BankInvest Optima (Denmark) Probability of Future Stock Price Finishing Over 111.51
| BIV30 Stock | 111.05 0.55 0.49% |
BankInvest |
BankInvest Optima Target Price Odds to finish over 111.51
The tendency of BankInvest 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 over 111.51 or more in 90 days |
| 111.05 | 90 days | 111.51 | about 19.25 |
Based on a normal probability distribution, the odds of BankInvest Optima to move over 111.51 or more in 90 days from now is about 19.25 (This BankInvest Optima 30 probability density function shows the probability of BankInvest Stock to fall within a particular range of prices over 90 days) . Probability of BankInvest Optima price to stay between its current price of 111.05 and 111.51 at the end of the 90-day period is about 8.8 .
Assuming the 90 days trading horizon BankInvest Optima has a beta of 0.0627 suggesting as returns on the market go up, BankInvest Optima average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding BankInvest Optima 30 will be expected to be much smaller as well. Additionally BankInvest Optima 30 has an alpha of 0.0388, implying that it can generate a 0.0388 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). BankInvest Optima Price Density |
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Predictive Modules for BankInvest Optima
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 Optima. 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.BankInvest Optima Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. BankInvest Optima is not an exception. The market had few large corrections towards the BankInvest Optima'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 Optima 30, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of BankInvest Optima within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.04 | |
β | Beta against Dow Jones | 0.06 | |
σ | Overall volatility | 1.60 | |
Ir | Information ratio | 0.04 |
BankInvest Optima Technical Analysis
BankInvest Optima's future price can be derived by breaking down and analyzing its technical indicators over time. BankInvest Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of BankInvest Optima 30. In general, you should focus on analyzing BankInvest Stock price patterns and their correlations with different microeconomic environments and drivers.
BankInvest Optima Predictive Forecast Models
BankInvest Optima's time-series forecasting models is one of many BankInvest Optima'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 BankInvest Optima'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 BankInvest Optima 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 Optima's short interest history, or implied volatility extrapolated from BankInvest Optima options trading.