Automatic Capital Expenditures from 2010 to 2024
| ADP Stock | USD 246.84 0.53 0.22% |
Capital Expenditures | First Reported 1989-06-30 | Previous Quarter 126.3 M | Current Value 133.5 M | Quarterly Volatility 48.1 M |
Check Automatic Data financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Automatic main balance sheet or income statement drivers, such as Depreciation And Amortization of 663.3 M, Interest Expense of 305.9 M or Selling General Administrative of 4.3 B, as well as many exotic indicators such as Price To Sales Ratio of 2.41, Dividend Yield of 0.0153 or PTB Ratio of 24.49. Automatic financial statements analysis is a perfect complement when working with Automatic Data Valuation or Volatility modules.
Automatic | Capital Expenditures |
Latest Automatic Data's Capital Expenditures Growth Pattern
Below is the plot of the Capital Expenditures of Automatic Data Processing over the last few years. Capital Expenditures are funds used by Automatic Data Processing to acquire physical assets such as property, industrial buildings or equipment. This type of outlay is used by management to increase the scope of Automatic Data operations. These expenditures can include everything from repairing an office equipment, building a brand new facility, or writing new software. It is Automatic Data's Capital Expenditures historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Automatic Data's overall financial position and show how it may be relating to other accounts over time.
| Capital Expenditures | 10 Years Trend |
|
Capital Expenditures |
| Timeline |
Automatic Capital Expenditures Regression Statistics
| Arithmetic Mean | 457,583,133 | |
| Geometric Mean | 424,627,288 | |
| Coefficient Of Variation | 35.00 | |
| Mean Deviation | 131,266,507 | |
| Median | 470,800,000 | |
| Standard Deviation | 160,166,088 | |
| Sample Variance | 25653.2T | |
| Range | 550.9M | |
| R-Value | 0.95 | |
| Mean Square Error | 2534.2T | |
| R-Squared | 0.91 | |
| Slope | 34,132,104 | |
| Total Sum of Squares | 359144.5T |
Automatic Capital Expenditures History
About Automatic Data Financial Statements
There are typically three primary documents that fall into the category of financial statements. These documents include Automatic Data income statement, its balance sheet, and the statement of cash flows. Automatic Data investors use historical funamental indicators, such as Automatic Data's Capital Expenditures, to determine how well the company is positioned to perform in the future. Although Automatic Data investors may use 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. We offer a historical overview of the basic patterns found on Automatic Data Financial Statements. Understanding these patterns can help to make the right decision on long term investment in Automatic Data. Please read more on our technical analysis and fundamental analysis pages.
| Last Reported | Projected for Next Year | ||
| Capital Expenditures | 657.3 M | 690.2 M |
Pair Trading with Automatic Data
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.Moving against Automatic Stock
| 0.67 | EXPO | Exponent Earnings Call Tomorrow | PairCorr |
| 0.54 | VIRC | Virco Manufacturing Report 26th of April 2024 | PairCorr |
| 0.53 | FC | Franklin Covey Financial Report 26th of June 2024 | PairCorr |
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.Check out the analysis of Automatic Data Correlation against competitors. Note that the Automatic Data Processing information on this page should be used as a complementary analysis to other Automatic Data's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Global Markets Map module to get a quick overview of global market snapshot using zoomable world map. Drill down to check world indexes.
Complementary 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.
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Is Automatic Data's industry 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 0.092 | Dividend Share 5.15 | Earnings Share 8.6 | Revenue Per Share 45.09 | Quarterly Revenue Growth 0.063 |
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.