Automatic Historical Cash Flow
| ADP Stock | USD 306.93 0.01 0% |
Analysis of Automatic Data cash flow over time is an excellent tool to project Automatic Data Processing future capital expenditures as well as to predict the amount of cash needed to cover cost of sales, R&D expenses or production expansions. Investors should almost always look for trends in cash flow indicators such as Free Cash Flow of 3.8 B or Begin Period Cash Flow of 9.2 B as it is a great indicator of Automatic Data ability to facilitate future growth, repay debt on time or pay out dividends.
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 Cash Flow Analysis
The Cash Flow Statement is a financial statement that shows how changes in Automatic balance sheet and income statement accounts affect cash and cash equivalents. It breaks the analysis down to operating, investing, and financing activities. One of the most critical aspects of the cash flow statement is liquidity, which is the degree to which Automatic's non-liquid assets can be easily converted into cash.
Automatic Data Cash Flow Chart
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Free Cash Flow
The amount of cash a company generates after accounting for cash outflows to support operations and maintain its capital assets.Begin Period Cash Flow
The amount of cash a company has at the beginning of a financial reporting period. It serves as the starting point for calculating the period's cash flow from operations, investing, and financing activities.Capital Expenditures
Capital Expenditures are funds used by Automatic Data Processing to acquire physical assets such as property, industrial buildings or equipment. This type of outlay is used by management to increase the scope of Automatic Data operations. These expenditures can include everything from repairing an office equipment, building a brand new facility, or writing new software.Net Income
Net income is one of the most important fundamental items in finance. It plays a large role in Automatic Data Processing financial statement analysis. It represents the amount of money remaining after all of Automatic Data Processing operating expenses, interest, taxes and preferred stock dividends have been deducted from a company total revenue.Most accounts from Automatic Data's cash flow statement are interrelated and interconnected. However, analyzing cash flow statement 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 cash flow statement 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 Other Non Cash Items is relatively stable compared to the past year. As of 11/30/2024, Change To Liabilities is likely to grow to about 233.3 M, while Depreciation is likely to drop slightly above 340.5 M.
Automatic Data cash flow statement Correlations
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Automatic Data Account Relationship Matchups
High Positive Relationship
High Negative Relationship
Automatic Data cash flow statement Accounts
| 2019 | 2020 | 2021 | 2022 | 2023 | 2024 (projected) | ||
| Sale Purchase Of Stock | (1.0B) | (1.4B) | (2.0B) | (1.1B) | (1.2B) | (1.2B) | |
| Change In Cash | 257.4M | 6.1B | 9.6B | (14.0B) | 1.3B | 1.4B | |
| Free Cash Flow | 2.4B | 2.6B | 2.5B | 3.6B | 3.6B | 3.8B | |
| Change In Working Capital | (1.1B) | (937.4M) | (1.6B) | (938.7M) | (1.4B) | (1.3B) | |
| Begin Period Cash Flow | 6.8B | 7.1B | 13.1B | 22.8B | 8.8B | 9.2B | |
| Other Cashflows From Financing Activities | (4.4B) | 8.4B | 17.2B | (12.7B) | 1.1B | 1.1B | |
| Depreciation | 480M | 510.7M | 515.1M | 549.3M | 561.9M | 340.5M | |
| Dividends Paid | 1.5B | (1.6B) | (1.7B) | (1.9B) | (2.2B) | (2.1B) | |
| Capital Expenditures | 616.4M | 505.9M | 553.4M | 571.6M | 563.4M | 326.2M | |
| Total Cash From Operating Activities | 3.0B | 3.1B | 3.1B | 4.2B | 4.2B | 4.4B | |
| Net Income | 2.5B | 2.6B | 2.9B | 3.4B | 3.8B | 3.9B | |
| Total Cash From Financing Activities | (5.9B) | 6.4B | 13.7B | (15.7B) | (1.4B) | (1.4B) | |
| End Period Cash Flow | 7.1B | 13.1B | 22.8B | 8.8B | 10.1B | 10.6B | |
| Other Non Cash Items | 1.0B | 997.3M | 1.0B | 1.0B | 1.1B | 1.1B | |
| Other Cashflows From Investing Activities | (414.3M) | (308.5M) | (356.5M) | (397.7M) | (357.9M) | (340.0M) | |
| Change To Liabilities | (107.4M) | 36.9M | (16.4M) | 246.9M | 222.2M | 233.3M | |
| Total Cashflows From Investing Activities | 3.2B | (3.5B) | (7.0B) | (2.5B) | (2.3B) | (2.2B) | |
| Stock Based Compensation | 130.8M | 175.3M | 201.7M | 220.4M | 243.5M | 255.7M | |
| Change To Account Receivables | (113.8M) | (339.8M) | (486.5M) | 129.2M | (483.7M) | (459.5M) | |
| Change To Inventory | 107.7M | 266M | (77.5M) | (938.7M) | (1.1B) | (1.0B) | |
| Investments | 3.7B | (3.0B) | (6.5B) | (2.5B) | (1.4B) | (1.5B) | |
| Change Receivables | (113.8M) | (339.8M) | (486.5M) | 129.2M | 116.3M | 122.1M | |
| Net Borrowings | (2.2M) | 989.6M | 127.4M | (1M) | (1.2M) | (1.1M) | |
| Cash And Cash Equivalents Changes | 291.9M | 6.0B | 9.7B | (14.0B) | (12.6B) | (12.0B) | |
| Cash Flows Other Operating | 30.6M | (345.2M) | (266.6M) | (444.6M) | (400.1M) | (380.1M) | |
| Change To Netincome | 220.1M | (13.8M) | 318.6M | 291.8M | 335.6M | 211.1M | |
| Change To Operating Activities | (987.9M) | (634.5M) | (1.1B) | (1.1B) | (950.5M) | (998.0M) |
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
| 0.82 | DJCO | Daily Journal Corp | PairCorr |
| 0.8 | AI | C3 Ai Inc Earnings Call This Week | PairCorr |
| 0.95 | BL | Blackline | PairCorr |
| 0.69 | DT | Dynatrace Holdings LLC | PairCorr |
Moving against Automatic Stock
| 0.61 | VERB | VERB TECHNOLOGY PANY Tech Boost | PairCorr |
| 0.59 | VTEX | VTEX | PairCorr |
| 0.35 | DMAN | Innovativ Media Group | 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.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.