Data Communications Management Stock Market Value
| DCM Stock | CAD 1.99 0.10 5.29% |
| Symbol | Data |
Data Communications Price To Book Ratio
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.
| 12/07/2022 |
| 11/26/2024 |
If you would invest 0.00 in Data Communications on December 7, 2022 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 720 days. Data Communications is related to or competes with Baylin Technologies, Kits Eyecare, Supremex, and Cipher Pharmaceuticals. 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.
| Information Ratio | (0.16) | |||
| Maximum Drawdown | 35.85 | |||
| Value At Risk | (3.39) | |||
| Potential Upside | 3.15 |
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 | (0.09) | |||
| Jensen Alpha | (0.61) | |||
| Total Risk Alpha | (1.25) | |||
| Treynor Ratio | (1.56) |
Data Communications Backtested Returns
Data Communications secures Sharpe Ratio (or Efficiency) of -0.12, which denotes the company had a -0.12% return per unit of risk over the last 3 months. Data Communications Management exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please confirm Data Communications' Mean Deviation of 1.89, standard deviation of 4.35, and Variance of 18.89 to check the risk estimate we provide. The firm shows a Beta (market volatility) of 0.36, 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. At this point, Data Communications has a negative expected return of -0.54%. Please make sure to confirm Data Communications' accumulation distribution, and the relationship between the potential upside and day median price , to decide if Data Communications performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.04 |
Virtually no predictability
Data Communications Management has virtually no predictability. Overlapping area represents the amount of predictability between Data Communications time series from 7th of December 2022 to 2nd of December 2023 and 2nd of December 2023 to 26th of November 2024. 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 0.04 indicates that only as little as 4.0% of current Data Communications price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.04 | |
| Spearman Rank Test | 0.12 | |
| Residual Average | 0.0 | |
| Price Variance | 0.11 |
Data Communications lagged returns against current returns
Autocorrelation, which is Data Communications stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Data Communications' stock expected returns. We can calculate the autocorrelation of Data Communications returns to help us make a trade decision. For example, suppose you find that Data Communications has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Data Communications regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Data Communications stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Data Communications stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Data Communications stock over time.
Current vs Lagged Prices |
| Timeline |
Data Communications Lagged Returns
When evaluating Data Communications' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Data Communications stock have on its future price. Data Communications autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Data Communications autocorrelation shows the relationship between Data Communications stock current value and its past values and can show if there is a momentum factor associated with investing in Data Communications Management.
Regressed Prices |
| Timeline |
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
| 0.76 | FFH-PM | Fairfax Financial | PairCorr |
| 0.75 | FFH | Fairfax Financial | PairCorr |
| 0.73 | FFH-PD | Fairfax Financial | PairCorr |
| 0.66 | FFH-PE | Fairfax Financial | PairCorr |
| 0.64 | FFH-PH | Fairfax Financial | 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.