Morrow Bank (Norway) Probability of Future Stock Price Finishing Under 5.22
| MOBA Stock | 8.80 0.20 2.22% |
Morrow |
Morrow Bank Target Price Odds to finish below 5.22
The tendency of Morrow 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 drop to 5.22 or more in 90 days |
| 8.80 | 90 days | 5.22 | about 5.49 |
Based on a normal probability distribution, the odds of Morrow Bank to drop to 5.22 or more in 90 days from now is about 5.49 (This Morrow Bank ASA probability density function shows the probability of Morrow Stock to fall within a particular range of prices over 90 days) . Probability of Morrow Bank ASA price to stay between 5.22 and its current price of 8.8 at the end of the 90-day period is about 92.3 .
Assuming the 90 days trading horizon Morrow Bank has a beta of 0.53. This indicates as returns on the market go up, Morrow Bank average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Morrow Bank ASA will be expected to be much smaller as well. Additionally Morrow Bank ASA has an alpha of 0.5169, implying that it can generate a 0.52 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Morrow Bank Price Density |
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Predictive Modules for Morrow Bank
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Morrow Bank ASA. 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.Morrow Bank Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Morrow Bank is not an exception. The market had few large corrections towards the Morrow Bank'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 Morrow Bank ASA, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Morrow Bank within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.52 | |
β | Beta against Dow Jones | 0.53 | |
σ | Overall volatility | 0.99 | |
Ir | Information ratio | 0.22 |
Morrow Bank Technical Analysis
Morrow Bank's future price can be derived by breaking down and analyzing its technical indicators over time. Morrow Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Morrow Bank ASA. In general, you should focus on analyzing Morrow Stock price patterns and their correlations with different microeconomic environments and drivers.
Morrow Bank Predictive Forecast Models
Morrow Bank's time-series forecasting models is one of many Morrow Bank'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 Morrow Bank'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 Morrow Bank 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, Morrow Bank's short interest history, or implied volatility extrapolated from Morrow Bank options trading.