Automatic Data (UK) Volatility Indicators True Range
| 0HJI Stock | 296.94 2.82 0.94% |
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The output start index for this execution was one with a total number of output elements of sixty. The True Range is a measure of Automatic Data Processing volatility developed by Welles Wilder.
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.| Cycle Indicators | ||
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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 volatility 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.
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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.Did you try this?
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Automatic Data Processing pair trading
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.Automatic Data Pair Trading
Automatic Data Processing Pair Trading Analysis
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.