Automatic Data Processing Stock Debt To Equity

ADP Stock

USD 306.93 0.01 0%

Automatic Data Processing fundamentals help investors to digest information that contributes to Automatic Data's financial success or failures. It also enables traders to predict the movement of Automatic Stock. The fundamental analysis module provides a way to measure Automatic Data's intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Automatic Data stock.

		Last Reported	Projected for Next Year
	Debt To Equity	0.76	0.80

As of 11/30/2024, Debt To Equity is likely to grow to 0.80.

This module does not cover all equities due to inconsistencies in global equity categorizations. Continue to Equity Screeners to view more equity screening tools.

Automatic Data Processing Company Debt To Equity Analysis

Automatic Data's Debt to Equity is calculated by dividing the Total Debt of a company by its Equity. If the debt exceeds equity of a company, then the creditors have more stakes in a firm than the stockholders. In other words, Debt to Equity ratio provides analysts with insights about composition of both equity and debt, and its influence on the valuation of the company.

D/E

Total Debt

Total Equity

More About Debt To Equity | All Equity Analysis

Current Automatic Data Debt To Equity

1.40 %

Most of Automatic Data's fundamental indicators, such as Debt To Equity, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, Automatic Data Processing is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.

Automatic Debt To Equity Driver Correlations

Understanding the fundamental principles of building solid financial models for Automatic Data is extremely important. It helps to project a fair market value of Automatic Stock properly, considering its historical fundamentals such as Debt To Equity. Since Automatic Data's main accounts across its financial reports are all linked and dependent on each other, it is essential to analyze all possible correlations between related accounts. However, instead of reviewing all of Automatic Data's historical financial statements, investors can examine the correlated drivers to determine its overall health. This can be effectively done using a conventional correlation matrix of Automatic Data's interrelated accounts and indicators.

