Automatic Operating Profit Margin vs Pretax Profit Margin Analysis

ADP Stock

USD 302.23 4.67 1.57%

Automatic Data financial indicator trend analysis is way more than just evaluating Automatic Data Processing prevailing accounting drivers to predict future trends. We encourage investors to analyze account correlations over time for multiple indicators to determine whether Automatic Data Processing is a good investment. Please check the relationship between Automatic Data Operating Profit Margin and its Pretax Profit Margin accounts. Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in Automatic Data Processing. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in unemployment.

Operating Profit Margin vs Pretax Profit Margin

Operating Profit Margin vs Pretax Profit Margin Correlation Analysis

The overlapping area represents the amount of trend that can be explained by analyzing historical patterns of Automatic Data Processing Operating Profit Margin account and Pretax Profit Margin. At this time, the significance of the direction appears to have strong relationship.

The correlation between Automatic Data's Operating Profit Margin and Pretax Profit Margin is 0.79. Overlapping area represents the amount of variation of Operating Profit Margin that can explain the historical movement of Pretax Profit Margin in the same time period over historical financial statements of Automatic Data Processing, assuming nothing else is changed. The correlation between historical values of Automatic Data's Operating Profit Margin and Pretax Profit Margin is a relative statistical measure of the degree to which these accounts tend to move together. The correlation coefficient measures the extent to which Operating Profit Margin of Automatic Data Processing are associated (or correlated) with its Pretax Profit Margin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when Pretax Profit Margin has no effect on the direction of Operating Profit Margin i.e., Automatic Data's Operating Profit Margin and Pretax Profit Margin go up and down completely randomly.

Correlation Coefficient

0.79

Relationship Direction	Positive
Relationship Strength	Significant

View All Relationships

Operating Profit Margin

Pretax Profit Margin

Most indicators from Automatic Data's fundamental ratios are interrelated and interconnected. However, analyzing fundamental ratios indicators one by one will only give a small insight into Automatic Data Processing current financial condition. On the other hand, looking into the entire matrix of fundamental ratios indicators, and analyzing their relationships over time can provide a more complete picture of the company financial strength now and in the future. Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in Automatic Data Processing. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in unemployment.

At this time, Automatic Data's Sales General And Administrative To Revenue is relatively stable compared to the past year. As of 12/11/2024, Enterprise Value is likely to grow to about 61 B, while Selling General Administrative is likely to drop slightly above 2 B.

	2021	2022	2023	2024 (projected)
Gross Profit	7.0B	8.1B	8.7B	9.2B
Total Revenue	16.5B	18.0B	19.2B	20.2B

