Automatic Data Return On Asset vs. Net Income
| ADP Stock | USD 225.53 1.09 0.48% |
| Current Value | Last Year | Change From Last Year | 10 Year Trend | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Gross Profit Margin | 0.57 | 0.58 |
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| Net Profit Margin | 0.11 | 0.18 |
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| Operating Profit Margin | 0.16 | 0.24 |
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| Pretax Profit Margin | 0.16 | 0.23 |
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| Return On Assets | 0.0805 | 0.0879 |
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| Return On Equity | 0.62 | 0.59 |
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For Automatic Data profitability analysis, we use financial ratios and fundamental drivers that measure the ability of Automatic Data to generate income relative to revenue, assets, operating costs, and current equity. These fundamental indicators attest to how well Automatic Data Processing utilizes its assets to generate profit and value for its shareholders. The profitability module also shows relationships between Automatic Data's most relevant fundamental drivers. It provides multiple suggestions of what could affect the performance of Automatic Data Processing over time as well as its relative position and ranking within its peers.
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Automatic Data's Revenue Breakdown by Earning Segment
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Automatic Data Revenue Breakdown by Earning Segment
By analyzing Automatic Data's earnings estimates, investors can diagnose different trends across Automatic Data's analyst sentiment over time as well as compare current estimates against different timeframes.
Can Human Resource & Employment Services industry sustain growth momentum? Does Automatic have expansion opportunities? 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. Determining accurate worth demands scrutiny of both present operating results and projected expansion capacity. Evaluating Automatic Data demands reviewing these metrics collectively while recognizing certain factors exert disproportionate influence.
Quarterly Earnings Growth 0.115 | Dividend Share 6.32 | Earnings Share 10.35 | Revenue Per Share | Quarterly Revenue Growth 0.062 |
Understanding Automatic Data Processing requires distinguishing between market price and book value, where the latter reflects Automatic's accounting equity. The concept of intrinsic value - what Automatic Data's is actually worth based on fundamentals - guides informed investors toward better entry and exit points. Market participants employ diverse analytical approaches to determine fair value and identify buying opportunities when prices dip below calculated worth. Market sentiment, economic cycles, and investor behavior can push Automatic Data's price substantially above or below its fundamental value.
Understanding that Automatic Data's value differs from its trading price is crucial, as each reflects different aspects of the company. Evaluating whether Automatic Data represents a sound investment requires analyzing earnings trends, revenue growth, technical signals, industry dynamics, and expert forecasts. In contrast, Automatic Data's trading price reflects the actual exchange value where willing buyers and sellers reach mutual agreement.
Automatic Data Processing Net Income vs. Return On Asset Fundamental Analysis
Comparative valuation techniques use various fundamental indicators to help in determining Automatic Data's current stock value. Our valuation model uses many indicators to compare Automatic Data value to that of its competitors to determine the firm's financial worth. Automatic Data Processing is rated fourth in return on asset category among its peers. It is number one stock in net income category among its peers making up about 86,617,834,395 of Net Income per Return On Asset. At this time, Automatic Data's Net Income is relatively stable compared to the past year. Comparative valuation analysis is a catch-all technique that is used if you cannot value Automatic Data by discounting back its dividends or cash flows. It compares the stock's price multiples to nearest competition to determine if the stock is relatively undervalued or overvalued.Automatic Net Income vs. Return On Asset
Return on Asset or ROA shows how effective is the management of the company in generating income from utilizing all of the assets at their disposal. It is a useful ratio to evaluate the performance of different departments of a company as well as to understand management performance over time.
Automatic Data |
| = | 0.0471 |
Return on Asset measures overall efficiency of a company in generating profits from its total assets. It is expressed as the percentage of profits earned per dollar of Asset. A low ROA typically means that a company is asset-intensive and therefore will needs more money to continue generating revenue in the future.
Net income is the profit of a company for the reporting period, which is derived after taking revenues and gains and subtracting all expenses and losses. Net income is one of the most-watched numbers by money managers as well as individual investors.
Automatic Data |
| = | 4.08 B |
Because income is reported on the Income Statement of a company and is measured in dollars some investors prefer to use Profit Margin, which measures income as a percentage of sales.
Automatic Net Income Comparison
Automatic Data is currently under evaluation in net income category among its peers.