	Total Assets	Total Stockholder Equity	Net Debt	Retained Earnings	Net Receivables	Good Will	Total Liab	Total Current Assets	Short Term Debt	Intangible Assets	Accounts Payable	Short Term Investments	Common Stock	Long Term Debt	Treasury Stock	Property Plant Equipment	Current Deferred Revenue	Net Tangible Assets	Capital Surpluse	Deferred Long Term Liab	Long Term Investments	Short Long Term Debt	Long Term Debt Total	Net Invested Capital	Net Working Capital	Capital Stock
Total Assets		0.23	0.61	0.95	0.94	0.41	0.99	1.0	0.18	0.85	0.14	-0.15	0.47	0.8	-0.93	0.6	-0.89	-0.7	0.78	0.49	-0.61	-0.63	0.78	0.48	-0.7	-0.42
Total Stockholder Equity	0.23		-0.41	0.31	0.2	0.84	0.13	0.19	0.06	0.2	0.7	0.3	0.03	-0.23	-0.13	0.14	-0.32	0.38	-0.15	-0.07	0.21	0.0	-0.2	0.25	0.27	0.05
Net Debt	0.61	-0.41		0.6	0.71	-0.16	0.66	0.59	0.19	0.78	-0.64	-0.32	0.32	0.81	-0.73	0.53	-0.44	-0.77	0.83	0.61	-0.59	-0.65	0.78	0.55	-0.85	-0.32
Retained Earnings	0.95	0.31	0.6		0.98	0.46	0.93	0.92	0.3	0.9	0.1	-0.1	0.58	0.77	-0.95	0.48	-0.87	-0.69	0.85	0.4	-0.6	-0.66	0.73	0.6	-0.72	-0.52
Net Receivables	0.94	0.2	0.71	0.98		0.37	0.94	0.91	0.28	0.92	-0.04	-0.07	0.62	0.81	-0.95	0.53	-0.8	-0.75	0.91	0.47	-0.61	-0.69	0.78	0.64	-0.79	-0.57
Good Will	0.41	0.84	-0.16	0.46	0.37		0.34	0.37	0.25	0.42	0.56	0.27	0.07	-0.05	-0.33	0.26	-0.4	-0.02	0.03	0.07	0.2	-0.02	-0.01	0.08	-0.09	0.05
Total Liab	0.99	0.13	0.66	0.93	0.94	0.34		0.99	0.18	0.84	0.07	-0.18	0.48	0.84	-0.94	0.6	-0.87	-0.76	0.81	0.51	-0.64	-0.65	0.82	0.46	-0.74	-0.42
Total Current Assets	1.0	0.19	0.59	0.92	0.91	0.37	0.99		0.14	0.81	0.16	-0.17	0.45	0.81	-0.92	0.61	-0.89	-0.71	0.76	0.49	-0.63	-0.61	0.79	0.43	-0.68	-0.4
Short Term Debt	0.18	0.06	0.19	0.3	0.28	0.25	0.18	0.14		0.33	-0.16	0.38	-0.03	0.14	-0.33	-0.18	-0.16	-0.23	0.29	-0.24	-0.09	-0.17	0.15	-0.01	-0.46	0.04
Intangible Assets	0.85	0.2	0.78	0.9	0.92	0.42	0.84	0.81	0.33		-0.19	-0.17	0.42	0.75	-0.94	0.55	-0.77	-0.69	0.83	0.56	-0.57	-0.7	0.76	0.66	-0.8	-0.3
Accounts Payable	0.14	0.7	-0.64	0.1	-0.04	0.56	0.07	0.16	-0.16	-0.19		0.17	-0.12	-0.28	0.04	0.08	-0.29	0.33	-0.35	-0.14	0.14	0.11	-0.3	-0.23	0.44	0.07
Short Term Investments	-0.15	0.3	-0.32	-0.1	-0.07	0.27	-0.18	-0.17	0.38	-0.17	0.17		0.09	-0.3	0.22	-0.04	0.28	0.24	-0.15	-0.29	0.25	0.28	-0.29	-0.12	0.16	-0.06
Common Stock	0.47	0.03	0.32	0.58	0.62	0.07	0.48	0.45	-0.03	0.42	-0.12	0.09		0.46	-0.42	0.06	-0.29	-0.55	0.71	-0.06	-0.28	-0.29	0.43	0.49	-0.44	-0.84
Long Term Debt	0.8	-0.23	0.81	0.77	0.81	-0.05	0.84	0.81	0.14	0.75	-0.28	-0.3	0.46		-0.85	0.56	-0.69	-0.79	0.85	0.61	-0.75	-0.58	0.97	0.53	-0.71	-0.44
Treasury Stock	-0.93	-0.13	-0.73	-0.95	-0.95	-0.33	-0.94	-0.92	-0.33	-0.94	0.04	0.22	-0.42	-0.85		-0.54	0.91	0.74	-0.85	-0.54	0.72	0.72	-0.85	-0.56	0.79	0.34
Property Plant Equipment	0.6	0.14	0.53	0.48	0.53	0.26	0.6	0.61	-0.18	0.55	0.08	-0.04	0.06	0.56	-0.54		-0.46	-0.33	0.38	0.74	-0.33	-0.45	0.56	0.44	-0.26	-0.05
Current Deferred Revenue	-0.89	-0.32	-0.44	-0.87	-0.8	-0.4	-0.87	-0.89	-0.16	-0.77	-0.29	0.28	-0.29	-0.69	0.91	-0.46		0.53	-0.61	-0.48	0.7	0.64	-0.7	-0.41	0.53	0.18
Net Tangible Assets	-0.7	0.38	-0.77	-0.69	-0.75	-0.02	-0.76	-0.71	-0.23	-0.69	0.33	0.24	-0.55	-0.79	0.74	-0.33	0.53		-0.84	-0.4	0.54	0.45	-0.76	-0.19	0.9	0.52
Capital Surpluse	0.78	-0.15	0.83	0.85	0.91	0.03	0.81	0.76	0.29	0.83	-0.35	-0.15	0.71	0.85	-0.85	0.38	-0.61	-0.84		0.36	-0.64	-0.68	0.8	0.65	-0.86	-0.69
Deferred Long Term Liab	0.49	-0.07	0.61	0.4	0.47	0.07	0.51	0.49	-0.24	0.56	-0.14	-0.29	-0.06	0.61	-0.54	0.74	-0.48	-0.4	0.36		-0.51	-0.46	0.6	0.39	-0.36	0.04
Long Term Investments	-0.61	0.21	-0.59	-0.6	-0.61	0.2	-0.64	-0.63	-0.09	-0.57	0.14	0.25	-0.28	-0.75	0.72	-0.33	0.7	0.54	-0.64	-0.51		0.62	-0.74	-0.44	0.52	0.24
Short Long Term Debt	-0.63	0.0	-0.65	-0.66	-0.69	-0.02	-0.65	-0.61	-0.17	-0.7	0.11	0.28	-0.29	-0.58	0.72	-0.45	0.64	0.45	-0.68	-0.46	0.62		-0.59	-0.64	0.6	0.22
Long Term Debt Total	0.78	-0.2	0.78	0.73	0.78	-0.01	0.82	0.79	0.15	0.76	-0.3	-0.29	0.43	0.97	-0.85	0.56	-0.7	-0.76	0.8	0.6	-0.74	-0.59		0.51	-0.68	-0.28
Net Invested Capital	0.48	0.25	0.55	0.6	0.64	0.08	0.46	0.43	-0.01	0.66	-0.23	-0.12	0.49	0.53	-0.56	0.44	-0.41	-0.19	0.65	0.39	-0.44	-0.64	0.51		-0.32	-0.44
Net Working Capital	-0.7	0.27	-0.85	-0.72	-0.79	-0.09	-0.74	-0.68	-0.46	-0.8	0.44	0.16	-0.44	-0.71	0.79	-0.26	0.53	0.9	-0.86	-0.36	0.52	0.6	-0.68	-0.32		0.41
Capital Stock	-0.42	0.05	-0.32	-0.52	-0.57	0.05	-0.42	-0.4	0.04	-0.3	0.07	-0.06	-0.84	-0.44	0.34	-0.05	0.18	0.52	-0.69	0.04	0.24	0.22	-0.28	-0.44	0.41

