Automatic Data Processing Stock Cycle Indicators Hilbert Transform Dominant Cycle Period

ADP Stock  USD 249.74  1.41  0.57%   
Automatic Data cycle indicators tool provides the execution environment for running the Hilbert Transform Dominant Cycle Period indicator and other technical functions against Automatic Data. Automatic Data value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of cycle indicators indicators. As with most other technical indicators, the Hilbert Transform Dominant Cycle Period indicator function is designed to identify and follow existing trends. Cycle Indicators are used by chartists in order to analyze variations of the instantaneous phase or amplitude of Automatic Data price series.

Indicator
The output start index for this execution was thirty-two with a total number of output elements of twenty-nine. The Hilbert Transform - Dominant Cycle Period indicator is used to generate in-phase and quadrature components of Automatic Data Processing price series in order to analyze variations of the instantaneous cycles.

Automatic Data Technical Analysis Modules

Most technical analysis of Automatic Data help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Automatic from various momentum indicators to cycle indicators. When you analyze Automatic charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.

About Automatic Data Predictive Technical Analysis

Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Automatic Data Processing. We use our internally-developed statistical techniques to arrive at the intrinsic value of Automatic Data Processing based on widely used predictive technical indicators. In general, we focus on analyzing Automatic Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Automatic Data's daily price indicators and compare them against related drivers, such as cycle indicators and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Automatic Data's intrinsic value. In addition to deriving basic predictive indicators for Automatic Data, we also check how macroeconomic factors affect Automatic Data price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
 2021 2022 2023 2024 (projected)
Price To Sales Ratio5.485.294.762.41
Price Earnings Ratio29.8326.6523.9817.23
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.
Hype
Prediction
LowEstimatedHigh
247.71248.43249.15
Details
Intrinsic
Valuation
LowRealHigh
221.13221.85273.16
Details
Naive
Forecast
LowNextHigh
253.55254.27254.99
Details
21 Analysts
Consensus
LowTargetHigh
236.54259.93288.52
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Automatic Data. Your research has to be compared to or analyzed against Automatic Data's peers to derive any actionable benefits. When done correctly, Automatic Data's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Automatic Data Processing.

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As an individual investor, you need to find a reliable way to track all your investment portfolios' performance accurately. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing you full analytical transparency into your positions, our tools can tell you how much better you can do without increasing your risk or reducing expected return.

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When determining whether Automatic Data Processing is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if Automatic Stock is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Automatic Data Processing Stock. Highlighted below are key reports to facilitate an investment decision about Automatic Data Processing Stock:
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 tightly coupled with the direction of predictive economic indicators such as signals in unemployment.
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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.

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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
0.092
Dividend Share
5.15
Earnings Share
8.6
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.