Data Communications Management Stock Net Income
| DCM Stock | CAD 1.49 0.03 2.05% |
As of the 16th of February 2026, Data Communications shows the Coefficient Of Variation of 1033.4, mean deviation of 2.1, and Downside Deviation of 2.68. Data Communications technical analysis allows you to utilize historical prices and volume patterns in order to determine a pattern that computes the direction of the firm's future prices.
Data Communications Total Revenue |
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Gross Profit | Profit Margin | Market Capitalization | Enterprise Value Revenue 0.7383 | Revenue |
| Last Reported | Projected for Next Year | ||
| Net Income | 3.2 M | 3.4 M | |
| Net Income From Continuing Ops | 4.1 M | 4.3 M | |
| Net Income Applicable To Common Shares | 4.1 M | 4.3 M | |
| Net Income Per Share | 0.07 | 0.08 | |
| Net Income Per E B T | 0.78 | 0.79 |
Data | Net Income |
Evaluating Data Communications's Net Income 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 Income Growth Pattern
Below is the plot of the Net Income of Data Communications Management over the last few years. Net income is one of the most important fundamental items in finance. It plays a large role in Data Communications financial statement analysis. It represents the amount of money remaining after all of Data Communications Management operating expenses, interest, taxes and preferred stock dividends have been deducted from a company total revenue. It is Data Communications' Net Income 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.
| View | Last Reported 3.57 M | 10 Years Trend |
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Net Income |
| Timeline |
Data Net Income Regression Statistics
| Arithmetic Mean | (6,452,079) | |
| Coefficient Of Variation | (279.63) | |
| Mean Deviation | 14,749,003 | |
| Median | 2,249,000 | |
| Standard Deviation | 18,042,241 | |
| Sample Variance | 325.5T | |
| Range | 59.8M | |
| R-Value | 0.35 | |
| Mean Square Error | 304.2T | |
| R-Squared | 0.12 | |
| Significance | 0.17 | |
| Slope | 1,257,483 | |
| Total Sum of Squares | 5208.4T |
Data Net Income History
Data Net Income Driver Correlations
Understanding the fundamental principles of building solid financial models for Data Communications is extremely important. It helps to project a fair market value of Data Stock properly, considering its historical fundamentals such as Net Income. Since Data Communications' main accounts across its financial reports are all linked and dependent on each other, it is essential to analyze all possible correlations between related accounts. However, instead of reviewing all of Data Communications' historical financial statements, investors can examine the correlated drivers to determine its overall health. This can be effectively done using a conventional correlation matrix of Data Communications' interrelated accounts and indicators.
Click cells to compare fundamentals
Data Communications 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Data Communications' stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Data Communications.
| 11/18/2025 |
| 02/16/2026 |
If you would invest 0.00 in Data Communications on November 18, 2025 and sell it all today you would earn a total of 0.00 from holding Data Communications Management or generate 0.0% return on investment in Data Communications over 90 days. Data Communications is related to or competes with Titanium Transportation, BluMetric Environmental, Northstar Clean, Vitreous Glass, Atlas Engineered, BioRem, and SSC Security. DATA Communications Management Corp. provides business communication solutions in North America More
Data Communications Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Data Communications' stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Data Communications Management upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.68 | |||
| Information Ratio | 0.0715 | |||
| Maximum Drawdown | 12.85 | |||
| Value At Risk | (3.75) | |||
| Potential Upside | 5.47 |
Data Communications Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data Communications' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data Communications' standard deviation. In reality, there are many statistical measures that can use Data Communications historical prices to predict the future Data Communications' volatility.| Risk Adjusted Performance | 0.0852 | |||
| Jensen Alpha | 0.2327 | |||
| Total Risk Alpha | 0.0522 | |||
| Sortino Ratio | 0.0739 | |||
| Treynor Ratio | 0.6164 |
Data Communications February 16, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0852 | |||
| Market Risk Adjusted Performance | 0.6264 | |||
| Mean Deviation | 2.1 | |||
| Semi Deviation | 2.08 | |||
| Downside Deviation | 2.68 | |||
| Coefficient Of Variation | 1033.4 | |||
| Standard Deviation | 2.77 | |||
| Variance | 7.66 | |||
| Information Ratio | 0.0715 | |||
| Jensen Alpha | 0.2327 | |||
| Total Risk Alpha | 0.0522 | |||
| Sortino Ratio | 0.0739 | |||
| Treynor Ratio | 0.6164 | |||
| Maximum Drawdown | 12.85 | |||
| Value At Risk | (3.75) | |||
| Potential Upside | 5.47 | |||
| Downside Variance | 7.16 | |||
| Semi Variance | 4.31 | |||
| Expected Short fall | (2.94) | |||
| Skewness | 0.443 | |||
| Kurtosis | 0.0542 |
Data Communications Backtested Returns
As of now, Data Stock is very risky. Data Communications secures Sharpe Ratio (or Efficiency) of 0.0499, which denotes the company had a 0.0499 % return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Data Communications Management, which you can use to evaluate the volatility of the firm. Please confirm Data Communications' Mean Deviation of 2.1, coefficient of variation of 1033.4, and Downside Deviation of 2.68 to check if the risk estimate we provide is consistent with the expected return of 0.14%. Data Communications has a performance score of 3 on a scale of 0 to 100. The firm shows a Beta (market volatility) of 0.42, which means possible diversification benefits within a given portfolio. As returns on the market increase, Data Communications' returns are expected to increase less than the market. However, during the bear market, the loss of holding Data Communications is expected to be smaller as well. Data Communications right now shows a risk of 2.75%. Please confirm Data Communications expected short fall, day median price, and the relationship between the potential upside and accumulation distribution , to decide if Data Communications will be following its price patterns.
