ALM ES (Germany) Chance of Future Fund Price Finishing Under 125.26
0P0001NBQF | 127.76 0.00 0.00% |
ALM |
ALM ES Target Price Odds to finish below 125.26
The tendency of ALM Fund 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 drop to 125.26 or more in 90 days |
127.76 | 90 days | 125.26 | about 14.2 |
Based on a normal probability distribution, the odds of ALM ES to drop to 125.26 or more in 90 days from now is about 14.2 (This ALM ES Actions probability density function shows the probability of ALM Fund to fall within a particular range of prices over 90 days) . Probability of ALM ES Actions price to stay between 125.26 and its current price of 127.76 at the end of the 90-day period is about 36.86 .
Assuming the 90 days trading horizon ALM ES Actions has a beta of -0.0959. This suggests as returns on the benchmark increase, returns on holding ALM ES are expected to decrease at a much lower rate. During a bear market, however, ALM ES Actions is likely to outperform the market. Additionally ALM ES Actions has an alpha of 0.0236, implying that it can generate a 0.0236 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). ALM ES Price Density |
Price |
Predictive Modules for ALM ES
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as ALM ES Actions. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the fund 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.ALM ES Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. ALM ES is not an exception. The market had few large corrections towards the ALM ES'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 ALM ES Actions, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of ALM ES within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.02 | |
β | Beta against Dow Jones | -0.1 | |
σ | Overall volatility | 2.29 | |
Ir | Information ratio | 0.04 |
ALM ES Technical Analysis
ALM ES's future price can be derived by breaking down and analyzing its technical indicators over time. ALM Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of ALM ES Actions. In general, you should focus on analyzing ALM Fund price patterns and their correlations with different microeconomic environments and drivers.
ALM ES Predictive Forecast Models
ALM ES's time-series forecasting models is one of many ALM ES's fund 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 ALM ES'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 fund 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 ALM ES 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, ALM ES's short interest history, or implied volatility extrapolated from ALM ES options trading.
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