Automatic Data Price To Sales vs. EBITDA

0HJI Stock   296.94  2.82  0.94%   
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 this time. It has a very high probability of underperforming in January. 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 EBITDA vs. Price To Sales 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 sales category among its peers. It also is number one stock in ebitda category among its peers totaling about  849,314,443  of EBITDA per Price To Sales. At this time, Automatic Data's EBITDA is comparatively stable compared to the past year. 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 EBITDA vs. Price To Sales

Price to Sales ratio is typically used for valuing equity relative to its own past performance as well as to performance of other companies or market indexes. In most cases, the lower the ratio, the better it is for investors. However, it is advisable for investors to exercise caution when looking at price-to-sales ratios across different industries.

Automatic Data

P/S

 = 

MV Per Share

Revenue Per Share

 = 
6.57 X
The most critical factor to remember is that the price of equity takes a firm's debt into account, whereas the sales indicators do not consider financial leverage. Generally speaking, Price to Sales ratio shows how much market values every dollar of the company's sales.
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

 = 
5.58 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.

Automatic EBITDA Comparison

Automatic Data is currently under evaluation in ebitda 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 ReportedProjected for Next Year
Accumulated Other Comprehensive Income-1.8 B-1.7 B
Operating Income4.5 B3.2 B
Income Before Tax4.9 B3.2 B
Total Other Income Expense Net337.9 M354.8 M
Net Income3.8 B2.5 B
Income Tax Expense1.1 B829.4 M
Interest Income11.7 M13.2 M
Net Income Applicable To Common Shares3.9 B2.7 B
Change To Netincome172.9 M207.6 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.
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 Cancer Fighters Thematic Idea Now

Cancer Fighters
Cancer Fighters Theme
Biotech and medical diagnostic companies that work on researching drugs or manufacturing of medical and therapeutics equipment that is directly related to the research, treatment, and detection of cancer or cancer related diseases. The Cancer Fighters theme has 60 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 Cancer Fighters Theme or any other thematic opportunities.
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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.