Data Net Debt from 2010 to 2026
| DCM Stock | CAD 1.49 0.03 2.05% |
Net Debt | First Reported 2005-09-30 | Previous Quarter 261 M | Current Value 257.1 M | Quarterly Volatility 65.6 M |
Check Data Communications financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among Data Communications' main balance sheet or income statement drivers, such as Depreciation And Amortization of 15.5 M, Interest Expense of 25.9 M or Selling General Administrative of 33.7 M, as well as many indicators such as Price To Sales Ratio of 0.26, Dividend Yield of 0.57 or PTB Ratio of 2.73. Data financial statements analysis is a perfect complement when working with Data Communications Valuation or Volatility modules.
Data | Net Debt |
Evaluating Data Communications's Net Debt across multiple reporting periods reveals the company's ability to sustain growth and manage resources effectively. This longitudinal analysis highlights inflection points, cyclical patterns, and structural changes that short-term snapshots might miss, offering deeper insight into Data Communications Management's fundamental strength.
Latest Data Communications' Net Debt Growth Pattern
Below is the plot of the Net Debt of Data Communications Management over the last few years. It is the total debt of a company minus its cash and cash equivalents. It represents the actual debt burden on the company after accounting for the liquid assets it holds. Data Communications' Net Debt historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in Data Communications' overall financial position and show how it may be relating to other accounts over time.
| Net Debt | 10 Years Trend |
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Net Debt |
| Timeline |
Data Net Debt Regression Statistics
| Arithmetic Mean | 117,368,688 | |
| Coefficient Of Variation | 82.17 | |
| Mean Deviation | 80,887,559 | |
| Median | 74,497,000 | |
| Standard Deviation | 96,446,800 | |
| Sample Variance | 9302T | |
| Range | 307.1M | |
| R-Value | 0.81 | |
| Mean Square Error | 3402.1T | |
| R-Squared | 0.66 | |
| Significance | 0.000079 | |
| Slope | 15,482,485 | |
| Total Sum of Squares | 148831.8T |
Data Net Debt History
About Data Communications Financial Statements
Data Communications investors utilize fundamental indicators, such as Net Debt, to predict how Data Stock might perform in the future. Analyzing these trends over time helps investors make informed market timing decisions. For further insights, please visit our fundamental analysis page.
| Last Reported | Projected for Next Year | ||
| Net Debt | 284 M | 298.2 M | |
| Net Debt To EBITDA | 4.19 | 3.06 |
Pair Trading with Data Communications
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 Data Communications 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 Data Communications will appreciate offsetting losses from the drop in the long position's value.Moving against Data Stock
The ability to find closely correlated positions to Data Communications could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Data Communications 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 Data Communications - 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 Data Communications Management to buy it.
The correlation of Data Communications 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 Data Communications moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Data Communications 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 Data Communications 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.Other Information on Investing in Data Stock
Data Communications financial ratios help investors to determine whether Data Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Data with respect to the benefits of owning Data Communications security.