Beerenberg (Norway) Probability of Future Stock Price Finishing Over 41.0
| BBERG Stock | 41.00 0.10 0.24% |
Beerenberg |
Beerenberg Target Price Odds to finish over 41.0
The tendency of Beerenberg 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 |
| 41.00 | 90 days | 41.00 | about 19.71 |
Based on a normal probability distribution, the odds of Beerenberg to move above the current price in 90 days from now is about 19.71 (This Beerenberg AS probability density function shows the probability of Beerenberg Stock to fall within a particular range of prices over 90 days) .
Assuming the 90 days trading horizon Beerenberg has a beta of 0.13 suggesting as returns on the market go up, Beerenberg average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Beerenberg AS will be expected to be much smaller as well. Additionally Beerenberg AS 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. Beerenberg Price Density |
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Predictive Modules for Beerenberg
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Beerenberg AS. 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.Please note, it is not enough to conduct a financial or market analysis of a single entity such as Beerenberg. Your research has to be compared to or analyzed against Beerenberg's peers to derive any actionable benefits. When done correctly, Beerenberg's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Beerenberg AS.Beerenberg Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Beerenberg is not an exception. The market had few large corrections towards the Beerenberg'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 Beerenberg AS, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Beerenberg within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | -0.0088 | |
β | Beta against Dow Jones | 0.13 | |
σ | Overall volatility | 0.54 | |
Ir | Information ratio | -0.17 |
Beerenberg Technical Analysis
Beerenberg's future price can be derived by breaking down and analyzing its technical indicators over time. Beerenberg Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Beerenberg AS. In general, you should focus on analyzing Beerenberg Stock price patterns and their correlations with different microeconomic environments and drivers.
Beerenberg Predictive Forecast Models
Beerenberg's time-series forecasting models is one of many Beerenberg'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 Beerenberg'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 Beerenberg 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, Beerenberg's short interest history, or implied volatility extrapolated from Beerenberg options trading.