Automatic Historical Balance Sheet
ADP Stock | USD 306.93 0.01 0% |
Trend analysis of Automatic Data Processing balance sheet accounts such as Short Long Term Debt Total of 3.9 B, Other Current Liabilities of 46.5 B or Total Current Liabilities of 47.3 B provides information on Automatic Data's total assets, liabilities, and equity, which is the actual value of Automatic Data Processing to its prevalent stockholders. By breaking down trends over time using Automatic Data balance sheet statements, investors will see what precisely the company owns and what it owes to creditors or other parties at the end of each accounting year.
Financial Statement Analysis is much more than just reviewing and examining Automatic Data Processing latest accounting reports to predict its past. Macroaxis encourages investors to analyze financial statements over time for various trends across multiple indicators and accounts to determine whether Automatic Data Processing is a good buy for the upcoming year.
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About Automatic Balance Sheet Analysis
Balance Sheet is a snapshot of the financial position of Automatic Data Processing at a specified time, usually calculated after every quarter, six months, or one year. Automatic Data Balance Sheet has two main parts: assets and liabilities. Liabilities are the debts or obligations of Automatic Data and are divided into current liabilities and long term liabilities. An asset, on the other hand, is anything of value that can be converted into cash and which Automatic currently owns. An asset can also be divided into two categories, current and non-current.
Automatic Data Balance Sheet Chart
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Total Assets
Total assets refers to the total amount of Automatic Data assets owned. Assets are items that have some economic value and are expended over time to create a benefit for the owner. These assets are usually recorded in Automatic Data Processing books under different categories such as cash, marketable securities, accounts receivable,prepaid expenses, inventory, fixed assets, intangible assets, other assets, marketable securities, accounts receivable, prepaid expenses and others. The total value of all owned resources that are expected to provide future economic benefits to the business, including cash, investments, accounts receivable, inventory, property, plant, equipment, and intangible assets.Total Current Liabilities
Total Current Liabilities is an item on Automatic Data balance sheet that include short term debt, accounts payable, accrued salaries payable, payroll taxes payable, accrued liabilities and other debts. Total Current Liabilities of Automatic Data Processing are important to investors because some useful performance ratios such as Current Ratio and Quick Ratio require Total Current Liabilities to be accurate. The total amount of liabilities that a company is expected to pay within one year, including debts, accounts payable, and other short-term financial obligations.Most accounts from Automatic Data's balance sheet are interrelated and interconnected. However, analyzing balance sheet accounts one by one will only give a small insight into Automatic Data Processing current financial condition. On the other hand, looking into the entire matrix of balance sheet accounts, and analyzing their relationships over time can provide a more complete picture of the company financial strength now and in the future. 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 closely tied with the direction of predictive economic indicators such as signals in unemployment. At this time, Automatic Data's Net Receivables is relatively stable compared to the past year. As of 12/01/2024, Common Stock Shares Outstanding is likely to grow to about 431.7 M, while Cash is likely to drop slightly above 1.5 B.
