Automatic Tangible Book Value Per Share from 2010 to 2024
ADP Stock | USD 241.89 0.14 0.06% |
Tangible Book Value Per Share | First Reported 2010-12-31 | Previous Quarter (0.38) | Current Value (0.36) | Quarterly Volatility 2.63403918 |
Check Automatic Data financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Automatic main balance sheet or income statement drivers, such as Depreciation And Amortization of 663.3 M, Interest Expense of 305.9 M or Selling General Administrative of 4.3 B, as well as many exotic indicators such as Price To Sales Ratio of 2.41, Dividend Yield of 0.0153 or PTB Ratio of 24.49. Automatic financial statements analysis is a perfect complement when working with Automatic Data Valuation or Volatility modules.
Automatic | Tangible Book Value Per Share |
Latest Automatic Data's Tangible Book Value Per Share Growth Pattern
Below is the plot of the Tangible Book Value Per Share of Automatic Data Processing over the last few years. It is Automatic Data's Tangible Book Value Per Share 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.
Tangible Book Value Per Share | 10 Years Trend |
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Tangible Book Value Per Share |
Timeline |
Automatic Tangible Book Value Per Share Regression Statistics
Arithmetic Mean | 2.94 | |
Geometric Mean | 2.09 | |
Coefficient Of Variation | 89.62 | |
Mean Deviation | 2.41 | |
Median | 4.61 | |
Standard Deviation | 2.63 | |
Sample Variance | 6.94 | |
Range | 7.0808 | |
R-Value | (0.58) | |
Mean Square Error | 4.99 | |
R-Squared | 0.33 | |
Significance | 0.02 | |
Slope | (0.34) | |
Total Sum of Squares | 97.13 |
Automatic Tangible Book Value Per Share History
About Automatic Data Financial Statements
There are typically three primary documents that fall into the category of financial statements. These documents include Automatic Data income statement, its balance sheet, and the statement of cash flows. Automatic Data investors use historical funamental indicators, such as Automatic Data's Tangible Book Value Per Share, to determine how well the company is positioned to perform in the future. Although Automatic Data investors may use each financial statement separately, they are all related. The changes in Automatic Data's assets and liabilities, for example, are also reflected in the revenues and expenses that we see on Automatic Data's income statement, which results in the company's gains or losses. Cash flows can provide more information regarding cash listed on a balance sheet, but not equivalent to net income shown on the income statement. We offer a historical overview of the basic patterns found on Automatic Data Financial Statements. Understanding these patterns can help to make the right decision on long term investment in Automatic Data. Please read more on our technical analysis and fundamental analysis pages.
Last Reported | Projected for Next Year | ||
Tangible Book Value Per Share | (0.38) | (0.36) |
Automatic Data Investors Sentiment
The influence of Automatic Data's investor sentiment on the probability of its price appreciation or decline could be a good factor in your decision-making process regarding taking a position in Automatic. The overall investor sentiment generally increases the direction of a stock movement in a one-year investment horizon. However, the impact of investor sentiment on the entire stock market does not have solid backing from leading economists and market statisticians.
Investor biases related to Automatic Data's public news can be used to forecast risks associated with an investment in Automatic. The trend in average sentiment can be used to explain how an investor holding Automatic can time the market purely based on public headlines and social activities around Automatic Data Processing. Please note that most equities that are difficult to arbitrage are affected by market sentiment the most.
Automatic Data's market sentiment shows the aggregated news analyzed to detect positive and negative mentions from the text and comments. The data is normalized to provide daily scores for Automatic Data's and other traded tickers. The bigger the bubble, the more accurate is the estimated score. Higher bars for a given day show more participation in the average Automatic Data's news discussions. The higher the estimated score, the more favorable is the investor's outlook on Automatic Data.
Automatic Data Implied Volatility | 37.62 |
Automatic Data's implied volatility exposes the market's sentiment of Automatic Data Processing stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if Automatic Data's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that Automatic Data stock will not fluctuate a lot when Automatic Data's options are near their expiration.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Automatic Data in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Automatic Data's short interest history, or implied volatility extrapolated from Automatic Data options trading.
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 against Automatic Stock
0.46 | BV | BrightView Holdings Fiscal Year End 21st of November 2024 | PairCorr |
0.45 | LZ | LegalZoom Financial Report 14th of May 2024 | PairCorr |
0.41 | NL | NL Industries | PairCorr |
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.Check out the analysis of Automatic Data Correlation against competitors. Note that the Automatic Data Processing information on this page should be used as a complementary analysis to other Automatic Data's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
Complementary 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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Is Automatic Data's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Automatic Data. If investors know Automatic will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Automatic Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Quarterly Earnings Growth 0.147 | Dividend Share 5.3 | Earnings Share 8.95 | Revenue Per Share 45.972 | Quarterly Revenue Growth 0.066 |
The market value of Automatic Data Processing is measured differently than its book value, which is the value of Automatic that is recorded on the company's balance sheet. Investors also form their own opinion of Automatic Data's value that differs from its market value or its book value, called intrinsic value, which is Automatic Data's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Automatic Data's market value can be influenced by many factors that don't directly affect Automatic Data's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Automatic Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Automatic Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Automatic Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.