Automatic Data Profitability Projections
The most important aspect of a successful company is its ability to generate a profit. For investors in Automatic Data, profitability is also one of the essential criteria for including it into their portfolios because, without profit, Automatic Data will eventually generate negative long term returns. The profitability progress is the general direction of Automatic Data's change in net profit over the period of time. It can combine multiple indicators of Automatic Data, where stable trends show no significant progress. An accelerating trend is seen as positive, while a decreasing one is unfavorable. A rising trend means that profits are rising, and operational efficiency may be rising as well. A decreasing trend is a sign of poor performance and may indicate upcoming losses.
| Last Reported | Projected for Next Year | ||
| Accumulated Other Comprehensive Income | -795.1 M | -755.3 M | |
| Operating Income | 6.2 B | 6.5 B | |
| Income Before Tax | 6.1 B | 6.4 B | |
| Total Other Income Expense Net | -91.6 M | -87 M | |
| Net Income | 4.7 B | 4.9 B | |
| Income Tax Expense | 1.4 B | 1.5 B | |
| Net Income Applicable To Common Shares | 3.9 B | 4.1 B | |
| Net Income From Continuing Ops | 4.7 B | 2.4 B | |
| Non Operating Income Net Other | 165.2 M | 173.4 M | |
| Net Interest Income | -156.9 M | -149 M | |
| Interest Income | 367.4 M | 263.6 M | |
| Change To Netincome | 335.6 M | 211.1 M | |
| Net Income Per Share | 9.02 | 9.47 | |
| Income Quality | 1.39 | 1.46 | |
| Net Income Per E B T | 0.69 | 0.56 |
Automatic Profitability Driver Comparison
Profitability drivers are factors that can directly affect your investment outlook on Automatic Data. Investors often realize that things won't turn out the way they predict. There are maybe way too many unforeseen events and contingencies during the holding period of Automatic Data position where the market behavior may be hard to predict, tax policy changes, gold or oil price hikes, calamities change, and many others. The question is, are you prepared for these unexpected events? Although some of these situations are obviously beyond your control, you can still follow the important profit indicators to know where you should focus on when things like this occur. Below are some of the Automatic Data's important profitability drivers and their relationship over time.
Automatic Data Earnings Estimation Breakdown
The calculation of Automatic Data's earning per share is based on the data from the past 12 consecutive months, used for reporting the company's financial figures. The next projected EPS of Automatic Data is estimated to be 2.74145 with the future projection ranging from a low of 2.7325 to a high of 2.7575. Please be aware that this consensus of annual earnings estimates for Automatic Data Processing is based on EPS before non-recurring items and includes expenses related to employee stock options.Last Reported EPS
2.73 Lowest | Expected EPS | 2.76 Highest |
Automatic Data Earnings Projection Consensus
Suppose the current estimates of Automatic Data's value are higher than the current market price of the Automatic Data stock. In this case, investors may conclude that Automatic Data is overpriced and will exhibit bullish sentiment. On the other hand, if the present value is lower than the stock price, analysts may conclude that the market undervalues the equity. These scenarios may suggest that the market is not as efficient as it should be at the estimation time, and Automatic Data's stock will quickly adjusts to the new information provided by the consensus estimate.
| Number of Analysts | Historical Accuracy | Last Reported EPS | Estimated EPS for 30th of June 2026 | Current EPS (TTM) | |
| 17 | 94.61% | 0.0 | 2.74145 | 10.35 |
Automatic Data Earnings History
Earnings estimate consensus by Automatic Data Processing analysts from Wall Street is used by the market to judge Automatic Data's stock performance. Investors also use these earnings estimates to evaluate and project the stock performance into the future in order to make their investment decisions. However, we suggest analyzing not only Automatic Data's upcoming profit reports and earnings-per-share forecasts but also comparing them to our different valuation methods.Automatic Data Quarterly Gross Profit |
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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 Earnings per Share Projection vs Actual
Actual Earning per Share of Automatic Data refers to what the company shows during its earnings calls or quarterly reports. The Expected EPS is what analysts covering Automatic Data Processing predict the company's earnings will be in the future. The higher the earnings per share of Automatic Data, the better is its profitability. While calculating the Earning per Share, we use the weighted ratio, as the number of shares outstanding can change over time.Automatic Data Estimated Months Earnings per Share
For an investor who is primarily interested in generating an income out of investing in entities such as Automatic Data, the EPS ratio can tell if the company is intending to increase its current dividend. Although EPS is an essential tool for investors, it should not be used in isolation. EPS of Automatic Data should always be considered in relation to other companies to make a more educated investment decision.Automatic Quarterly Analyst Estimates and Surprise Metrics
Earnings surprises can significantly impact Automatic Data's stock price both in the short term and over time. Negative earnings surprises usually result in a price decline. However, it has been seen that positive earnings surprises lead to an immediate rise in a stock's price and a gradual increase over time. This is why we often hear news about some companies beating earning projections. Financial analysts spend a large amount of time predicting earnings per share (EPS) along with other important future indicators. Many analysts use forecasting models, management guidance, and additional fundamental information to derive an EPS estimate.
