Automatic Data Processing Stock Price To Book

ADP Stock

USD 304.57 5.98 2.00%

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.

Short Long Term Debt Total Total Assets

As of 11/22/2024, Price To Book Ratio is likely to grow to 22.34.

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 Price To Book Analysis

Automatic Data's Price to Book (P/B) ratio is used to relate a company book value to its current market price. A high P/B ratio indicates that investors expect executives to generate more returns on their investments from a given set of assets. Book value is the accounting value of assets minus liabilities.

P/B

MV Per Share

BV Per Share

More About Price To Book | All Equity Analysis

Current Automatic Data Price To Book

22.75 X

Most of Automatic Data's fundamental indicators, such as Price To Book, 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 Price To Book 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 Price To Book. 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		0.61	0.72	-0.16	0.67	0.6	0.19	0.78	-0.63	-0.31	0.34	0.81	-0.73	0.52	-0.44	-0.78	0.84	0.6	-0.59	-0.65	0.79	0.56	-0.85	-0.34
Retained Earnings	0.95	0.31	0.61		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	0.72	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	0.67	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	0.6	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	-0.63	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	-0.31	-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	0.34	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	0.52	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	-0.78	-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	0.84	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	0.6	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	0.79	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	0.56	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	-0.34	-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 Price To Book 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 price to book 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 price to book as a starting point in their analysis.

Automatic Data Price To Book

Timeline

Price to Book ratio is mostly used in financial services industries where assets and liabilities are typically represented by dollars. Although low Price to Book ratio generally implies that the firm is undervalued, it is often a good indicator that the company may be in financial or managerial distress and should be investigated more carefully.

Competition

Predict Automatic Data

Price Book Value Ratio Over Time

Automatic Book Value Per Share

Book Value Per Share

6.13

At this time, Automatic Data's Book Value Per Share is relatively stable compared to the past year.

Based on the latest financial disclosure, Automatic Data Processing has a Price To Book of 22.7466 times. This is 285.54% higher than that of the Professional Services sector and significantly higher than that of the Industrials industry. The price to book for all United States stocks is 139.19% lower than that of the firm.

Automatic Price To Book 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 Price To Book 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 price to book 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	123.67 B
	Shares Outstanding	407.46 M
	Shares Owned By Insiders	0.12 %
	Shares Owned By Institutions	84.42 %
	Number Of Shares Shorted	6.51 M
	Price To Earning	35.60 X
	Price To Book	22.75 X
	Price To Sales	6.36 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	3.8 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	4.24 X
	Earnings Per Share	9.35 X
	Price To Earnings To Growth	2.69 X
	Target Price	298.67
	Number Of Employees	64 K
	Beta	0.8
	Market Capitalization	124.1 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

0.78	BV	BrightView Holdings	Pair Corr
0.75	DRVN	Driven Brands Holdings	Pair Corr

Moving against Automatic Stock

0.83	WHLM	Wilhelmina	Pair Corr
0.68	MLKN	MillerKnoll	Pair Corr
0.6	CVEO	Civeo Corp	Pair Corr
0.5	RTO	Rentokil Initial PLC	Pair Corr
0.47	AP	Ampco Pittsburgh	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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