Automatic Data Ownership
| ADP Stock | USD 296.18 0.05 0.02% |
Shares in Circulation | First Issued 1985-09-30 | Previous Quarter 410.6 M | Current Value 409.5 M | Avarage Shares Outstanding 528.5 M | Quarterly Volatility 73.6 M |
Automatic |
Automatic Stock Ownership Analysis
About 84.0% of the company shares are held by institutions such as insurance companies. The company has Price/Earnings To Growth (PEG) ratio of 2.69. Automatic Data Processing recorded earning per share (EPS) of 9.36. The entity last dividend was issued on the 14th of March 2025. The firm had 1139:1000 split on the 1st of October 2014. Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. The company was founded in 1949 and is headquartered in Roseland, New Jersey. Automatic Data operates under Staffing Employment Services classification in the United States and is traded on NASDAQ Exchange. It employs 60000 people. For more info on Automatic Data Processing please contact Carlos Rodriguez at 973 974 5000 or go to https://www.adp.com.Besides selling stocks to institutional investors, Automatic Data also allocates a substantial amount of its earnings to a pull of share-based compensation to be paid out to its employees, managers, executives, and members of the board of directors. Share-Based compensation (also sometimes called Stock-Based Compensation) is a way of paying different Automatic Data's stakeholders with equity in the business. It is typically used as a motivation factor for employees to contribute beyond their regular compensation (salary and bonus). It is also used as a tool to align Automatic Data's strategic interests with those of the company's shareholders. Shares issued to employees are usually subject to a vesting period before they are earned and sold.
Automatic Data Quarterly Liabilities And Stockholders Equity |
|
Automatic Data Insider Trades History
Less than 1% of Automatic Data Processing are currently held by insiders. Unlike Automatic Data's institutional investors, corporate insiders most likely have a limit on the maximum percentage of share ownership. This is done to align insiders' influence against Automatic Data's private investors even though both sides will benefit from rising prices or experience loss when the share price declines. The good rule to have in mind is that the maximum share ownership percentage of the corporate insiders should not surpass 25%. View all of Automatic Data's insider trades
Automatic Stock Institutional Investors
Have you ever been surprised when a price of an equity instrument such as Automatic Data is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Automatic Data Processing backward and forwards among themselves. Automatic Data's institutional investor refers to the entity that pools money to purchase Automatic Data's securities or originate loans. Institutional investors include commercial and private banks, credit unions, insurance companies, pension funds, hedge funds, endowments, and mutual funds. Operating companies that invest excess capital in these types of assets may also be included in the term and may influence corporate governance by exercising voting rights in their investments.
| Shares | Capital Research Global Investors | 2024-09-30 | 4.8 M | Bank Of America Corp | 2024-09-30 | 4.5 M | State Farm Mutual Automobile Ins Co | 2024-09-30 | 3.7 M | Amvescap Plc. | 2024-09-30 | 3.7 M | Legal & General Group Plc | 2024-09-30 | 3.5 M | Goldman Sachs Group Inc | 2024-09-30 | 3.4 M | Ameriprise Financial Inc | 2024-09-30 | 3.3 M | Ubs Asset Mgmt Americas Inc | 2024-09-30 | 3.2 M | Deutsche Bank Ag | 2024-09-30 | 2.9 M | Vanguard Group Inc | 2024-09-30 | 40.5 M | Blackrock Inc | 2024-09-30 | 35.9 M |
Automatic Data Processing Insider Trading Activities
Some recent studies suggest that insider trading raises the cost of capital for securities issuers and decreases overall economic growth. Trading by specific Automatic Data insiders, such as employees or executives, is commonly permitted as long as it does not rely on Automatic Data's material information that is not in the public domain. Local jurisdictions usually require such trading to be reported in order to monitor insider transactions. In many U.S. states, trading conducted by corporate officers, key employees, directors, or significant shareholders must be reported to the regulator or publicly disclosed, usually within a few business days of the trade. In these cases Automatic Data insiders are required to file a Form 4 with the U.S. Securities and Exchange Commission (SEC) when buying or selling shares of their own companies.
Automatic Data's latest congressional trading
Congressional trading in companies like Automatic Data Processing, is subject to rigorous scrutiny to prevent conflicts of interest and insider trading. This is governed by multiple SEC regulations which were established to foster transparency and deter members of Congress from leveraging non-public information for personal gain. This oversight helps maintain public trust and ensures that investments in Automatic Data by those in governmental positions are based on the same information available to the general public.
| 2024-10-16 | Representative Scott Franklin | Acquired $50K to $100K | Verify | ||
| 2024-10-15 | Representative C Scott Franklin | Acquired Under $15K | Verify | ||
| 2024-09-06 | Representative John James | Acquired Under $15K | Verify | ||
| 2024-09-02 | Representative John James | Acquired Under $15K | Verify | ||
| 2024-08-21 | Representative Jared Moskowitz | Acquired Under $15K | Verify | ||
| 2023-11-16 | Senator Tommy Tuberville | Acquired Under $15K | Verify | ||
| 2023-11-15 | Senator Tommy Tuberville | Acquired Under $15K | Verify | ||
| 2023-10-20 | Senator Pete Ricketts | Acquired $50K to $100K | Verify | ||
| 2016-03-02 | Senator John Hoeven | Acquired $50K to $100K | Verify |
Automatic Data Outstanding Bonds
Automatic Data issues bonds to finance its operations. Corporate bonds make up one of the largest components of the U.S. bond market, which is considered the world's largest securities market. Automatic Data Processing uses the proceeds from bond sales for a wide variety of purposes, including financing ongoing mergers and acquisitions, buying new equipment, investing in research and development, buying back their own stock, paying dividends to shareholders, and even refinancing existing debt. Most Automatic bonds can be classified according to their maturity, which is the date when Automatic Data Processing has to pay back the principal to investors. Maturities can be short-term, medium-term, or long-term (more than ten years). Longer-term bonds usually offer higher interest rates but may entail additional risks.
| AUTOMATIC DATA PROCESSING Corp BondUS053015AF05 | View | |
| AUTOMATIC DATA PROCESSING Corp BondUS053015AE30 | View | |
| AUTOMATIC DATA PROCESSING Corp BondUS053015AG87 | View | |
| International Game Technology Corp BondUS460599AD57 | View |
Automatic Data Corporate Filings
F4 | 15th of January 2025 The report filed by a party regarding the acquisition or disposition of a company's common stock, as well as derivative securities such as options, warrants, and convertible securities | ViewVerify |
F3 | 2nd of January 2025 The report used by insiders such as officers, directors, and major shareholders (beneficial owners holding more than 10% of any class of the company's equity securities) to declare their ownership of a company's stock | ViewVerify |
8K | 12th of November 2024 Report filed with the SEC to announce major events that shareholders should know about | ViewVerify |
10Q | 1st of November 2024 Quarterly performance report mandated by Securities and Exchange Commission (SEC), to be filed by publicly traded corporations | ViewVerify |
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
Moving against Automatic Stock
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.