Automatic Net Current Asset Value from 2010 to 2024

ADP Stock  USD 304.67  0.48  0.16%   
Automatic Data Net Current Asset Value yearly trend continues to be relatively stable with very little volatility. Net Current Asset Value is likely to drop to 0.00. At this time, Automatic Data's Cost Of Revenue is relatively stable compared to the past year. As of 11/25/2024, Total Operating Expenses is likely to grow to about 8.1 B, though Total Other Income Expense Net is likely to grow to (99.7 M). . View All Fundamentals
 
Net Current Asset Value  
First Reported
2010-12-31
Previous Quarter
0.0
Current Value
0.0
Quarterly Volatility
0.0
 
Credit Downgrade
 
Yuan Drop
 
Covid
Check Automatic Data financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Automatic Data's main balance sheet or income statement drivers, such as Depreciation And Amortization of 323.3 M, Interest Expense of 379.5 M or Selling General Administrative of 2 B, as well as many indicators such as Price To Sales Ratio of 5.29, Dividend Yield of 0.0154 or PTB Ratio of 22.34. Automatic financial statements analysis is a perfect complement when working with Automatic Data Valuation or Volatility modules.
  
Check out the analysis of Automatic Data Correlation against competitors.

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 together with Automatic Stock

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Moving against Automatic Stock

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  0.48MMS MaximusPairCorr
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.
Pair CorrelationCorrelation Matching

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.