| Reported | Fiscal Date | Estimated EPS | Reported EPS | Surprise | |||
|---|---|---|---|---|---|---|---|
null | null | null | null | null | 0 | ||
2026-01-28 | 2025-12-31 | 2.57 | 2.62 | 0.05 | 1 | ||
2025-10-29 | 2025-09-30 | 2.45 | 2.49 | 0.04 | 1 | ||
2025-07-30 | 2025-06-30 | 2.23 | 2.26 | 0.03 | 1 | ||
2025-04-30 | 2025-03-31 | 2.97 | 3.06 | 0.09 | 3 | ||
2025-01-29 | 2024-12-31 | 2.3 | 2.35 | 0.05 | 2 | ||
2024-10-30 | 2024-09-30 | 2.21 | 2.33 | 0.12 | 5 | ||
2024-07-31 | 2024-06-30 | 2.06 | 2.09 | 0.03 | 1 | ||
2024-05-01 | 2024-03-31 | 2.79 | 2.88 | 0.09 | 3 | ||
2024-01-31 | 2023-12-31 | 2.1 | 2.13 | 0.03 | 1 | ||
2023-10-25 | 2023-09-30 | 2.03 | 2.08 | 0.05 | 2 | ||
2023-07-26 | 2023-06-30 | 1.83 | 1.89 | 0.06 | 3 | ||
2023-04-26 | 2023-03-31 | 2.45 | 2.52 | 0.07 | 2 | ||
2023-01-25 | 2022-12-31 | 1.94 | 1.96 | 0.02 | 1 | ||
2022-10-26 | 2022-09-30 | 1.8 | 1.86 | 0.06 | 3 | ||
2022-07-27 | 2022-06-30 | 1.46 | 1.5 | 0.04 | 2 | ||
2022-04-27 | 2022-03-31 | 2.08 | 2.21 | 0.13 | 6 | ||
2022-01-26 | 2021-12-31 | 1.63 | 1.65 | 0.02 | 1 | ||
2021-10-27 | 2021-09-30 | 1.49 | 1.65 | 0.16 | 10 | ||
2021-07-28 | 2021-06-30 | 1.14 | 1.2 | 0.06 | 5 | ||
2021-04-28 | 2021-03-31 | 1.82 | 1.89 | 0.07 | 3 | ||
2021-01-27 | 2020-12-31 | 1.29 | 1.52 | 0.23 | 17 | ||
2020-10-28 | 2020-09-30 | 0.98 | 1.41 | 0.43 | 43 | ||
2020-07-29 | 2020-06-30 | 0.96 | 1.14 | 0.18 | 18 | ||
2020-04-29 | 2020-03-31 | 1.89 | 1.92 | 0.03 | 1 | ||
2020-01-29 | 2019-12-31 | 1.45 | 1.52 | 0.07 | 4 | ||
2019-10-30 | 2019-09-30 | 1.33 | 1.34 | 0.01 | 0 | ||
2019-07-31 | 2019-06-30 | 1.13 | 1.14 | 0.01 | 0 | ||
2019-05-01 | 2019-03-31 | 1.69 | 1.77 | 0.08 | 4 | ||
2019-01-30 | 2018-12-31 | 1.18 | 1.34 | 0.16 | 13 | ||
2018-10-31 | 2018-09-30 | 1.11 | 1.2 | 0.09 | 8 | ||
2018-08-01 | 2018-06-30 | 0.9 | 0.92 | 0.02 | 2 | ||
2018-05-02 | 2018-03-31 | 1.44 | 1.52 | 0.08 | 5 | ||
2018-01-31 | 2017-12-31 | 0.9 | 0.99 | 0.09 | 10 | ||
2017-11-02 | 2017-09-30 | 0.85 | 0.91 | 0.06 | 7 | ||
2017-07-27 | 2017-06-30 | 0.67 | 0.66 | -0.01 | 1 | ||
2017-05-03 | 2017-03-31 | 1.23 | 1.31 | 0.08 | 6 | ||
2017-02-01 | 2016-12-31 | 0.81 | 0.87 | 0.06 | 7 | ||
2016-11-02 | 2016-09-30 | 0.76 | 0.86 | 0.1 | 13 | ||
2016-07-28 | 2016-06-30 | 0.67 | 0.69 | 0.02 | 2 | ||
2016-04-28 | 2016-03-31 | 1.18 | 1.17 | -0.01 | 0 | ||
2016-02-03 | 2015-12-31 | 0.72 | 0.72 | 0.0 | 0 | ||
2015-10-28 | 2015-09-30 | 0.65 | 0.68 | 0.03 | 4 | ||
2015-07-30 | 2015-06-30 | 0.59 | 0.55 | -0.04 | 6 | ||
2015-04-30 | 2015-03-31 | 1.02 | 1.04 | 0.02 | 1 | ||
2015-02-04 | 2014-12-31 | 0.68 | 0.7 | 0.02 | 2 | ||
