Siemens Ag Class Stock Technical Analysis
| SMAWF Stock | USD 188.85 0.31 0.16% |
As of the 29th of November, Siemens AG has the Semi Deviation of 1.44, coefficient of variation of 6054.14, and Risk Adjusted Performance of 0.0188. In relation to fundamental indicators, the technical analysis model makes it possible for you to check existing technical drivers of Siemens AG Class, as well as the relationship between them. Please validate Siemens AG Class variance, as well as the relationship between the maximum drawdown and semi variance to decide if Siemens AG is priced more or less accurately, providing market reflects its prevalent price of 188.85 per share. Given that Siemens AG Class has jensen alpha of (0.01), we advise you to double-check Siemens AG Class's current market performance to make sure the company can sustain itself at a future point.
Siemens AG Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Siemens, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to SiemensSiemens |
Siemens AG 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.
Siemens AG Class 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 Siemens AG Class volatility. High ATR values indicate high volatility, and low values indicate low volatility.
Siemens AG Class Trend Analysis
Use this graph to draw trend lines for Siemens AG Class. You can use it to identify possible trend reversals for Siemens AG 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 Siemens AG price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.Siemens AG Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Siemens AG Class applied against its price change over selected period. The best fit line has a slop of 0.11 , which means Siemens AG Class will continue generating value for investors. It has 122 observation points and a regression sum of squares at 462.38, which is the sum of squared deviations for the predicted Siemens AG price change compared to its average price change.About Siemens AG 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 Siemens AG Class 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 Siemens AG Class based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Siemens AG Class price pattern first instead of the macroeconomic environment surrounding Siemens AG Class. By analyzing Siemens AG'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 Siemens AG'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 Siemens AG specific price patterns or momentum indicators. Please read more on our technical analysis page.
Siemens AG November 29, 2024 Technical Indicators
Most technical analysis of Siemens 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 Siemens from various momentum indicators to cycle indicators. When you analyze Siemens 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 | 0.0188 | |||
| Market Risk Adjusted Performance | 0.0815 | |||
| Mean Deviation | 1.41 | |||
| Semi Deviation | 1.44 | |||
| Downside Deviation | 1.5 | |||
| Coefficient Of Variation | 6054.14 | |||
| Standard Deviation | 1.98 | |||
| Variance | 3.93 | |||
| Information Ratio | (0.05) | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.28) | |||
| Sortino Ratio | (0.06) | |||
| Treynor Ratio | 0.0715 | |||
| Maximum Drawdown | 11.05 | |||
| Value At Risk | (2.82) | |||
| Potential Upside | 3.29 | |||
| Downside Variance | 2.26 | |||
| Semi Variance | 2.06 | |||
| Expected Short fall | (1.89) | |||
| Skewness | 1.3 | |||
| Kurtosis | 3.21 |
Complementary Tools for Siemens Pink Sheet analysis
When running Siemens AG's price analysis, check to measure Siemens AG'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 Siemens AG is operating at the current time. Most of Siemens AG's value examination focuses on studying past and present price action to predict the probability of Siemens AG's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Siemens AG's price. Additionally, you may evaluate how the addition of Siemens AG to your portfolios can decrease your overall portfolio volatility.
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