Fidelity Momentum Etf Probability of Future Etf Price Finishing Over 17.16
| FCMO Etf | 17.68 0.03 0.17% |
Fidelity |
Fidelity Momentum Target Price Odds to finish over 17.16
The tendency of Fidelity Etf 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 17.16 in 90 days |
| 17.68 | 90 days | 17.16 | about 12.13 |
Based on a normal probability distribution, the odds of Fidelity Momentum to stay above 17.16 in 90 days from now is about 12.13 (This Fidelity Momentum ETF probability density function shows the probability of Fidelity Etf to fall within a particular range of prices over 90 days) . Probability of Fidelity Momentum ETF price to stay between 17.16 and its current price of 17.68 at the end of the 90-day period is about 7.52 .
Assuming the 90 days trading horizon Fidelity Momentum has a beta of 0.49. This usually indicates as returns on the market go up, Fidelity Momentum average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding Fidelity Momentum ETF will be expected to be much smaller as well. Additionally Fidelity Momentum ETF has an alpha of 0.2186, implying that it can generate a 0.22 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). Fidelity Momentum Price Density |
| Price |
Predictive Modules for Fidelity Momentum
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Fidelity Momentum ETF. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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.Fidelity Momentum Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. Fidelity Momentum is not an exception. The market had few large corrections towards the Fidelity Momentum'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 Fidelity Momentum ETF, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of Fidelity Momentum within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | 0.22 | |
β | Beta against Dow Jones | 0.49 | |
σ | Overall volatility | 1.01 | |
Ir | Information ratio | 0.17 |
Fidelity Momentum Technical Analysis
Fidelity Momentum's future price can be derived by breaking down and analyzing its technical indicators over time. Fidelity Etf technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Fidelity Momentum ETF. In general, you should focus on analyzing Fidelity Etf price patterns and their correlations with different microeconomic environments and drivers.
Fidelity Momentum Predictive Forecast Models
Fidelity Momentum's time-series forecasting models is one of many Fidelity Momentum's etf 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 Fidelity Momentum'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 etf 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 Fidelity Momentum 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, Fidelity Momentum's short interest history, or implied volatility extrapolated from Fidelity Momentum options trading.
Other Information on Investing in Fidelity Etf
Fidelity Momentum financial ratios help investors to determine whether Fidelity Etf 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 Fidelity with respect to the benefits of owning Fidelity Momentum security.