Gross Profit Total Revenue

Automatic Data fundamental ratios Correlations

	Total Assets	Short Long Term Debt Total	Other Current Liab	Total Current Liabilities	Total Stockholder Equity	Property Plant And Equipment Net	Net Debt	Retained Earnings	Cash	Non Current Assets Total	Non Currrent Assets Other	Cash And Short Term Investments	Net Receivables	Good Will	Common Stock Shares Outstanding	Non Current Liabilities Total	Inventory	Other Current Assets	Other Stockholder Equity	Total Liab	Property Plant And Equipment Gross	Total Current Assets	Short Term Debt	Intangible Assets	Accounts Payable	Common Stock Total Equity
Total Assets		0.7	0.99	0.99	0.23	0.72	0.61	0.95	0.27	0.85	0.78	0.3	0.94	0.41	-0.93	0.88	0.37	0.69	-0.95	0.99	0.62	1.0	0.18	0.85	0.14	0.47
Short Long Term Debt Total	0.7		0.67	0.71	-0.14	0.65	0.74	0.75	0.24	0.7	0.8	0.26	0.78	0.09	-0.71	0.83	0.19	0.42	-0.8	0.73	0.49	0.68	0.67	0.76	-0.33	0.34
Other Current Liab	0.99	0.67		1.0	0.14	0.68	0.64	0.91	0.21	0.79	0.75	0.23	0.92	0.33	-0.89	0.87	0.4	0.73	-0.92	1.0	0.62	1.0	0.1	0.81	0.11	0.48
Total Current Liabilities	0.99	0.71	1.0		0.15	0.7	0.64	0.93	0.23	0.82	0.76	0.25	0.93	0.36	-0.9	0.88	0.37	0.71	-0.94	1.0	0.62	1.0	0.18	0.83	0.1	0.47
Total Stockholder Equity	0.23	-0.14	0.14	0.15		0.31	-0.41	0.31	0.51	0.45	0.04	0.51	0.2	0.84	-0.32	-0.01	-0.06	-0.08	-0.15	0.13	0.01	0.19	0.06	0.2	0.7	0.03
Property Plant And Equipment Net	0.72	0.65	0.68	0.7	0.31		0.62	0.75	0.28	0.84	0.64	0.28	0.74	0.45	-0.81	0.72	0.52	0.45	-0.79	0.71	0.27	0.69	0.35	0.88	-0.09	0.2
Net Debt	0.61	0.74	0.64	0.64	-0.41	0.62		0.6	-0.27	0.58	0.71	-0.26	0.71	-0.16	-0.54	0.79	0.52	0.67	-0.7	0.66	0.47	0.59	0.19	0.78	-0.64	0.32
Retained Earnings	0.95	0.75	0.91	0.93	0.31	0.75	0.6		0.27	0.92	0.85	0.29	0.98	0.46	-0.94	0.87	0.25	0.61	-0.98	0.93	0.71	0.92	0.3	0.9	0.1	0.58
Cash	0.27	0.24	0.21	0.23	0.51	0.28	-0.27	0.27		0.25	0.14	1.0	0.2	0.43	-0.38	0.21	-0.06	-0.05	-0.23	0.23	0.08	0.28	0.29	0.11	0.43	0.14
Non Current Assets Total	0.85	0.7	0.79	0.82	0.45	0.84	0.58	0.92	0.25		0.77	0.26	0.91	0.63	-0.87	0.77	0.3	0.54	-0.88	0.82	0.55	0.8	0.39	0.94	0.04	0.44
Non Currrent Assets Other	0.78	0.8	0.75	0.76	0.04	0.64	0.71	0.85	0.14	0.77		0.16	0.87	0.13	-0.79	0.87	0.34	0.58	-0.87	0.79	0.67	0.75	0.31	0.8	-0.18	0.53
Cash And Short Term Investments	0.3	0.26	0.23	0.25	0.51	0.28	-0.26	0.29	1.0	0.26	0.16		0.22	0.43	-0.39	0.23	-0.07	-0.02	-0.25	0.25	0.11	0.3	0.29	0.12	0.43	0.16
Net Receivables	0.94	0.78	0.92	0.93	0.2	0.74	0.71	0.98	0.2	0.91	0.87	0.22		0.37	-0.9	0.9	0.29	0.71	-0.97	0.94	0.75	0.91	0.28	0.92	-0.04	0.62
Good Will	0.41	0.09	0.33	0.36	0.84	0.45	-0.16	0.46	0.43	0.63	0.13	0.43	0.37		-0.46	0.13	0.04	0.06	-0.33	0.34	0.09	0.37	0.25	0.42	0.56	0.07
Common Stock Shares Outstanding	-0.93	-0.71	-0.89	-0.9	-0.32	-0.81	-0.54	-0.94	-0.38	-0.87	-0.79	-0.39	-0.9	-0.46		-0.88	-0.42	-0.47	0.96	-0.91	-0.5	-0.91	-0.25	-0.88	-0.16	-0.4
Non Current Liabilities Total	0.88	0.83	0.87	0.88	-0.01	0.72	0.79	0.87	0.21	0.77	0.87	0.23	0.9	0.13	-0.88		0.47	0.65	-0.93	0.9	0.6	0.88	0.19	0.86	-0.18	0.45
Inventory	0.37	0.19	0.4	0.37	-0.06	0.52	0.52	0.25	-0.06	0.3	0.34	-0.07	0.29	0.04	-0.42	0.47		0.33	-0.35	0.38	-0.17	0.38	-0.24	0.45	-0.14	-0.27
Other Current Assets	0.69	0.42	0.73	0.71	-0.08	0.45	0.67	0.61	-0.05	0.54	0.58	-0.02	0.71	0.06	-0.47	0.65	0.33		-0.63	0.71	0.73	0.69	-0.18	0.59	-0.14	0.6
Other Stockholder Equity	-0.95	-0.8	-0.92	-0.94	-0.15	-0.79	-0.7	-0.98	-0.23	-0.88	-0.87	-0.25	-0.97	-0.33	0.96	-0.93	-0.35	-0.63		-0.95	-0.68	-0.93	-0.29	-0.92	0.02	-0.55
Total Liab	0.99	0.73	1.0	1.0	0.13	0.71	0.66	0.93	0.23	0.82	0.79	0.25	0.94	0.34	-0.91	0.9	0.38	0.71	-0.95		0.62	0.99	0.18	0.84	0.07	0.48
Property Plant And Equipment Gross	0.62	0.49	0.62	0.62	0.01	0.27	0.47	0.71	0.08	0.55	0.67	0.11	0.75	0.09	-0.5	0.6	-0.17	0.73	-0.68	0.62		0.59	0.04	0.54	-0.1	0.95
Total Current Assets	1.0	0.68	1.0	1.0	0.19	0.69	0.59	0.92	0.28	0.8	0.75	0.3	0.91	0.37	-0.91	0.88	0.38	0.69	-0.93	0.99	0.59		0.14	0.81	0.16	0.45
Short Term Debt	0.18	0.67	0.1	0.18	0.06	0.35	0.19	0.3	0.29	0.39	0.31	0.29	0.28	0.25	-0.25	0.19	-0.24	-0.18	-0.29	0.18	0.04	0.14		0.33	-0.16	-0.03
Intangible Assets	0.85	0.76	0.81	0.83	0.2	0.88	0.78	0.9	0.11	0.94	0.8	0.12	0.92	0.42	-0.88	0.86	0.45	0.59	-0.92	0.84	0.54	0.81	0.33		-0.19	0.42
Accounts Payable	0.14	-0.33	0.11	0.1	0.7	-0.09	-0.64	0.1	0.43	0.04	-0.18	0.43	-0.04	0.56	-0.16	-0.18	-0.14	-0.14	0.02	0.07	-0.1	0.16	-0.16	-0.19		-0.12
Common Stock Total Equity	0.47	0.34	0.48	0.47	0.03	0.2	0.32	0.58	0.14	0.44	0.53	0.16	0.62	0.07	-0.4	0.45	-0.27	0.6	-0.55	0.48	0.95	0.45	-0.03	0.42	-0.12

