Warehouses (Germany) Technical Analysis
| WPHB Stock | EUR 18.96 0.26 1.39% |
As of the 25th of December, Warehouses maintains the Mean Deviation of 1.06, standard deviation of 1.42, and Market Risk Adjusted Performance of 18.56. Relative to fundamental indicators, the technical analysis model lets you check existing technical drivers of Warehouses De Pauw, as well as the relationship between them. Please check out Warehouses De Pauw mean deviation, standard deviation, information ratio, as well as the relationship between the coefficient of variation and variance to decide if Warehouses De Pauw is priced fairly, providing market reflects its latest price of 18.96 per share.
Warehouses Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as Warehouses, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to WarehousesWarehouses |
Warehouses 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.
Warehouses De Pauw Technical Analysis
Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. 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 Warehouses De Pauw volatility. High ATR values indicate high volatility, and low values indicate low volatility.
Warehouses De Pauw Trend Analysis
Use this graph to draw trend lines for Warehouses De Pauw. You can use it to identify possible trend reversals for Warehouses 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 Warehouses price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.Warehouses Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Warehouses De Pauw applied against its price change over selected period. The best fit line has a slop of 0.08 , which may suggest that Warehouses De Pauw market price will keep on failing further. It has 122 observation points and a regression sum of squares at 221.42, which is the sum of squared deviations for the predicted Warehouses price change compared to its average price change.About Warehouses 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 Warehouses De Pauw 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 Warehouses De Pauw based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on Warehouses De Pauw price pattern first instead of the macroeconomic environment surrounding Warehouses De Pauw. By analyzing Warehouses'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 Warehouses'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 Warehouses specific price patterns or momentum indicators. Please read more on our technical analysis page.
Warehouses December 25, 2024 Technical Indicators
Most technical analysis of Warehouses 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 Warehouses from various momentum indicators to cycle indicators. When you analyze Warehouses 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 | (0.20) | |||
| Market Risk Adjusted Performance | 18.56 | |||
| Mean Deviation | 1.06 | |||
| Coefficient Of Variation | (386.63) | |||
| Standard Deviation | 1.42 | |||
| Variance | 2.01 | |||
| Information Ratio | (0.29) | |||
| Jensen Alpha | (0.38) | |||
| Total Risk Alpha | (0.44) | |||
| Treynor Ratio | 18.55 | |||
| Maximum Drawdown | 7.52 | |||
| Value At Risk | (2.81) | |||
| Potential Upside | 1.86 | |||
| Skewness | (0.54) | |||
| Kurtosis | 1.52 |
Complementary Tools for Warehouses Stock analysis
When running Warehouses' price analysis, check to measure Warehouses' 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 Warehouses is operating at the current time. Most of Warehouses' value examination focuses on studying past and present price action to predict the probability of Warehouses' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Warehouses' price. Additionally, you may evaluate how the addition of Warehouses to your portfolios can decrease your overall portfolio volatility.
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