2014-10-29 | 2014-09-30 | 0.6 | 0.62 | 0.02 | 3 | ||
2014-07-31 | 2014-06-30 | 0.63 | 0.63 | 0.0 | 0 | ||
2014-04-30 | 2014-03-31 | 1.08 | 1.06 | -0.02 | 1 | ||
2014-02-05 | 2013-12-31 | 0.77 | 0.8 | 0.03 | 3 | ||
2013-10-30 | 2013-09-30 | 0.66 | 0.68 | 0.02 | 3 | ||
2013-08-01 | 2013-06-30 | 0.57 | 0.55 | -0.02 | 3 | ||
2013-05-03 | 2013-03-31 | 0.98 | 0.99 | 0.01 | 1 | ||
2013-02-05 | 2012-12-31 | 0.71 | 0.72 | 0.01 | 1 | ||
2012-11-01 | 2012-09-30 | 0.62 | 0.62 | 0.0 | 0 | ||
2012-08-01 | 2012-06-30 | 0.53 | 0.53 | 0.0 | 0 | ||
2012-05-01 | 2012-03-31 | 0.91 | 0.92 | 0.01 | 1 | ||
2012-01-25 | 2011-12-31 | 0.68 | 0.68 | 0.0 | 0 | ||
2011-10-26 | 2011-09-30 | 0.61 | 0.61 | 0.0 | 0 | ||
2011-07-28 | 2011-06-30 | 0.49 | 0.48 | -0.01 | 2 | ||
2011-05-02 | 2011-03-31 | 0.85 | 0.85 | 0.0 | 0 | ||
2011-01-26 | 2010-12-31 | 0.61 | 0.62 | 0.01 | 1 | ||
2010-10-27 | 2010-09-30 | 0.53 | 0.56 | 0.03 | 5 | ||
2010-07-29 | 2010-06-30 | 0.42 | 0.42 | 0.0 | 0 | ||
2010-04-27 | 2010-03-31 | 0.78 | 0.79 | 0.01 | 1 | ||
2010-02-02 | 2009-12-31 | 0.57 | 0.6 | 0.03 | 5 | ||
2009-11-04 | 2009-09-30 | 0.5 | 0.56 | 0.06 | 12 | ||
2009-07-30 | 2009-06-30 | 0.45 | 0.45 | 0.0 | 0 | ||
2009-05-05 | 2009-03-31 | 0.8 | 0.8 | 0.0 | 0 | ||
2009-02-03 | 2008-12-31 | 0.56 | 0.59 | 0.03 | 5 | ||
2008-11-03 | 2008-09-30 | 0.5 | 0.54 | 0.04 | 8 | ||
2008-07-31 | 2008-06-30 | 0.41 | 0.42 | 0.01 | 2 | ||
2008-05-01 | 2008-03-31 | 0.75 | 0.77 | 0.02 | 2 | ||
2008-02-01 | 2007-12-31 | 0.53 | 0.55 | 0.02 | 3 | ||
2007-10-30 | 2007-09-30 | 0.43 | 0.45 | 0.02 | 4 | ||
2007-07-31 | 2007-06-30 | 0.36 | 0.35 | -0.01 | 2 | ||
2007-05-01 | 2007-03-31 | 0.63 | 0.65 | 0.02 | 3 | ||
2007-02-06 | 2006-12-31 | 0.51 | 0.51 | 0.0 | 0 | ||
2006-10-31 | 2006-09-30 | 0.43 | 0.43 | 0.0 | 0 | ||
2006-08-02 | 2006-06-30 | 0.46 | 0.44 | -0.02 | 4 | ||
2006-04-28 | 2006-03-31 | 0.62 | 0.61 | -0.01 | 1 | ||
2006-01-25 | 2005-12-31 | 0.45 | 0.44 | -0.01 | 2 | ||
2005-10-26 | 2005-09-30 | 0.35 | 0.35 | 0.0 | 0 | ||
2005-07-26 | 2005-06-30 | 0.44 | 0.44 | 0.0 | 0 | ||
2005-04-21 | 2005-03-31 | 0.57 | 0.57 | 0.0 | 0 | ||
2005-01-21 | 2004-12-31 | 0.42 | 0.42 | 0.0 | 0 | ||
2004-10-25 | 2004-09-30 | 0.33 | 0.35 | 0.02 | 6 | ||
2004-07-27 | 2004-06-30 | 0.35 | 0.36 | 0.01 | 2 | ||
2004-04-22 | 2004-03-31 | 0.5 | 0.5 | 0.0 | 0 | ||
2004-01-22 | 2003-12-31 | 0.37 | 0.38 | 0.01 | 2 | ||
2003-10-17 | 2003-09-30 | 0.29 | 0.32 | 0.03 | 10 | ||
2003-07-29 | 2003-06-30 | 0.38 | 0.36 | -0.02 | 5 | ||
2003-04-17 | 2003-03-31 | 0.52 | 0.54 | 0.02 | 3 | ||
