REGIONS FINANCIAL (Germany) Probability of Future Stock Price Finishing Over 14.19
| RN70 Stock | 17.50 0.10 0.57% |
REGIONS |
REGIONS FINANCIAL Target Price Odds to finish over 14.19
The tendency of REGIONS 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 stay above 14.19 in 90 days |
| 17.50 | 90 days | 14.19 | close to 99 |
Based on a normal probability distribution, the odds of REGIONS FINANCIAL to stay above 14.19 in 90 days from now is close to 99 (This REGIONS FINANCIAL PFD probability density function shows the probability of REGIONS Stock to fall within a particular range of prices over 90 days) . Probability of REGIONS FINANCIAL PFD price to stay between 14.19 and its current price of 17.5 at the end of the 90-day period is about 57.89 .
Assuming the 90 days trading horizon REGIONS FINANCIAL has a beta of 0.0488 indicating as returns on the market go up, REGIONS FINANCIAL average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding REGIONS FINANCIAL PFD will be expected to be much smaller as well. Additionally REGIONS FINANCIAL PFD has an alpha of 0.0697, implying that it can generate a 0.0697 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). REGIONS FINANCIAL Price Density |
| Price |
Predictive Modules for REGIONS FINANCIAL
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as REGIONS FINANCIAL PFD. 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.REGIONS FINANCIAL Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. REGIONS FINANCIAL is not an exception. The market had few large corrections towards the REGIONS FINANCIAL'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 REGIONS FINANCIAL PFD, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of REGIONS FINANCIAL within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.07 | |
β | Beta against Dow Jones | 0.05 | |
σ | Overall volatility | 0.45 | |
Ir | Information ratio | -0.03 |
REGIONS FINANCIAL Technical Analysis
REGIONS FINANCIAL's future price can be derived by breaking down and analyzing its technical indicators over time. REGIONS Stock technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of REGIONS FINANCIAL PFD. In general, you should focus on analyzing REGIONS Stock price patterns and their correlations with different microeconomic environments and drivers.
REGIONS FINANCIAL Predictive Forecast Models
REGIONS FINANCIAL's time-series forecasting models is one of many REGIONS FINANCIAL'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 REGIONS FINANCIAL'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 REGIONS FINANCIAL 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, REGIONS FINANCIAL's short interest history, or implied volatility extrapolated from REGIONS FINANCIAL options trading.
Other Information on Investing in REGIONS Stock
REGIONS FINANCIAL financial ratios help investors to determine whether REGIONS Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in REGIONS with respect to the benefits of owning REGIONS FINANCIAL security.