Voya Retirement Servative Fund Probability of Future Mutual Fund Price Finishing Over 8.16
| IRCPX Fund | USD 8.18 0.03 0.37% |
Voya |
Voya Retirement Target Price Odds to finish over 8.16
The tendency of Voya 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 $ 8.16 in 90 days |
| 8.18 | 90 days | 8.16 | about 12.68 |
Based on a normal probability distribution, the odds of Voya Retirement to stay above $ 8.16 in 90 days from now is about 12.68 (This Voya Retirement Servative probability density function shows the probability of Voya Mutual Fund to fall within a particular range of prices over 90 days) . Probability of Voya Retirement Servative price to stay between $ 8.16 and its current price of $8.18 at the end of the 90-day period is about 7.18 .
Assuming the 90 days horizon Voya Retirement has a beta of 0.0357. This usually indicates as returns on the market go up, Voya Retirement average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Voya Retirement Servative will be expected to be much smaller as well. Additionally Voya Retirement Servative has an alpha of 0.009, implying that it can generate a 0.008996 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Voya Retirement Price Density |
| Price |
Predictive Modules for Voya Retirement
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Voya Retirement Servative. 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.Voya Retirement Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Voya Retirement is not an exception. The market had few large corrections towards the Voya Retirement'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 Voya Retirement Servative, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Voya Retirement within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.01 | |
β | Beta against Dow Jones | 0.04 | |
σ | Overall volatility | 0.04 | |
Ir | Information ratio | -0.37 |
Voya Retirement Technical Analysis
Voya Retirement's future price can be derived by breaking down and analyzing its technical indicators over time. Voya Mutual Fund technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Voya Retirement Servative. In general, you should focus on analyzing Voya Mutual Fund price patterns and their correlations with different microeconomic environments and drivers.
Voya Retirement Predictive Forecast Models
Voya Retirement's time-series forecasting models is one of many Voya Retirement'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 Voya Retirement'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 Voya Retirement 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, Voya Retirement's short interest history, or implied volatility extrapolated from Voya Retirement options trading.
Other Information on Investing in Voya Mutual Fund
Voya Retirement financial ratios help investors to determine whether Voya 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 Voya with respect to the benefits of owning Voya Retirement security.
| ETF Categories List of ETF categories grouped based on various criteria, such as the investment strategy or type of investments | |
| Sectors List of equity sectors categorizing publicly traded companies based on their primary business activities | |
| Money Flow Index Determine momentum by analyzing Money Flow Index and other technical indicators | |
| Bonds Directory Find actively traded corporate debentures issued by US companies |