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Automatic Debt To Equity Historical Pattern

Today, most investors in Automatic Data Stock are looking for potential investment opportunities by analyzing not only static indicators but also various Automatic Data's growth ratios. Consistent increases or drops in fundamental ratios usually indicate a possible pattern that can be successfully translated into profits. However, when comparing two companies, knowing each company's debt to equity growth rates may not be enough to decide which company is a better investment. That's why investors frequently use a static breakdown of Automatic Data debt to equity as a starting point in their analysis.

Automatic Data Debt To Equity

Timeline

High Debt to Equity ratio typically indicates that a firm has been borrowing aggressively to finance its growth and as a result may experience a burden of additional interest expense. This may reduce earnings or future growth. On the other hand a small D/E ratio may indicate that a company is not taking enough advantage from financial leverage. Debt to Equity ratio measures how the company is leveraging borrowing against the capital invested by the owners.

Competition

Predict Automatic Data

Debt To Equity Over Time

Automatic Total Stockholder Equity

Total Stockholder Equity

4.3 Billion

At this time, Automatic Data's Total Stockholder Equity is relatively stable compared to the past year.

According to the company disclosure, Automatic Data Processing has a Debt To Equity of 1.395%. This is 98.15% lower than that of the Software sector and significantly higher than that of the Information Technology industry. The debt to equity for all United States stocks is 97.14% higher than that of the company.

Automatic Debt To Equity Peer Comparison

Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Automatic Data's direct or indirect competition against its Debt To Equity to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Automatic Data could also be used in its relative valuation, which is a method of valuing Automatic Data by comparing valuation metrics of similar companies.

Automatic Data is currently under evaluation in debt to equity category among its peers.

Automatic Data ESG Sustainability

Some studies have found that companies with high sustainability scores are getting higher valuations than competitors with lower social-engagement activities. While most ESG disclosures are voluntary and do not directly affect the long term financial condition, Automatic Data's sustainability indicators can be used to identify proper investment strategies using environmental, social, and governance scores that are crucial to Automatic Data's managers, analysts, and investors.

Environmental

Governance

Social

Automatic Fundamentals

	Return On Equity	0.87
	Return On Asset	0.0654
	Profit Margin	0.20 %
	Operating Margin	0.26 %
	Current Valuation	127.06 B
	Shares Outstanding	407.46 M
	Shares Owned By Insiders	0.12 %
	Shares Owned By Institutions	84.40 %
	Number Of Shares Shorted	5.21 M
	Price To Earning	35.60 X
	Price To Book	23.38 X
	Price To Sales	6.41 X
	Revenue	19.2 B
	Gross Profit	8.51 B
	EBITDA	5.8 B
	Net Income	3.75 B
	Cash And Equivalents	1.23 B
	Cash Per Share	2.97 X
	Total Debt	3.71 B
	Debt To Equity	1.40 %
	Current Ratio	0.97 X
	Book Value Per Share	13.12 X
	Cash Flow From Operations	4.16 B
	Short Ratio	3.13 X
	Earnings Per Share	9.36 X
	Price To Earnings To Growth	2.69 X
	Target Price	298.67
	Number Of Employees	64 K
	Beta	0.8
	Market Capitalization	125.06 B
	Total Asset	54.36 B
	Retained Earnings	23.62 B
	Working Capital	462.5 M
	Current Asset	3.68 B
	Current Liabilities	2 B
	Annual Yield	0.02 %
	Five Year Return	1.95 %
	Net Asset	54.36 B
	Last Dividend Paid	5.6

About Automatic Data Fundamental Analysis

The Macroaxis Fundamental Analysis modules help investors analyze Automatic Data Processing's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Automatic Data using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Automatic Data Processing based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.

Please read more on our fundamental analysis page.

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

0.82	DJCO	Daily Journal Corp	Pair Corr
0.8	AI	C3 Ai Inc Earnings Call This Week	Pair Corr
0.95	BL	Blackline	Pair Corr
0.69	DT	Dynatrace Holdings LLC	Pair Corr

Moving against Automatic Stock

0.61	VERB	VERB TECHNOLOGY PANY Tech Boost	Pair Corr
0.59	VTEX	VTEX	Pair Corr
0.35	DMAN	Innovativ Media Group	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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