Carlos Rodriguez - Automatic Data CEO and President and Director
| ADP Stock | USD 243.31 1.32 0.55% |
CEO
Mr. Carlos A. Rodriguez is President, Chief Executive Officer, Director of Automatic Data Processing, Inc. Prior to his appointment in November 2011 to President and Chief Executive Officer, he served as President and Chief Operating Officer from May 2011 to November 2011, and as President, Employer Services International National Account Services, ADP Canada, and GlobalView and Employer Services International, from March 2010 to May 2011. since 2011.
| Age | 60 |
| Tenure | 13 years |
| Phone | 973 974 5000 |
| Web | https://www.adp.com |
Carlos Rodriguez Latest Insider Activity
Tracking and analyzing the buying and selling activities of Carlos Rodriguez against Automatic Data stock is an integral part of due diligence when investing in Automatic Data. Carlos Rodriguez insider activity provides valuable insight into whether Automatic Data is net buyers or sellers over its current business cycle. Note, Automatic Data insiders must abide by specific rules, including filing SEC forms every time they buy or sell Automatic Data'sshares to prevent insider trading or benefiting illegally from material non-public information that their positions give them access to.
Carlos Rodriguez over a year ago Acquisition by Carlos Rodriguez of 51813 shares of Hf Foods subject to Rule 16b-3 |
Automatic Data Management Efficiency
The company has Return on Asset of 0.0532 % which means that on every $100 spent on assets, it made $0.0532 of profit. This is way below average. In the same way, it shows a return on shareholders' equity (ROE) of 0.9738 %, implying that it generated $0.9738 on every 100 dollars invested. Automatic Data's management efficiency ratios could be used to measure how well Automatic Data manages its routine affairs as well as how well it operates its assets and liabilities.Similar Executives
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Management Performance
| Return On Equity | 0.97 | ||||
| Return On Asset | 0.0532 |
Automatic Data Processing Leadership Team
Elected by the shareholders, the Automatic Data's board of directors comprises two types of representatives: Automatic Data inside directors who are chosen from within the company, and outside directors, selected externally and held independent of Automatic. The board's role is to monitor Automatic Data's management team and ensure that shareholders' interests are well served. Automatic Data's inside directors are responsible for reviewing and approving budgets prepared by upper management to implement core corporate initiatives and projects. On the other hand, Automatic Data's outside directors are responsible for providing unbiased perspectives on the board's policies.
| David Kwon, Chief VP | ||
| Edward Flynn, Vice President - Employer Services, Sales and Marketing | ||
| Douglas Politi, President - Added Value Services | ||
| Max Li, Global Officer | ||
| Maria Black, President - Employer Services - TotalSource | ||
| Brock Albinson, Principal Accounting Officer and Corporate Controller | ||
| Dermot OBrien, Chief HR Officer | ||
| John Jones, Independent Director | ||
| Joseph Timko, Chief Strategy Officer | ||
| Richard Clark, Independent Director | ||
| William Ready, Director | ||
| Michael Gregoire, Director | ||
| Michael Eberhard, Vice President Treasurer | ||
| Michael Bonarti, VP, General Counsel and Secretary | ||
| Vipul Nagrath, Global Officer | ||
| Donald Weinstein, Chief Strategy Officer | ||
| Linda Gooden, Independent Director | ||
| Thomas Perrotti, President - Major Account Services and ADP Canada | ||
| Ellen Alemany, Independent Director | ||
| Christian Greyenbuhl, Vice President Investor Relations | ||
| Kathleen Winters, CFO, Corporate Vice President | ||
| Joseph DeSilva, President Sales | ||
| Scott Powers, Director | ||
| Robert Hubbard, Independent Director | ||
| Thomas Lynch, Director | ||
| Deborah Dyson, Vice President - Client Experience and Continuous Improvement | ||
| Francine Katsoudas, Director | ||
| Mark Benjamin, President of Global Enterprise Solutions | ||
| Don McGuire, Chief Officer | ||
| Peter Bisson, Director | ||
| Allyce Hackmann, Vice Communications | ||
| Eric Fast, Independent Director | ||
| Sandra Wijnberg, Director | ||
| Dorothy Wisniowski, Vice President Assistant Corporate Secretary | ||
| Carlos Rodriguez, CEO and President and Director | ||
| Gus Blanchard, Chief Officer | ||
| Jan Siegmund, CFO | ||
| John Ayala, Vice President - Client Experience and Continuous Improvement | ||
| Stuart Sackman, VP of Global Product and Technology | ||
| Glenn Hubbard, Independent Director |
Automatic Stock Performance Indicators
The ability to make a profit is the ultimate goal of any investor. But to identify the right stock is not an easy task. Is Automatic Data a good investment? Although profit is still the single most important financial element of any organization, multiple performance indicators can help investors identify the equity that they will appreciate over time.
| Return On Equity | 0.97 | ||||
| Return On Asset | 0.0532 | ||||
| Profit Margin | 0.19 % | ||||
| Operating Margin | 0.26 % | ||||
| Current Valuation | 101.18 B | ||||
| Shares Outstanding | 410.79 M | ||||
| Shares Owned By Insiders | 0.11 % | ||||
| Shares Owned By Institutions | 83.67 % | ||||
| Number Of Shares Shorted | 4.56 M | ||||
| Price To Earning | 35.60 X |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Automatic Data in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Automatic Data's short interest history, or implied volatility extrapolated from Automatic Data options trading.
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
| 0.52 | VIRC | Virco Manufacturing Report 26th of April 2024 | PairCorr |
| 0.43 | BR | Broadridge Financial Financial Report 7th of May 2024 | PairCorr |
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.Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in Automatic Data Processing. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as signals in unemployment. Note that the Automatic Data Processing information on this page should be used as a complementary analysis to other Automatic Data's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
Complementary 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.
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Is Automatic Data's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? 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. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Automatic Data listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
The market value of Automatic Data Processing is measured differently than its book value, which is the value of Automatic that is recorded on the company's balance sheet. Investors also form their own opinion of Automatic Data's value that differs from its market value or its book value, called intrinsic value, which is Automatic Data's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Automatic Data's market value can be influenced by many factors that don't directly affect Automatic Data's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Automatic Data's value and its price as these two are different measures arrived at by different means. Investors typically determine if Automatic Data is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Automatic Data's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.