Click cells to compare fundamentals

Automatic Data Account Relationship Matchups

Automatic Data fundamental ratios Accounts

	2019	2020	2021	2022	2023	2024 (projected)
Total Assets	39.2B	48.8B	63.1B	51.0B	54.4B	57.1B
Short Long Term Debt Total	2.3B	3.3B	3.5B	6.8B	3.7B	3.9B
Other Current Liab	28.8B	37.7B	54.6B	38.6B	44.3B	46.5B
Total Current Liabilities	30.1B	38.1B	55.2B	42.8B	45.1B	47.3B
Total Stockholder Equity	5.8B	5.7B	3.2B	3.5B	4.5B	4.3B
Property Plant And Equipment Net	1.2B	1.1B	1.1B	1.1B	1.1B	723.2M
Net Debt	440.5M	753M	2.1B	1.3B	791.9M	831.5M
Retained Earnings	18.4B	19.5B	20.7B	22.1B	23.6B	24.8B
Cash	1.9B	2.6B	1.4B	2.1B	2.9B	1.5B
Non Current Assets Total	7.6B	8.0B	8.3B	8.8B	8.8B	7.8B
Non Currrent Assets Other	2.9B	3.3B	3.3B	4.0B	4.1B	4.6B
Cash And Short Term Investments	1.9B	2.6B	1.5B	2.1B	2.9B	1.6B
Net Receivables	2.4B	2.7B	3.2B	3.0B	3.4B	3.6B
Good Will	2.3B	2.3B	2.3B	2.3B	2.4B	1.9B
Common Stock Shares Outstanding	432.7M	428.1M	421.1M	415.7M	412.2M	431.7M
Liabilities And Stockholders Equity	39.2B	48.8B	63.1B	51.0B	54.4B	57.1B
Non Current Liabilities Total	3.3B	5.0B	4.7B	4.7B	4.7B	4.8B
Inventory	26.7B	34.9B	49.6B	1.0	1.15	1.09
Other Current Assets	506.2M	35.4B	50.2B	743.9M	39.2B	41.2B
Other Stockholder Equity	(12.7B)	(13.9B)	(15.5B)	(16.4B)	(17.3B)	(16.5B)
Total Liab	33.4B	43.1B	59.8B	47.5B	49.8B	52.3B
Property Plant And Equipment Gross	703M	1.1B	1.1B	1.1B	2.9B	3.0B
Total Current Assets	31.6B	40.7B	54.8B	42.2B	45.5B	47.8B
Accumulated Other Comprehensive Income	(14.8M)	10.6M	(2.0B)	(2.3B)	(1.8B)	(1.7B)
Short Term Debt	1.0B	23.5M	232.7M	3.8B	478.7M	506.5M
Intangible Assets	1.2B	1.2B	1.3B	1.3B	1.3B	1.1B
Accounts Payable	102M	141.1M	110.2M	96.8M	100.6M	137.4M
Short Term Investments	0.0	10.4M	32.7M	14.7M	384M	231.6M
Other Liab	1.9B	1.7B	1.3B	1.4B	1.2B	1.2B
Other Assets	2.9B	3.3B	3.5B	4.0B	1.0	0.95
Long Term Debt	1.0B	3.0B	3.0B	3.0B	3.0B	3.1B
Treasury Stock	(14.1B)	(15.4B)	(17.3B)	(18.5B)	(16.6B)	(15.8B)
Property Plant Equipment	703.9M	1.1B	1.1B	681.4M	783.6M	809.7M
Current Deferred Revenue	212.5M	203.9M	188.2M	188.6M	199.8M	223.3M
Net Tangible Assets	2.2B	2.1B	(408.3M)	(173.9M)	(156.5M)	(148.7M)
Retained Earnings Total Equity	18.4B	19.5B	20.7B	22.1B	25.4B	17.1B
Capital Surpluse	1.3B	1.5B	1.8B	2.1B	2.4B	2.5B

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 together with Automatic Stock

0.86	DJCO	Daily Journal Corp	Pair Corr
0.76	AI	C3 Ai Inc Tech Boost	Pair Corr
0.93	BL	Blackline	Pair Corr
0.63	DT	Dynatrace Holdings LLC	Pair Corr

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 Correlation Correlation Matching

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.

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