Auto-correlation | -0.11 |
Insignificant reverse predictability
Data Communications Management has insignificant reverse predictability. Overlapping area represents the amount of predictability between Data Communications time series from 18th of November 2025 to 2nd of January 2026 and 2nd of January 2026 to 16th of February 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Data Communications price movement. The serial correlation of -0.11 indicates that less than 11.0% of current Data Communications price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.11 | |
| Spearman Rank Test | -0.34 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
Because income is reported on the Income Statement of a company and is measured in dollars some investors prefer to use Profit Margin, which measures income as a percentage of sales.
| Competition |
Data Accumulated Other Comprehensive Income
Accumulated Other Comprehensive Income |
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Based on the recorded statements, Data Communications Management reported net income of 3.57 M. This is 98.62% lower than that of the Commercial Services & Supplies sector and 98.45% lower than that of the Industrials industry. The net income for all Canada stocks is 99.37% higher than that of the company.
Data Net Income Peer Comparison
Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Data Communications' direct or indirect competition against its Net Income to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Data Communications could also be used in its relative valuation, which is a method of valuing Data Communications by comparing valuation metrics of similar companies.Data Communications is currently under evaluation in net income category among its peers.
Data Communications Current Valuation Drivers
We derive many important indicators used in calculating different scores of Data Communications from analyzing Data Communications' financial statements. These drivers represent accounts that assess Data Communications' ability to generate profits relative to its revenue, operating costs, and shareholders' equity. Below are some of Data Communications' important valuation drivers and their relationship over time.
| 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (projected) | ||
| Market Cap | 56.3M | 63.9M | 137.2M | 115.4M | 103.9M | 109.1M | |
| Enterprise Value | 130.8M | 126.5M | 376.7M | 362.3M | 326.1M | 342.4M |
Data Fundamentals
| Return On Equity | 0.27 | ||||
| Return On Asset | 0.0581 | ||||
| Profit Margin | 0.02 % | ||||
| Operating Margin | 0.05 % | ||||
| Current Valuation | 338.92 M | ||||
| Shares Outstanding | 54.94 M | ||||
| Shares Owned By Insiders | 22.35 % | ||||
| Shares Owned By Institutions | 13.00 % | ||||
| Number Of Shares Shorted | 25.72 K | ||||
| Price To Earning | 312.50 X | ||||
| Price To Book | 2.08 X | ||||
| Price To Sales | 0.18 X | ||||
| Revenue | 479.96 M | ||||
| Gross Profit | 121.81 M | ||||
| EBITDA | 52.98 M | ||||
| Net Income | 3.57 M | ||||
| Cash And Equivalents | 6.77 M | ||||
| Cash Per Share | 0.14 X | ||||
| Total Debt | 253.7 M | ||||
| Current Ratio | 1.15 X | ||||
| Book Value Per Share | 0.72 X | ||||
| Cash Flow From Operations | 24.74 M | ||||
| Short Ratio | 1.16 X | ||||
| Earnings Per Share | 0.18 X | ||||
| Target Price | 3.38 | ||||
| Number Of Employees | 1.5 K | ||||
| Beta | 0.25 | ||||
| Market Capitalization | 81.86 M | ||||
| Total Asset | 392.3 M | ||||
| Retained Earnings | (248.24 M) | ||||
| Working Capital | 42.8 M | ||||
| Annual Yield | 0.07 % | ||||
| Net Asset | 392.3 M | ||||
| Last Dividend Paid | 0.075 |
About Data Communications Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Data Communications Management's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Data Communications using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Data Communications Management based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
Please read more on our fundamental analysis page.
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.