Ft Cboe Vest Etf Market Value
| XISE Etf | 30.42 0.02 0.07% |
| Symbol | XISE |
The market value of FT Cboe Vest is measured differently than its book value, which is the value of XISE 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.
FT Cboe 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to FT Cboe's etf what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of FT Cboe.
| 10/30/2025 |
| 01/28/2026 |
If you would invest 0.00 in FT Cboe on October 30, 2025 and sell it all today you would earn a total of 0.00 from holding FT Cboe Vest or generate 0.0% return on investment in FT Cboe over 90 days. FT Cboe is related to or competes with Innovator ETFs, Tema Monopolies, MRP SynthEquity, Cohen Steers, Innovator Growth, AIM ETF, and Impact Shares. FT Cboe is entity of United States. It is traded as Etf on BATS exchange. More
FT Cboe Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure FT Cboe's etf current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess FT Cboe Vest upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1956 | |||
| Information Ratio | (0.29) | |||
| Maximum Drawdown | 0.7728 | |||
| Value At Risk | (0.30) | |||
| Potential Upside | 0.3378 |
FT Cboe Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for FT Cboe's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as FT Cboe's standard deviation. In reality, there are many statistical measures that can use FT Cboe historical prices to predict the future FT Cboe's volatility.| Risk Adjusted Performance | 0.0963 | |||
| Jensen Alpha | 0.0087 | |||
| Total Risk Alpha | 0.0039 | |||
| Sortino Ratio | (0.25) | |||
| Treynor Ratio | 0.1237 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of FT Cboe's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
FT Cboe January 28, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0963 | |||
| Market Risk Adjusted Performance | 0.1337 | |||
| Mean Deviation | 0.1214 | |||
| Downside Deviation | 0.1956 | |||
| Coefficient Of Variation | 566.61 | |||
| Standard Deviation | 0.169 | |||
| Variance | 0.0285 | |||
| Information Ratio | (0.29) | |||
| Jensen Alpha | 0.0087 | |||
| Total Risk Alpha | 0.0039 | |||
| Sortino Ratio | (0.25) | |||
| Treynor Ratio | 0.1237 | |||
| Maximum Drawdown | 0.7728 | |||
| Value At Risk | (0.30) | |||
| Potential Upside | 0.3378 | |||
| Downside Variance | 0.0383 | |||
| Semi Variance | (0) | |||
| Expected Short fall | (0.13) | |||
| Skewness | (0.07) | |||
| Kurtosis | 0.337 |
FT Cboe Vest Backtested Returns
At this point, FT Cboe is very steady. FT Cboe Vest retains Efficiency (Sharpe Ratio) of 0.19, which denotes the etf had a 0.19 % return per unit of price deviation over the last 3 months. We have found twenty-eight technical indicators for FT Cboe, which you can use to evaluate the volatility of the entity. Please confirm FT Cboe's Variance of 0.0285, coefficient of variation of 566.61, and Market Risk Adjusted Performance of 0.1337 to check if the risk estimate we provide is consistent with the expected return of 0.0311%. The etf owns a Beta (Systematic Risk) of 0.16, which means not very significant fluctuations relative to the market. As returns on the market increase, FT Cboe's returns are expected to increase less than the market. However, during the bear market, the loss of holding FT Cboe is expected to be smaller as well.
Auto-correlation | 0.32 |
Below average predictability
FT Cboe Vest has below average predictability. Overlapping area represents the amount of predictability between FT Cboe time series from 30th of October 2025 to 14th of December 2025 and 14th of December 2025 to 28th of January 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of FT Cboe Vest price movement. The serial correlation of 0.32 indicates that nearly 32.0% of current FT Cboe price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.32 | |
| Spearman Rank Test | 0.62 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
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| HITI | High Tide | |
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Check out FT Cboe Correlation, FT Cboe Volatility and FT Cboe Alpha and Beta module to complement your research on FT Cboe. You can also try the Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.
FT Cboe technical etf analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, etf market cycles, or different charting patterns.