2003-01-15 | 2002-12-31 | 0.43 | 0.43 | 0.0 | 0 | ||
2002-10-17 | 2002-09-30 | 0.34 | 0.34 | 0.0 | 0 | ||
2002-07-17 | 2002-06-30 | 0.47 | 0.46 | -0.01 | 2 | ||
2002-04-15 | 2002-03-31 | 0.55 | 0.56 | 0.01 | 1 | ||
2002-01-17 | 2001-12-31 | 0.41 | 0.42 | 0.01 | 2 | ||
2001-10-17 | 2001-09-30 | 0.32 | 0.31 | -0.01 | 3 | ||
2001-08-13 | 2001-06-30 | 0.41 | 0.4 | -0.01 | 2 | ||
2001-04-16 | 2001-03-31 | 0.48 | 0.49 | 0.01 | 2 | ||
2001-01-17 | 2000-12-31 | 0.36 | 0.36 | 0.0 | 0 | ||
2000-10-13 | 2000-09-30 | 0.27 | 0.27 | 0.0 | 0 | ||
2000-08-14 | 2000-06-30 | 0.35 | 0.35 | 0.0 | 0 | ||
2000-04-18 | 2000-03-31 | 0.41 | 0.42 | 0.01 | 2 | ||
2000-01-18 | 1999-12-31 | 0.32 | 0.31 | -0.01 | 3 | ||
1999-10-14 | 1999-09-30 | 0.23 | 0.23 | 0.0 | 0 | ||
1999-08-10 | 1999-06-30 | 0.33 | 0.3 | -0.03 | 9 | ||
1999-04-15 | 1999-03-31 | 0.35 | 0.37 | 0.02 | 5 | ||
1999-01-14 | 1998-12-31 | 0.28 | 0.27 | -0.01 | 3 | ||
1998-10-13 | 1998-09-30 | 0.2 | 0.2 | 0.0 | 0 | ||
1998-08-13 | 1998-06-30 | 0.27 | 0.27 | 0.0 | 0 | ||
1998-04-15 | 1998-03-31 | 0.32 | 0.31 | -0.01 | 3 | ||
1998-01-16 | 1997-12-31 | 0.25 | 0.25 | 0.0 | 0 | ||
1997-10-14 | 1997-09-30 | 0.19 | 0.18 | -0.01 | 5 | ||
1997-08-20 | 1997-06-30 | 0.24 | 0.24 | 0.0 | 0 | ||
1997-04-14 | 1997-03-31 | 0.29 | 0.28 | -0.01 | 3 | ||
1997-01-16 | 1996-12-31 | 0.22 | 0.22 | 0.0 | 0 | ||
1996-10-11 | 1996-09-30 | 0.17 | 0.16 | -0.01 | 5 | ||
1996-08-14 | 1996-06-30 | 0.21 | 0.21 | 0.0 | 0 | ||
1996-04-11 | 1996-03-31 | 0.25 | 0.25 | 0.0 | 0 |
Use Automatic Data in 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.Use Investing Themes to Complement your Automatic Data position
In addition to having Automatic Data in your portfolios, you can quickly add positions using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your investment opportunity, you can then find an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility.Did You Try This Idea?
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Cannabis
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You can either use a buy-and-hold strategy to lock in the entire theme or actively trade it to take advantage of the short-term price volatility of individual constituents. Macroaxis can help you discover thousands of investment opportunities in different asset classes. In addition, you can partner with us for reliable portfolio optimization as you plan to utilize Cannabis Theme or any other thematic opportunities.
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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.