Automatic Net Receivables from 2010 to 2026

ADP Stock  EUR 197.60  1.66  0.85%   
Automatic Data's Net Receivables is increasing over the last several years with slightly volatile swings. Net Receivables is predicted to flatten to about 2.7 B. During the period from 2010 to 2026 Automatic Data Processing Net Receivables regressed destribution of quarterly values had coefficient of variationof  35.70 and r-value of  0.91. View All Fundamentals
 
Net Receivables  
First Reported
2017-03-31
Previous Quarter
3.5 B
Current Value
3.4 B
Quarterly Volatility
552.4 M
 
Covid
 
Interest Hikes
Check Automatic Data financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Automatic Data's main balance sheet or income statement drivers, such as Interest Expense of 550.5 M, Selling General Administrative of 3.4 B or Total Revenue of 16.1 B, as well as many indicators such as . Automatic financial statements analysis is a perfect complement when working with Automatic Data Valuation or Volatility modules.
  
This module can also supplement various Automatic Data Technical models . Check out the analysis of Automatic Data Correlation against competitors.
The Net Receivables trend for Automatic Data Processing offers valuable insights into the company's financial trajectory and strategic direction. By examining multi-year patterns, investors can identify whether Automatic Data is strengthening or weakening its position, and how this metric correlates with broader market conditions and industry benchmarks.

Latest Automatic Data's Net Receivables Growth Pattern

Below is the plot of the Net Receivables of Automatic Data Processing over the last few years. It is Automatic Data's Net Receivables 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.
Net Receivables10 Years Trend
Slightly volatile
   Net Receivables   
       Timeline  

Automatic Net Receivables Regression Statistics

Arithmetic Mean2,386,318,431
Geometric Mean2,249,327,435
Coefficient Of Variation35.70
Mean Deviation719,746,759
Median2,439,300,000
Standard Deviation851,877,803
Sample Variance725695.8T
Range2.6B
R-Value0.91
Mean Square Error134502.9T
R-Squared0.83
Slope153,341,769
Total Sum of Squares11611132.7T

Automatic Net Receivables History

20262.7 B
20254.1 B
20243.6 B
20233.4 B
2022B
20213.2 B
20202.7 B

About Automatic Data Financial Statements

Automatic Data stakeholders use historical fundamental indicators, such as Automatic Data's Net Receivables, to determine how well the company is positioned to perform in the future. Although Automatic Data investors may analyze each financial statement separately, they are all interrelated. For example, changes in Automatic Data's assets and liabilities are reflected in the revenues and expenses on Automatic Data's income statement, which ultimately affect the company's gains or losses. Understanding these patterns can help in making the right long-term investment decisions in Automatic Data Processing. Please read more on our technical analysis and fundamental analysis pages.
Last ReportedProjected for Next Year
Net Receivables4.1 B2.7 B

Currently Active Assets on Macroaxis

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 the analysis of Automatic Data Correlation against competitors.
You can also try the ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.
Understanding that Automatic Data's value differs from its trading price is crucial, as each reflects different aspects of the company. Evaluating whether Automatic Data represents a sound investment requires analyzing earnings trends, revenue growth, technical signals, industry dynamics, and expert forecasts. In contrast, Automatic Data's trading price reflects the actual exchange value where willing buyers and sellers reach mutual agreement.