Credit Agricole (Egypt) Probability of Future Stock Price Finishing Over 21.62
| CIEB Stock | 21.04 0.14 0.66% |
Credit |
Credit Agricole Target Price Odds to finish over 21.62
The tendency of Credit 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 21.62 or more in 90 days |
| 21.04 | 90 days | 21.62 | about 15.11 |
Based on a normal probability distribution, the odds of Credit Agricole to move over 21.62 or more in 90 days from now is about 15.11 (This Credit Agricole Egypt probability density function shows the probability of Credit Stock to fall within a particular range of prices over 90 days) . Probability of Credit Agricole Egypt price to stay between its current price of 21.04 and 21.62 at the end of the 90-day period is about 18.8 .
Assuming the 90 days trading horizon Credit Agricole Egypt has a beta of -0.26 suggesting as returns on the benchmark increase, returns on holding Credit Agricole are expected to decrease at a much lower rate. During a bear market, however, Credit Agricole Egypt is likely to outperform the market. Additionally Credit Agricole Egypt 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. Credit Agricole Price Density |
| Price |
Predictive Modules for Credit Agricole
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Credit Agricole Egypt. 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.Credit Agricole Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Credit Agricole is not an exception. The market had few large corrections towards the Credit Agricole'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 Credit Agricole Egypt, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Credit Agricole within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | -0.02 | |
β | Beta against Dow Jones | -0.26 | |
σ | Overall volatility | 0.94 | |
Ir | Information ratio | -0.07 |
Credit Agricole Technical Analysis
Credit Agricole's future price can be derived by breaking down and analyzing its technical indicators over time. Credit Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Credit Agricole Egypt. In general, you should focus on analyzing Credit Stock price patterns and their correlations with different microeconomic environments and drivers.
Credit Agricole Predictive Forecast Models
Credit Agricole's time-series forecasting models is one of many Credit Agricole'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 Credit Agricole'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 Credit Agricole 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, Credit Agricole's short interest history, or implied volatility extrapolated from Credit Agricole options trading.