Ft Cboe Vest Etf Odds of Future Etf Price Finishing Over 25.39
| SMAY Etf | 25.39 0.19 0.75% |
SMAY |
FT Cboe Target Price Odds to finish over 25.39
The tendency of SMAY 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 move above the current price in 90 days |
| 25.39 | 90 days | 25.39 | under 4 |
Based on a normal probability distribution, the odds of FT Cboe to move above the current price in 90 days from now is under 4 (This FT Cboe Vest probability density function shows the probability of SMAY Etf to fall within a particular range of prices over 90 days) .
Given the investment horizon of 90 days FT Cboe has a beta of 0.72. This usually implies as returns on the market go up, FT Cboe average returns are expected to increase less than the benchmark. However, during the bear market, the loss on holding FT Cboe Vest will be expected to be much smaller as well. Additionally FT Cboe Vest has a negative alpha, implying that the risk taken by holding this instrument is not justified. The company is significantly underperforming the Dow Jones Industrial. FT Cboe Price Density |
| Price |
Predictive Modules for FT Cboe
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as FT Cboe Vest. 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.FT Cboe Risk Indicators
For the most part, the last 10-20 years have been a very volatile time for the stock market. FT Cboe is not an exception. The market had few large corrections towards the FT Cboe'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 FT Cboe Vest, one way to have your portfolio be protected is to always look up for changing volatility and market elasticity of FT Cboe within the framework of very fundamental risk indicators.α | Alpha over Dow Jones | -0.0022 | |
β | Beta against Dow Jones | 0.72 | |
σ | Overall volatility | 0.46 | |
Ir | Information ratio | -0.05 |
FT Cboe Price Density Drivers
Market volatility will typically increase when nervous long traders begin to feel the short-sellers pressure to drive the market lower. The future price of SMAY Etf often depends not only on the future outlook of the current and potential FT Cboe's investors but also on the ongoing dynamics between investors with different trading styles. Because the market risk indicators may have small false signals, it is better to identify suitable times to hedge a portfolio using different long/short signals. FT Cboe's indicators that are reflective of the short sentiment are summarized in the table below.
FT Cboe Technical Analysis
FT Cboe's future price can be derived by breaking down and analyzing its technical indicators over time. SMAY Etf technical analysis helps investors analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of FT Cboe Vest. In general, you should focus on analyzing SMAY Etf price patterns and their correlations with different microeconomic environments and drivers.
FT Cboe Predictive Forecast Models
FT Cboe's time-series forecasting models is one of many FT Cboe'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 FT Cboe'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 FT Cboe 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, FT Cboe's short interest history, or implied volatility extrapolated from FT Cboe options trading.
Check out FT Cboe Backtesting, Portfolio Optimization, FT Cboe Correlation, FT Cboe Hype Analysis, FT Cboe Volatility, FT Cboe History as well as FT Cboe Performance. You can also try the Portfolio File Import module to quickly import all of your third-party portfolios from your local drive in csv format.
The market value of FT Cboe Vest is measured differently than its book value, which is the value of SMAY that is recorded on the company's balance sheet. Investors also form their own opinion of FT Cboe's value that differs from its market value or its book value, called intrinsic value, which is FT Cboe's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because FT Cboe's market value can be influenced by many factors that don't directly affect FT Cboe's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between FT Cboe's value and its price as these two are different measures arrived at by different means. Investors typically determine if FT Cboe is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, FT Cboe's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.