Deka Deutsche (Germany) Probability of Future Etf Price Finishing Over 107.79
| EL4U Etf | 107.50 0.36 0.33% |
Deka |
Deka Deutsche Target Price Odds to finish over 107.79
The tendency of Deka Etf price to converge on an average value over time is a known aspect in finance that investors have used since the beginning of the stock market for forecasting. However, many studies suggest that some traded equity instruments are consistently mispriced before traders' demand and supply correct the spread. One possible conclusion to this anomaly is that these stocks have additional risk, for which investors demand compensation in the form of extra returns.
| Current Price | Horizon | Target Price | Odds to move over 107.79 or more in 90 days |
| 107.50 | 90 days | 107.79 | about 25.25 |
Based on a normal probability distribution, the odds of Deka Deutsche to move over 107.79 or more in 90 days from now is about 25.25 (This Deka Deutsche Brse probability density function shows the probability of Deka Etf to fall within a particular range of prices over 90 days) . Probability of Deka Deutsche Brse price to stay between its current price of 107.50 and 107.79 at the end of the 90-day period is about 13.72 .
Assuming the 90 days trading horizon Deka Deutsche has a beta of 0.0395 suggesting as returns on the market go up, Deka Deutsche average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Deka Deutsche Brse will be expected to be much smaller as well. Additionally Deka Deutsche Brse has a negative alpha, implying that the risk taken by holding this instrument is not justified. The company is significantly underperforming the Dow Jones Industrial. Deka Deutsche Price Density |
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Predictive Modules for Deka Deutsche
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Deka Deutsche Brse. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Deka Deutsche Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Deka Deutsche is not an exception. The market had few large corrections towards the Deka Deutsche's value, including both sudden drops in prices as well as massive rallies. These swings have made and broken many portfolios. An investor can limit the violent swings in their portfolio by implementing a hedging strategy designed to limit downside losses. If you hold Deka Deutsche Brse, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Deka Deutsche within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | -0.01 | |
β | Beta against Dow Jones | 0.04 | |
σ | Overall volatility | 0.75 | |
Ir | Information ratio | -0.39 |
Deka Deutsche Technical Analysis
Deka Deutsche's future price can be derived by breaking down and analyzing its technical indicators over time. Deka Etf technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Deka Deutsche Brse. In general, you should focus on analyzing Deka Etf price patterns and their correlations with different microeconomic environments and drivers.
Deka Deutsche Predictive Forecast Models
Deka Deutsche's time-series forecasting models is one of many Deka Deutsche's etf analysis techniques aimed to predict future share value based on previously observed values. Time-series forecasting models are widely used for non-stationary data. Non-stationary data are called the data whose statistical properties, e.g., the mean and standard deviation, are not constant over time, but instead, these metrics vary over time. This non-stationary Deka Deutsche's historical data is usually called time series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the etf market movement and maximize returns from investment trading.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Deka Deutsche in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Deka Deutsche's short interest history, or implied volatility extrapolated from Deka Deutsche options trading.