CO OPERATIVE (Kenya) Probability of Future Stock Price Finishing Over 14.02
| CBKL Stock | 13.80 0.05 0.36% |
CBKL |
CO OPERATIVE Target Price Odds to finish over 14.02
The tendency of CBKL 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 14.02 or more in 90 days |
| 13.80 | 90 days | 14.02 | about 22.48 |
Based on a normal probability distribution, the odds of CO OPERATIVE to move over 14.02 or more in 90 days from now is about 22.48 (This CO OPERATIVE BANK OF probability density function shows the probability of CBKL Stock to fall within a particular range of prices over 90 days) . Probability of CO OPERATIVE BANK price to stay between its current price of 13.80 and 14.02 at the end of the 90-day period is about 18.83 .
Assuming the 90 days trading horizon CO OPERATIVE has a beta of 0.0757 suggesting as returns on the market go up, CO OPERATIVE average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding CO OPERATIVE BANK OF will be expected to be much smaller as well. Additionally CO OPERATIVE BANK OF has an alpha of 0.0132, implying that it can generate a 0.0132 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). CO OPERATIVE Price Density |
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Predictive Modules for CO OPERATIVE
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as CO OPERATIVE BANK. 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.CO OPERATIVE Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. CO OPERATIVE is not an exception. The market had few large corrections towards the CO OPERATIVE'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 CO OPERATIVE BANK OF, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of CO OPERATIVE within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.01 | |
β | Beta against Dow Jones | 0.08 | |
σ | Overall volatility | 0.41 | |
Ir | Information ratio | -0.13 |
CO OPERATIVE Technical Analysis
CO OPERATIVE's future price can be derived by breaking down and analyzing its technical indicators over time. CBKL Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of CO OPERATIVE BANK OF. In general, you should focus on analyzing CBKL Stock price patterns and their correlations with different microeconomic environments and drivers.
CO OPERATIVE Predictive Forecast Models
CO OPERATIVE's time-series forecasting models is one of many CO OPERATIVE'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 CO OPERATIVE'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 CO OPERATIVE 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, CO OPERATIVE's short interest history, or implied volatility extrapolated from CO OPERATIVE options trading.