work on each financial statement separately, they are all related. The changes in Automatic Data's assets and liabilities, for example, are also reflected in the revenues and expenses that we see on Automatic Data's income statement, which results in the company's gains or losses. Cash flows can provide more information regarding cash listed on a balance sheet but not equivalent to net income shown on the income statement. Please read more on our technical analysis and fundamental analysis pages.