BankInvest Emerging (Denmark) Probability of Future Fund Price Finishing Over 102.4
| BAIEMOLVA | DKK 102.95 0.45 0.44% |
BankInvest |
BankInvest Emerging Target Price Odds to finish over 102.4
The tendency of BankInvest 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 stay above kr 102.40 in 90 days |
| 102.95 | 90 days | 102.40 | about 36.59 |
Based on a normal probability distribution, the odds of BankInvest Emerging to stay above kr 102.40 in 90 days from now is about 36.59 (This BankInvest Emerging probability density function shows the probability of BankInvest Fund to fall within a particular range of prices over 90 days) . Probability of BankInvest Emerging price to stay between kr 102.40 and its current price of kr102.95 at the end of the 90-day period is about 17.28 .
Assuming the 90 days trading horizon BankInvest Emerging has a beta of 0.32 suggesting as returns on the market go up, BankInvest Emerging average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding BankInvest Emerging will be expected to be much smaller as well. Additionally BankInvest Emerging has an alpha of 0.0019, implying that it can generate a 0.001896 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). BankInvest Emerging Price Density |
| Price |
Predictive Modules for BankInvest Emerging
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as BankInvest Emerging. 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.BankInvest Emerging Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. BankInvest Emerging is not an exception. The market had few large corrections towards the BankInvest Emerging'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 BankInvest Emerging, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of BankInvest Emerging within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0 | |
β | Beta against Dow Jones | 0.32 | |
σ | Overall volatility | 1.05 | |
Ir | Information ratio | -0.13 |
BankInvest Emerging Technical Analysis
BankInvest Emerging's future price can be derived by breaking down and analyzing its technical indicators over time. BankInvest Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of BankInvest Emerging. In general, you should focus on analyzing BankInvest Fund price patterns and their correlations with different microeconomic environments and drivers.
BankInvest Emerging Predictive Forecast Models
BankInvest Emerging's time-series forecasting models is one of many BankInvest Emerging'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 BankInvest Emerging'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 BankInvest Emerging 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, BankInvest Emerging's short interest history, or implied volatility extrapolated from BankInvest Emerging options trading.
Other Information on Investing in BankInvest Fund
BankInvest Emerging financial ratios help investors to determine whether BankInvest Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in BankInvest with respect to the benefits of owning BankInvest Emerging security.
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