Automatic Data Processing Stock Market Value
| ADP Stock | USD 244.08 0.23 0.09% |
| Symbol | Automatic |
Automatic Data Processing Price To Book Ratio
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 0.092 | Dividend Share 5.15 | Earnings Share 8.59 | Revenue Per Share 45.09 | Quarterly Revenue Growth 0.063 |
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.
Automatic Data 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Automatic Data's stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Automatic Data.
| 03/17/2024 |
| 04/16/2024 |
If you would invest 0.00 in Automatic Data on March 17, 2024 and sell it all today you would earn a total of 0.00 from holding Automatic Data Processing or generate 0.0% return on investment in Automatic Data over 30 days. Automatic Data is related to or competes with Cass Information, Civeo Corp, Network 1, Maximus, AZZ Incorporated, CBIZ, and Rentokil Initial. Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide More
Automatic Data Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Automatic Data's stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Automatic Data Processing upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8269 | |||
| Information Ratio | 0.006 | |||
| Maximum Drawdown | 4.79 | |||
| Value At Risk | (1.40) | |||
| Potential Upside | 1.37 |
Automatic Data Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Automatic Data's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Automatic Data's standard deviation. In reality, there are many statistical measures that can use Automatic Data historical prices to predict the future Automatic Data's volatility.| Risk Adjusted Performance | 0.0536 | |||
| Jensen Alpha | 0.0341 | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | 0.006 | |||
| Treynor Ratio | 0.1289 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Automatic Data's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Automatic Data Processing Backtested Returns
We consider Automatic Data very steady. Automatic Data Processing secures Sharpe Ratio (or Efficiency) of 0.0827, which signifies that the company had a 0.0827% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Automatic Data Processing, which you can use to evaluate the volatility of the firm. Please confirm Automatic Data's Downside Deviation of 0.8269, risk adjusted performance of 0.0536, and Mean Deviation of 0.6297 to double-check if the risk estimate we provide is consistent with the expected return of 0.0702%. Automatic Data has a performance score of 6 on a scale of 0 to 100. The firm shows a Beta (market volatility) of 0.45, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, Automatic Data's returns are expected to increase less than the market. However, during the bear market, the loss of holding Automatic Data is expected to be smaller as well. Automatic Data Processing right now shows a risk of 0.85%. Please confirm Automatic Data Processing semi variance, and the relationship between the maximum drawdown and accumulation distribution , to decide if Automatic Data Processing will be following its price patterns.
Auto-correlation | -0.48 |
Modest reverse predictability
Automatic Data Processing has modest reverse predictability. Overlapping area represents the amount of predictability between Automatic Data time series from 17th of March 2024 to 1st of April 2024 and 1st of April 2024 to 16th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Automatic Data Processing price movement. The serial correlation of -0.48 indicates that about 48.0% of current Automatic Data price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.48 | |
| Spearman Rank Test | -0.14 | |
| Residual Average | 0.0 | |
| Price Variance | 4.7 |
Automatic Data Processing lagged returns against current returns
Autocorrelation, which is Automatic Data stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Automatic Data's stock expected returns. We can calculate the autocorrelation of Automatic Data returns to help us make a trade decision. For example, suppose you find that Automatic Data has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Automatic Data regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Automatic Data stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Automatic Data stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Automatic Data stock over time.
Current vs Lagged Prices |
| Timeline |
Automatic Data Lagged Returns
When evaluating Automatic Data's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Automatic Data stock have on its future price. Automatic Data autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Automatic Data autocorrelation shows the relationship between Automatic Data stock current value and its past values and can show if there is a momentum factor associated with investing in Automatic Data Processing.
Regressed Prices |
| Timeline |
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
| 0.59 | LNZA | LanzaTech Global Financial Report 20th of May 2024 | PairCorr |
| 0.57 | VIRC | Virco Manufacturing Report 26th of April 2024 | PairCorr |
| 0.55 | DSS | DSS Inc Financial Report 21st of May 2024 | PairCorr |
| 0.53 | BE | Bloom Energy Corp Financial Report 14th of May 2024 | PairCorr |
| 0.41 | BR | Broadridge Financial Financial Report 7th of May 2024 | 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 Automatic Data Correlation, Automatic Data Volatility and Automatic Data Alpha and Beta module to complement your research on Automatic Data. 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 Stock Tickers module to use high-impact, comprehensive, and customizable stock tickers that can be easily integrated to any websites.
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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