Sword Group (Germany) Probability of Future Stock Price Finishing Over 34.80
| 9RS Stock | 34.80 0.30 0.87% |
Sword |
Sword Group Target Price Odds to finish over 34.80
The tendency of Sword Stock 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 above the current price in 90 days |
| 34.80 | 90 days | 34.80 | about 45.87 |
Based on a normal probability distribution, the odds of Sword Group to move above the current price in 90 days from now is about 45.87 (This Sword Group SE probability density function shows the probability of Sword Stock to fall within a particular range of prices over 90 days) .
Assuming the 90 days trading horizon Sword Group has a beta of 0.013. This suggests as returns on the market go up, Sword Group average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Sword Group SE will be expected to be much smaller as well. Additionally Sword Group SE has an alpha of 0.2141, implying that it can generate a 0.21 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Sword Group Price Density |
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Predictive Modules for Sword Group
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Sword Group SE. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Sword Group's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Sword Group Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Sword Group is not an exception. The market had few large corrections towards the Sword Group'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 Sword Group SE, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Sword Group within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.21 | |
β | Beta against Dow Jones | 0.01 | |
σ | Overall volatility | 2.22 | |
Ir | Information ratio | 0.05 |
Sword Group Technical Analysis
Sword Group's future price can be derived by breaking down and analyzing its technical indicators over time. Sword Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Sword Group SE. In general, you should focus on analyzing Sword Stock price patterns and their correlations with different microeconomic environments and drivers.
Sword Group Predictive Forecast Models
Sword Group's time-series forecasting models is one of many Sword Group's stock 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 Sword Group'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 stock 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 Sword Group 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, Sword Group's short interest history, or implied volatility extrapolated from Sword Group options trading.
Additional Tools for Sword Stock Analysis
When running Sword Group's price analysis, check to measure Sword Group'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 Sword Group is operating at the current time. Most of Sword Group's value examination focuses on studying past and present price action to predict the probability of Sword Group's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Sword Group's price. Additionally, you may evaluate how the addition of Sword Group to your portfolios can decrease your overall portfolio volatility.