Data Modul (Germany) Technical Analysis
| DAM Stock | EUR 28.00 0.40 1.41% |
As of the 22nd of January, Data Modul shows the Coefficient Of Variation of 1466.35, downside deviation of 2.31, and Mean Deviation of 1.26. Data Modul AG 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. Please confirm Data Modul AG jensen alpha, potential upside, skewness, as well as the relationship between the maximum drawdown and semi variance to decide if Data Modul AG is priced favorably, providing market reflects its regular price of 28.0 per share.
Data Modul 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 Modul '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 Modul's 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 Modul.
| 10/24/2025 |
| 01/22/2026 |
If you would invest 0.00 in Data Modul on October 24, 2025 and sell it all today you would earn a total of 0.00 from holding Data Modul AG or generate 0.0% return on investment in Data Modul over 90 days. Data Modul is related to or competes with MeVis Medical, Kingdee International, Advanced Medical, Minerals Technologies, and ORMAT TECHNOLOGIES. More
Data Modul 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 Modul's 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 Modul AG upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.31 | |||
| Information Ratio | 0.0129 | |||
| Maximum Drawdown | 13.2 | |||
| Value At Risk | (2.22) | |||
| Potential Upside | 2.29 |
Data Modul Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Data Modul's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Data Modul's standard deviation. In reality, there are many statistical measures that can use Data Modul historical prices to predict the future Data Modul's volatility.| Risk Adjusted Performance | 0.0564 | |||
| Jensen Alpha | 0.146 | |||
| Total Risk Alpha | (0.12) | |||
| Sortino Ratio | 0.0105 | |||
| Treynor Ratio | (0.40) |
Data Modul January 22, 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 | 0.0564 | |||
| Market Risk Adjusted Performance | (0.39) | |||
| Mean Deviation | 1.26 | |||
| Semi Deviation | 1.55 | |||
| Downside Deviation | 2.31 | |||
| Coefficient Of Variation | 1466.35 | |||
| Standard Deviation | 1.88 | |||
| Variance | 3.54 | |||
| Information Ratio | 0.0129 | |||
| Jensen Alpha | 0.146 | |||
| Total Risk Alpha | (0.12) | |||
| Sortino Ratio | 0.0105 | |||
| Treynor Ratio | (0.40) | |||
| Maximum Drawdown | 13.2 | |||
| Value At Risk | (2.22) | |||
| Potential Upside | 2.29 | |||
| Downside Variance | 5.33 | |||
| Semi Variance | 2.39 | |||
| Expected Short fall | (1.93) | |||
| Skewness | (0.23) | |||
| Kurtosis | 4.19 |
Data Modul AG Backtested Returns
As of now, Data Stock is very steady. Data Modul AG secures Sharpe Ratio (or Efficiency) of 0.0682, which denotes the company had a 0.0682 % return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Data Modul AG, which you can use to evaluate the volatility of the firm. Please confirm Data Modul's Coefficient Of Variation of 1466.35, mean deviation of 1.26, and Downside Deviation of 2.31 to check if the risk estimate we provide is consistent with the expected return of 0.13%. Data Modul has a performance score of 5 on a scale of 0 to 100. The firm shows a Beta (market volatility) of -0.29, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Data Modul are expected to decrease at a much lower rate. During the bear market, Data Modul is likely to outperform the market. Data Modul AG right now shows a risk of 1.88%. Please confirm Data Modul AG potential upside, skewness, and the relationship between the maximum drawdown and semi variance , to decide if Data Modul AG will be following its price patterns.
Auto-correlation | 0.09 |
Virtually no predictability
Data Modul AG has virtually no predictability. Overlapping area represents the amount of predictability between Data Modul time series from 24th of October 2025 to 8th of December 2025 and 8th of December 2025 to 22nd of January 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 Modul AG price movement. The serial correlation of 0.09 indicates that less than 9.0% of current Data Modul price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.09 | |
| Spearman Rank Test | 0.35 | |
| Residual Average | 0.0 | |
| Price Variance | 0.12 |
Data Modul technical stock 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, stock market cycles, or different charting patterns.
Data Modul AG Technical Analysis
The output start index for this execution was twenty-four with a total number of output elements of thirty-seven. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of Data Modul AG volatility. High ATR values indicate high volatility, and low values indicate low volatility.
About Data Modul 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 Modul AG 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 Modul AG based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Data Modul AG price pattern first instead of the macroeconomic environment surrounding Data Modul AG. By analyzing Data Modul'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 Modul'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 Modul specific price patterns or momentum indicators. Please read more on our technical analysis page.
Data Modul January 22, 2026 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 | 0.0564 | |||
| Market Risk Adjusted Performance | (0.39) | |||
| Mean Deviation | 1.26 | |||
| Semi Deviation | 1.55 | |||
| Downside Deviation | 2.31 | |||
| Coefficient Of Variation | 1466.35 | |||
| Standard Deviation | 1.88 | |||
| Variance | 3.54 | |||
| Information Ratio | 0.0129 | |||
| Jensen Alpha | 0.146 | |||
| Total Risk Alpha | (0.12) | |||
| Sortino Ratio | 0.0105 | |||
| Treynor Ratio | (0.40) | |||
| Maximum Drawdown | 13.2 | |||
| Value At Risk | (2.22) | |||
| Potential Upside | 2.29 | |||
| Downside Variance | 5.33 | |||
| Semi Variance | 2.39 | |||
| Expected Short fall | (1.93) | |||
| Skewness | (0.23) | |||
| Kurtosis | 4.19 |
Data Modul January 22, 2026 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 | 0.99 | ||
| Day Median Price | 28.00 | ||
| Day Typical Price | 28.00 | ||
| Price Action Indicator | (0.20) |
Other Information on Investing in Data Stock
Data Modul 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 Modul security.