Automatic Current Deferred Revenue from 2010 to 2026

ADP Stock  USD 212.97  -0.03  -0.01%   
Automatic Data's Current Deferred Revenue is moving in a falling direction with slightly volatile fluctuations. Forward guidance implies movement down to approximately 207.4 M. Current Deferred Revenue is revenue that has been collected but not yet earned, typically from prepaid service contracts or subscriptions. This amount is considered a liability until the service is provided or the subscription period ends. View All Fundamentals
 
Current Deferred Revenue  
 First Reported
2005-12-31
 Previous Quarter
258.1 M
 Current Value
261.7 M
 Quarterly Volatility
93.4 M
Macro event markers
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
 
Interest Hikes
Review Automatic Data financial statements over time to add context on performance and capital structure. Track Depreciation And Amortization of 319 M, Interest Expense of 550.5 M or Selling General Administrative of 4.9 B and ratios such as Price To Sales Ratio of 5.77, Dividend Yield of 0.0148 or PTB Ratio of 19.17 to align performance context with Automatic Data Valuation and Volatility.
  
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Review Automatic Data Correlation against competitors for Automatic Data. The view adds relative comparison context.
Evaluating Automatic Data's Current Deferred Revenue across multiple reporting periods reveals the company's ability to sustain growth and manage resources effectively. This longitudinal analysis highlights inflection points, cyclical patterns, and structural changes that short-term snapshots might miss, offering deeper insight into Automatic Data Processing's fundamental strength.

Latest Automatic Data's Current Deferred Revenue Growth Pattern

Below is the plot of the Current Deferred Revenue of Automatic Data Processing over the last few years. It is revenue that has been collected but not yet earned, typically from prepaid service contracts or subscriptions. This amount is considered a liability until the service is provided or the subscription period ends. Automatic Data's Current Deferred Revenue 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.
Current Deferred Revenue10 Years Trend
Slightly volatile
   Current Deferred Revenue   
       Timeline  

Automatic Current Deferred Revenue Regression Statistics

Arithmetic Mean 233,637,176
Geometric Mean 230,811,384
Coefficient Of Variation 16.96
Mean Deviation 26,787,875
Median 228,600,000
Standard Deviation 39,635,420
Sample Variance1571T
Range145.9M
R-Value-0.58
Mean Square Error1120.5T
R-Squared 0.33
Significance 0.02
Slope-4,517,804
Total Sum of Squares25135.5T

Automatic Current Deferred Revenue History

2026207.4 M
2025236.5 M
2024262.8 M
2023199.8 M
2022188.6 M
2021188.2 M
2020203.9 M

About Automatic Data Processing Inc

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 Data operates under Staffing Employment Services classification in the United States and is traded on NASDAQ Exchange. It employs 60000 people. A high-level view of Automatic Data emphasizes earnings durability, balance-sheet flexibility, and competitive positioning. Current metrics include P/E of 35.6, P/B of 13.69, profit margin of 19.96%. Automatic Data has a market cap of 86.15 B, P/E of 35.6, ROE of 73.84%.

Methodology

Unless otherwise specified, financial data for Automatic Data Processing is derived from periodic company reporting (annual and quarterly where available). Asset-level metrics are computed daily by Macroaxis LLC and refreshed regularly based on asset type. Automatic (USA Stocks:ADP) prices are typically delayed by approximately 20 minutes from primary exchanges for listed equities. Data may be delayed depending on reporting sources and market conventions. Assumptions: Inputs are aggregated from public filings and market reference sources and public institutions such as U.S. Securities and Exchange Commission (SEC) via EDGAR. Certain values may not reflect real-time changes. All analytics are generated using standardized, rules-based models designed to promote consistency and comparability across instruments. Model assumptions, reference parameters, and selected computational inputs are available in the Model Inputs section. If you have questions about our data sources or methodology, please contact Macroaxis Support.

Analyst Sources

Automatic Data Processing is covered by 17 analysts. 8 analysts have submitted revenue and/or earnings estimates that may be incorporated into Macroaxis consensus inputs where available. Representative analyst firms may include Bernstein Research, Deutsche Bank, Morgan Stanley, BMO Capital Markets, Guggenheim Securities, Jefferies, Goldman Sachs, Evercore ISI, Raymond James, UBS Investment Research, among others. Updates may occur throughout the day.

Pair Trading with Automatic Data

Pair trading with Automatic Data can help investors hedge some company-specific exposure by balancing a long view with an offsetting position. The key question is whether the second leg adds real hedge value instead of just creating a more complex version of the same risk.

Moving together with Automatic Stock

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Moving against Automatic Stock

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Correlation analysis helps investors find suitable substitutes for Automatic Data during tax-loss harvesting periods. Selling Automatic Data Processing at a loss and immediately repurchasing it would violate IRS wash-sale rules, so a correlated replacement asset is required to maintain portfolio.
Measuring the statistical correlation of Automatic Data Processing against other instruments helps investors understand portfolio diversification. A correlation near zero implies that Automatic Data provides genuine diversification benefits, while high positive correlations suggest redundant exposures.
Correlation analysis and pair trading evaluation for Automatic Data can be used to frame hedging context. The context can be applied within sectors, industries, or broader universes.
Pair CorrelationCorrelation Matching

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