Secured Options Portfolio Fund Probability of Future Mutual Fund Price Finishing Over 16.16
| GLSOX Fund | USD 15.58 0.02 0.13% |
Secured |
Secured Options Target Price Odds to finish over 16.16
The tendency of Secured 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 move over $ 16.16 or more in 90 days |
| 15.58 | 90 days | 16.16 | near 1 |
Based on a normal probability distribution, the odds of Secured Options to move over $ 16.16 or more in 90 days from now is near 1 (This Secured Options Portfolio probability density function shows the probability of Secured Mutual Fund to fall within a particular range of prices over 90 days) . Probability of Secured Options Portfolio price to stay between its current price of $ 15.58 and $ 16.16 at the end of the 90-day period is roughly 2.56 .
Assuming the 90 days horizon Secured Options has a beta of 0.2. This usually indicates as returns on the market go up, Secured Options average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Secured Options Portfolio will be expected to be much smaller as well. Additionally Secured Options Portfolio has an alpha of 0.034, implying that it can generate a 0.034 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Secured Options Price Density |
| Price |
Predictive Modules for Secured Options
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Secured Options Portfolio. 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.Secured Options Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Secured Options is not an exception. The market had few large corrections towards the Secured Options' 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 Secured Options Portfolio, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Secured Options within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.03 | |
β | Beta against Dow Jones | 0.20 | |
σ | Overall volatility | 0.20 | |
Ir | Information ratio | -0.34 |
Secured Options Technical Analysis
Secured Options' future price can be derived by breaking down and analyzing its technical indicators over time. Secured Mutual Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Secured Options Portfolio. In general, you should focus on analyzing Secured Mutual Fund price patterns and their correlations with different microeconomic environments and drivers.
Secured Options Predictive Forecast Models
Secured Options' time-series forecasting models is one of many Secured Options' 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 Secured Options' 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 Secured Options 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, Secured Options' short interest history, or implied volatility extrapolated from Secured Options options trading.
Other Information on Investing in Secured Mutual Fund
Secured Options financial ratios help investors to determine whether Secured 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 Secured with respect to the benefits of owning Secured Options security.
| Commodity Directory Find actively traded commodities issued by global exchanges | |
| Bond Analysis Evaluate and analyze corporate bonds as a potential investment for your portfolios. | |
| Balance Of Power Check stock momentum by analyzing Balance Of Power indicator and other technical ratios | |
| Transaction History View history of all your transactions and understand their impact on performance |