Automatic Data Processing Stock Price Patterns
| ADP Stock | USD 246.82 0.85 0.35% |
Momentum 51
Impartial
Oversold | Overbought |
Quarterly Earnings Growth 0.115 | EPS Estimate Next Quarter 3.2823 | EPS Estimate Current Year 10.9579 | EPS Estimate Next Year 11.924 | Wall Street Target Price 280.7143 |
Using Automatic Data hype-based prediction, you can estimate the value of Automatic Data Processing from the perspective of Automatic Data response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards Automatic Data using Automatic Data's stock options and short interest. It helps to benchmark the overall future attitude of investors towards Automatic using crowd psychology based on the activity and movement of Automatic Data's stock price.
Automatic Data Short Interest
An investor who is long Automatic Data may also wish to track short interest. As short interest increases, investors should be becoming more worried about Automatic Data and may potentially protect profits, hedge Automatic Data with its derivative instruments, or be ready for some potential downside.
200 Day MA 287.9771 | Short Percent 0.0203 | Short Ratio 3.31 | Shares Short Prior Month 7 M | 50 Day MA 257.8908 |
Automatic Data Processing Hype to Price Pattern
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.
Some investors profit by finding stocks that are overvalued or undervalued based on market sentiment. The correlation of Automatic Data's market sentiment to its price can help taders to make decisions based on the overall investors consensus about Automatic Data.
Automatic Data Implied Volatility | 0.43 |
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.
The fear of missing out, i.e., FOMO, can cause potential investors in Automatic Data to buy its stock at a price that has no basis in reality. In that case, they are not buying Automatic because the equity is a good investment, but because they need to do something to avoid the feeling of missing out. On the other hand, investors will often sell stocks at prices well below their value during bear markets because they need to stop feeling the pain of losing money.
Automatic Data after-hype prediction price | USD 246.65 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Prediction based on Rule 16 of the current Automatic contract
Based on the Rule 16, the options market is currently suggesting that Automatic Data Processing will have an average daily up or down price movement of about 0.0269% per day over the life of the 2026-03-20 option contract. With Automatic Data trading at USD 246.82, that is roughly USD 0.0663 . If you think that the market is fully incorporating Automatic Data's daily price movement you should consider acquiring Automatic Data Processing options at the current volatility level of 0.43%. But if you have an opposite viewpoint you should avoid it and even consider selling them.
Automatic | Build AI portfolio with Automatic Stock |
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 After-Hype Price Density Analysis
As far as predicting the price of Automatic Data at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Automatic Data or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of Automatic Data, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
Automatic Data Estimiated After-Hype Price Volatility
In the context of predicting Automatic Data's stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Automatic Data's historical news coverage. Automatic Data's after-hype downside and upside margins for the prediction period are 245.55 and 247.75, respectively. We have considered Automatic Data's daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
Automatic Data is very steady at this time. Analysis and calculation of next after-hype price of Automatic Data Processing is based on 3 months time horizon.
Automatic Data Stock Price Outlook Analysis
Have you ever been surprised when a price of a Company such as Automatic Data is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Automatic Data backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Automatic Data, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.05 | 1.10 | 0.17 | 0.08 | 10 Events / Month | 6 Events / Month | In about 10 days |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
246.82 | 246.65 | 0.07 |
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Automatic Data Hype Timeline
On the 1st of February Automatic Data Processing is traded for 246.82. The entity has historical hype elasticity of -0.17, and average elasticity to hype of competition of -0.08. Automatic is forecasted to decline in value after the next headline, with the price expected to drop to 246.65. The average volatility of media hype impact on the company price is about 32.74%. The price depreciation on the next news is expected to be -0.07%, whereas the daily expected return is presently at -0.05%. The volatility of related hype on Automatic Data is about 71.43%, with the expected price after the next announcement by competition of 246.74. About 87.0% of the company shares are held by institutions such as insurance companies. The company has Price/Earnings To Growth (PEG) ratio of 2.94. Automatic Data Processing recorded earning per share (EPS) of 10.4. The entity last dividend was issued on the 13th of March 2026. The firm had 1139:1000 split on the 1st of October 2014. Considering the 90-day investment horizon the next forecasted press release will be in about 10 days. Check out Automatic Data Basic Forecasting Models to cross-verify your projections.Automatic Data Related Hype Analysis
Having access to credible news sources related to Automatic Data's direct competition is more important than ever and may enhance your ability to predict Automatic Data's future price movements. Getting to know how Automatic Data's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Automatic Data may potentially react to the hype associated with one of its peers.
| HypeElasticity | NewsDensity | SemiDeviation | InformationRatio | PotentialUpside | ValueAt Risk | MaximumDrawdown | |||
| PAYX | Paychex | (0.23) | 9 per month | 0.00 | (0.21) | 2.32 | (3.16) | 6.16 | |
| PH | Parker Hannifin | 3.42 | 7 per month | 0.66 | 0.19 | 2.46 | (1.57) | 9.94 | |
| LMT | Lockheed Martin | (3.82) | 6 per month | 1.28 | 0.22 | 2.92 | (2.25) | 7.74 | |
| GD | General Dynamics | (3.32) | 8 per month | 1.40 | (0.03) | 1.99 | (2.23) | 7.72 | |
| TT | Trane Technologies plc | (8.35) | 9 per month | 1.49 | (0.01) | 2.26 | (2.74) | 7.87 | |
| MMM | 3M Company | 4.07 | 8 per month | 0.00 | (0.11) | 1.77 | (2.10) | 9.29 | |
| NOC | Northrop Grumman | (1.25) | 8 per month | 1.38 | 0.12 | 2.85 | (1.69) | 9.88 | |
| DE | Deere Company | (3.83) | 9 per month | 1.54 | 0.09 | 2.70 | (2.07) | 7.96 | |
| HON | Honeywell International | (0.51) | 6 per month | 0.96 | 0.11 | 2.22 | (1.93) | 5.31 | |
| UPS | United Parcel Service | (1.58) | 8 per month | 1.20 | 0.15 | 2.75 | (2.42) | 11.51 |
Automatic Data Additional Predictive Modules
Most predictive techniques to examine Automatic price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Automatic using various technical 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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Automatic Data Predictive Indicators
The successful prediction of Automatic Data stock price could yield a significant profit to investors. But is it possible? The efficient-market hypothesis suggests that all published stock prices of traded companies, such as Automatic Data Processing, already reflect all publicly available information. This academic statement is a fundamental principle of many financial and investing theories used today. However, the typical investor usually disagrees with a 'textbook' version of this hypothesis and continually tries to find mispriced stocks to increase returns. We use internally-developed statistical techniques to arrive at the intrinsic value of Automatic Data based on analysis of Automatic Data hews, social hype, general headline patterns, and widely used predictive technical indicators.
We also calculate exposure to Automatic Data's market risk, different technical and fundamental indicators, relevant financial multiples and ratios, and then comparing them to Automatic Data's related companies. | 2023 | 2024 | 2025 | 2026 (projected) | Dividend Yield | 0.0226 | 0.0191 | 0.0172 | 0.0148 | Price To Sales Ratio | 5.04 | 6.11 | 5.5 | 5.77 |
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
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.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.