Automatic Data (UK) Performance

Automatic Data Relative Risk vs. Return Landscape

If you would invest  25,974  in Automatic Data Processing on October 31, 2025 and sell it today you would lose (911.00) from holding Automatic Data Processing or give up 3.51% of portfolio value over 90 days. Automatic Data Processing is generating negative expected returns and assumes 1.1373% volatility on return distribution over the 90 days horizon. Simply put, 10% of stocks are less volatile than Automatic, and 99% of all equity instruments are likely to generate higher returns than the company over the next 90 trading days.Assuming the 90 days trading horizon Automatic Data is expected to under-perform the market. In addition to that, the company is 1.51 times more volatile than its market benchmark. It trades about -0.05 of its total potential returns per unit of risk. The Dow Jones Industrial is currently generating roughly 0.07 per unit of volatility.

Automatic Data Target Price Odds to finish over Current Price

Assuming the 90 days trading horizon Automatic Data has a beta of 0.13. This suggests as returns on the market go up, Automatic Data average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Automatic Data Processing will be expected to be much smaller as well. Additionally Automatic Data Processing has a negative alpha, implying that the risk taken by holding this instrument is not justified. The company is significantly underperforming the Dow Jones Industrial.

Predictive Modules for Automatic Data

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Automatic Data Processing. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.

Hype Prediction Low Estimated High 249.50 250.63 251.76 Details

Intrinsic Valuation Low Real High 216.92 218.05 275.69 Details

Naive Forecast Low Next High 249.75 250.88 252.00 Details

Bollinger Band Projection (param) Lower Middle Band Upper 251.41 258.71 266.01 Details

Automatic Data Risk Indicators

For the most part, the last 10-20 years have been a very volatile time for the stock market. Automatic Data is not an exception. The market had few large corrections towards the Automatic Data's value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold Automatic Data Processing, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Automatic Data within the framework of very fundamental risk indicators.

Automatic Data Alerts and Suggestions

In today's market, stock alerts give investors the competitive edge they need to time the market and increase returns. Checking the ongoing alerts of Automatic Data for significant developments is a great way to find new opportunities for your next move. Suggestions and notifications for Automatic Data Processing can help investors quickly react to important events or material changes in technical or fundamental conditions and significant headlines that can affect investment decisions.

Automatic Data Price Density Drivers

Automatic Data Fundamentals Growth

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.