Data Call Technologi Stock Technical Analysis
| DCLT Stock | USD 0.0001 0.0001 50.00% |
As of the 20th of July, Data Call shows the Variance of 557.17, standard deviation of 23.6, and Mean Deviation of 7.22. Data Call Technologi 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 Call Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Data, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to DataData |
Data Call technical pink sheet analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, pink sheet market cycles, or different charting patterns.
Data Call Technologi Technical Analysis
The output start index for this execution was fourteen with a total number of output elements of fourty-seven. The Normalized Average True Range is used to analyze tradable apportunities for Data Call Technologi across different markets.
Data Call Technologi Trend Analysis
Use this graph to draw trend lines for Data Call Technologi. You can use it to identify possible trend reversals for Data Call as well as other signals and approximate when it will take place. Remember, you need at least two touches of the trend line with actual Data Call price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.Data Call Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Data Call Technologi applied against its price change over selected period. The best fit line has a slop of 0 , which may suggest that Data Call Technologi market price will keep on failing further. It has 122 observation points and a regression sum of squares at 0.0, which is the sum of squared deviations for the predicted Data Call price change compared to its average price change.About Data Call Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of Data Call Technologi on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of Data Call Technologi based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Data Call Technologi price pattern first instead of the macroeconomic environment surrounding Data Call Technologi. By analyzing Data Call's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of Data Call's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to Data Call specific price patterns or momentum indicators. Please read more on our technical analysis page.
Data Call July 20, 2025 Technical Indicators
Most technical analysis of Data help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Data from various momentum indicators to cycle indicators. When you analyze Data charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0034 | |||
| Market Risk Adjusted Performance | (0.14) | |||
| Mean Deviation | 7.22 | |||
| Coefficient Of Variation | (15,100) | |||
| Standard Deviation | 23.6 | |||
| Variance | 557.17 | |||
| Information Ratio | (0.01) | |||
| Jensen Alpha | (0.31) | |||
| Total Risk Alpha | (3.47) | |||
| Treynor Ratio | (0.15) | |||
| Maximum Drawdown | 150.0 | |||
| Value At Risk | (50.00) | |||
| Skewness | 1.16 | |||
| Kurtosis | 12.21 |
Data Call July 20, 2025 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as Data stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 0.00 | ||
| Daily Balance Of Power | (Huge) | ||
| Rate Of Daily Change | 0.50 | ||
| Day Median Price | 0.00 | ||
| Day Typical Price | 0.00 | ||
| Price Action Indicator | 0.00 |
Additional Tools for Data Pink Sheet Analysis
When running Data Call's price analysis, check to measure Data Call'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 Data Call is operating at the current time. Most of Data Call's value examination focuses on studying past and present price action to predict the probability of Data Call's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Data Call's price. Additionally, you may evaluate how the addition of Data Call to your portfolios can decrease your overall portfolio volatility.