2021 | 2022 | 2023 | 2024 (projected) | Short and Long Term Debt Total | 3.5B | 6.8B | 3.7B | 3.9B | Total Assets | 63.1B | 51.0B | 54.4B | 57.1B |
Automatic Data balance sheet Correlations
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Automatic Data Account Relationship Matchups
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Automatic Data balance sheet Accounts
2019 | 2020 | 2021 | 2022 | 2023 | 2024 (projected) | ||
Total Assets | 39.2B | 48.8B | 63.1B | 51.0B | 54.4B | 57.1B | |
Short Long Term Debt Total | 2.3B | 3.3B | 3.5B | 6.8B | 3.7B | 3.9B | |
Other Current Liab | 28.8B | 37.7B | 54.6B | 38.6B | 44.3B | 46.5B | |
Total Current Liabilities | 30.1B | 38.1B | 55.2B | 42.8B | 45.1B | 47.3B | |
Total Stockholder Equity | 5.8B | 5.7B | 3.2B | 3.5B | 4.5B | 4.3B | |
Property Plant And Equipment Net | 1.2B | 1.1B | 1.1B | 1.1B | 1.1B | 723.2M | |
Net Debt | 440.5M | 753M | 2.1B | 1.3B | 791.9M | 831.5M | |
Retained Earnings | 18.4B | 19.5B | 20.7B | 22.1B | 23.6B | 24.8B | |
Cash | 1.9B | 2.6B | 1.4B | 2.1B | 2.9B | 1.5B | |
Non Current Assets Total | 7.6B | 8.0B | 8.3B | 8.8B | 8.8B | 7.8B | |
Non Currrent Assets Other | 2.9B | 3.3B | 3.3B | 4.0B | 4.1B | 4.6B | |
Cash And Short Term Investments | 1.9B | 2.6B | 1.5B | 2.1B | 2.9B | 1.6B | |
Net Receivables | 2.4B | 2.7B | 3.2B | 3.0B | 3.4B | 3.6B | |
Good Will | 2.3B | 2.3B | 2.3B | 2.3B | 2.4B | 1.9B | |
Common Stock Shares Outstanding | 432.7M | 428.1M | 421.1M | 415.7M | 412.2M | 431.7M | |
Liabilities And Stockholders Equity | 39.2B | 48.8B | 63.1B | 51.0B | 54.4B | 57.1B | |
Non Current Liabilities Total | 3.3B | 5.0B | 4.7B | 4.7B | 4.7B | 4.8B | |
Inventory | 26.7B | 34.9B | 49.6B | 1.0 | 1.15 | 1.09 | |
Other Current Assets | 506.2M | 35.4B | 50.2B | 743.9M | 39.2B | 41.2B | |
Other Stockholder Equity | (12.7B) | (13.9B) | (15.5B) | (16.4B) | (17.3B) | (16.5B) | |
Total Liab | 33.4B | 43.1B | 59.8B | 47.5B | 49.8B | 52.3B | |
Property Plant And Equipment Gross | 703M | 1.1B | 1.1B | 1.1B | 2.9B | 3.0B | |
Total Current Assets | 31.6B | 40.7B | 54.8B | 42.2B | 45.5B | 47.8B | |
Accumulated Other Comprehensive Income | (14.8M) | 10.6M | (2.0B) | (2.3B) | (1.8B) | (1.7B) | |
Short Term Debt | 1.0B | 23.5M | 232.7M | 3.8B | 478.7M | 506.5M | |
Intangible Assets | 1.2B | 1.2B | 1.3B | 1.3B | 1.3B | 1.1B | |
Accounts Payable | 102M | 141.1M | 110.2M | 96.8M | 100.6M | 137.4M | |
Short Term Investments | 0.0 | 10.4M | 32.7M | 14.7M | 384M | 231.6M | |
Other Liab | 1.9B | 1.7B | 1.3B | 1.4B | 1.2B | 1.2B | |
Other Assets | 2.9B | 3.3B | 3.5B | 4.0B | 1.0 | 0.95 | |
Long Term Debt | 1.0B | 3.0B | 3.0B | 3.0B | 3.0B | 3.1B | |
Treasury Stock | (14.1B) | (15.4B) | (17.3B) | (18.5B) | (16.6B) | (15.8B) | |
Property Plant Equipment | 703.9M | 1.1B | 1.1B | 681.4M | 783.6M | 809.7M | |
Current Deferred Revenue | 212.5M | 203.9M | 188.2M | 188.6M | 199.8M | 223.3M | |
Net Tangible Assets | 2.2B | 2.1B | (408.3M) | (173.9M) | (156.5M) | (148.7M) | |
Retained Earnings Total Equity | 18.4B | 19.5B | 20.7B | 22.1B | 25.4B | 17.1B | |
Capital Surpluse | 1.3B | 1.5B | 1.8B | 2.1B | 2.4B | 2.5B |
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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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.