Data Communications Management Stock Profit Margin
| DCM Stock | CAD 1.77 0.03 1.67% |
Data Communications Management fundamentals help investors to digest information that contributes to Data Communications' financial success or failures. It also enables traders to predict the movement of Data Stock. The fundamental analysis module provides a way to measure Data Communications' intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Data Communications stock.
| Last Reported | Projected for Next Year | ||
| Net Loss | (0.04) | (0.03) |
Data | Profit Margin |
Data Communications Management Company Profit Margin Analysis
Data Communications' Profit Margin measures overall efficiency of a company and shows its ability to withstand competition as well as defend against adverse conditions such as rising costs, falling prices, decline in sales or management distress. Profit margin tells investors how well the company executes on its overall pricing strategies as well as how effective the company in controlling its costs.
Current Data Communications Profit Margin | (0.01) % |
Most of Data Communications' fundamental indicators, such as Profit Margin, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, Data Communications Management is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.
Data Profit Margin 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 Profit Margin. 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.
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In a nutshell, Profit Margin indicator shows the amount of money the company makes from total sales or revenue. It can provide a good insight into companies in the same sector, as well as help to identify trends of a company from year to year.
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Data Pretax Profit Margin
Pretax Profit Margin |
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Based on the latest financial disclosure, Data Communications Management has a Profit Margin of -0.0071%. This is 100.73% lower than that of the Commercial Services & Supplies sector and 101.13% lower than that of the Industrials industry. The profit margin for all Canada stocks is 99.44% lower than that of the firm.
Data Profit Margin 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 Profit Margin 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 profit margin 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.
| 2019 | 2020 | 2021 | 2022 | 2023 | 2024 (projected) | ||
| Market Cap | 5.2M | 27.2M | 56.3M | 63.9M | 133.2M | 139.8M | |
| Enterprise Value | 211.0M | 122.8M | 130.8M | 126.5M | 372.7M | 391.3M |
Data Fundamentals
| Return On Equity | -0.0861 | ||||
| Return On Asset | 0.0649 | ||||
| Profit Margin | (0.01) % | ||||
| Operating Margin | 0.05 % | ||||
| Current Valuation | 339.29 M | ||||
| Shares Outstanding | 55.31 M | ||||
| Shares Owned By Insiders | 22.41 % | ||||
| Shares Owned By Institutions | 8.87 % | ||||
| Number Of Shares Shorted | 21.65 K | ||||
| Price To Earning | 312.50 X | ||||
| Price To Book | 2.53 X | ||||
| Price To Sales | 0.20 X | ||||
| Revenue | 447.73 M | ||||
| Gross Profit | 84.22 M | ||||
| EBITDA | 53.39 M | ||||
| Net Income | (15.85 M) | ||||
| Cash And Equivalents | 4.21 M | ||||
| Cash Per Share | 0.14 X | ||||
| Total Debt | 257.13 M | ||||
| Current Ratio | 1.15 X | ||||
| Book Value Per Share | 0.74 X | ||||
| Cash Flow From Operations | 32.8 M | ||||
| Short Ratio | 1.39 X | ||||
| Earnings Per Share | (0.07) X | ||||
| Target Price | 4.89 | ||||
| Number Of Employees | 1.8 K | ||||
| Beta | 3.37 | ||||
| Market Capitalization | 97.9 M | ||||
| Total Asset | 418.75 M | ||||
| Retained Earnings | (258.5 M) | ||||
| Working Capital | 64.52 M | ||||
| Net Asset | 418.75 M |
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
| 0.73 | FFH-PM | Fairfax Financial | PairCorr |
| 0.72 | FFH | Fairfax Financial | PairCorr |
| 0.7 | FFH-PD | Fairfax Financial | PairCorr |
| 0.62 | FFH-PE | Fairfax Financial | PairCorr |
| 0.61 | GS | GOLDMAN SACHS CDR | PairCorr |
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.