Boulder Growth Income Fund Probability of Future Mutual Fund Price Finishing Over 16.32
| XBIFX Fund | USD 16.73 0.05 0.30% |
Boulder |
Boulder Growth Target Price Odds to finish over 16.32
The tendency of Boulder Mutual Fund 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 $ 16.32 in 90 days |
| 16.73 | 90 days | 16.32 | about 8.71 |
Based on a normal probability distribution, the odds of Boulder Growth to stay above $ 16.32 in 90 days from now is about 8.71 (This Boulder Growth Income probability density function shows the probability of Boulder Mutual Fund to fall within a particular range of prices over 90 days) . Probability of Boulder Growth Income price to stay between $ 16.32 and its current price of $16.73 at the end of the 90-day period is about 7.91 .
Assuming the 90 days horizon Boulder Growth Income has a beta of -0.12. This entails as returns on the benchmark increase, returns on holding Boulder Growth are expected to decrease at a much lower rate. During a bear market, however, Boulder Growth Income is likely to outperform the market. Additionally Boulder Growth Income has an alpha of 0.1174, implying that it can generate a 0.12 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Boulder Growth Price Density |
| Price |
Predictive Modules for Boulder Growth
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Boulder Growth Income. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund 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.Boulder Growth Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Boulder Growth is not an exception. The market had few large corrections towards the Boulder Growth'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 Boulder Growth Income, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Boulder Growth within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.12 | |
β | Beta against Dow Jones | -0.12 | |
σ | Overall volatility | 0.39 | |
Ir | Information ratio | 0 |
Boulder Growth Technical Analysis
Boulder Growth's future price can be derived by breaking down and analyzing its technical indicators over time. Boulder Mutual Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Boulder Growth Income. In general, you should focus on analyzing Boulder Mutual Fund price patterns and their correlations with different microeconomic environments and drivers.
Boulder Growth Predictive Forecast Models
Boulder Growth's time-series forecasting models is one of many Boulder Growth's mutual fund 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 Boulder Growth'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 mutual fund 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 Boulder Growth 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, Boulder Growth's short interest history, or implied volatility extrapolated from Boulder Growth options trading.
Other Information on Investing in Boulder Mutual Fund
Boulder Growth financial ratios help investors to determine whether Boulder Mutual Fund 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 Boulder with respect to the benefits of owning Boulder Growth security.
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