Ft Cboe Vest Etf Market Value
| FAPR Etf | USD 44.61 0.01 0.02% |
| Symbol | FAPR |
The market value of FT Cboe Vest is measured differently than its book value, which is the value of FAPR 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. Market participants employ diverse analytical approaches to determine fair value and identify buying opportunities when prices dip below calculated worth. 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. Meanwhile, FT Cboe's quoted price indicates the marketplace figure where supply meets demand through bilateral consent.
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.
| 11/03/2025 |
| 02/01/2026 |
If you would invest 0.00 in FT Cboe on November 3, 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 FT Cboe, First Trust, FT Cboe, First Trust, FT Cboe, FT Cboe, and Innovator. Under normal market conditions, the fund will invest substantially all of its assets in FLexible EXchange Options that r... 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 | 0.2019 | |||
| Information Ratio | (0.07) | |||
| Maximum Drawdown | 0.9327 | |||
| Value At Risk | (0.25) | |||
| Potential Upside | 0.346 |
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 | 0.1023 | |||
| Jensen Alpha | 0.0229 | |||
| Total Risk Alpha | 0.0141 | |||
| Sortino Ratio | (0.06) | |||
| Treynor Ratio | (3.10) |
FT Cboe February 1, 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 | 0.1023 | |||
| Market Risk Adjusted Performance | (3.09) | |||
| Mean Deviation | 0.1224 | |||
| Downside Deviation | 0.2019 | |||
| Coefficient Of Variation | 543.45 | |||
| Standard Deviation | 0.1775 | |||
| Variance | 0.0315 | |||
| Information Ratio | (0.07) | |||
| Jensen Alpha | 0.0229 | |||
| Total Risk Alpha | 0.0141 | |||
| Sortino Ratio | (0.06) | |||
| Treynor Ratio | (3.10) | |||
| Maximum Drawdown | 0.9327 | |||
| Value At Risk | (0.25) | |||
| Potential Upside | 0.346 | |||
| Downside Variance | 0.0408 | |||
| Semi Variance | (0.01) | |||
| Expected Short fall | (0.15) | |||
| Skewness | (0.16) | |||
| Kurtosis | 1.65 |
FT Cboe Vest Backtested Returns
Currently, FT Cboe Vest is very steady. FT Cboe Vest retains Efficiency (Sharpe Ratio) of 0.18, which denotes the etf had a 0.18 % return per unit of price deviation over the last 3 months. We have found twenty-nine technical indicators for FT Cboe, which you can use to evaluate the volatility of the entity. Please confirm FT Cboe's Market Risk Adjusted Performance of (3.09), variance of 0.0315, and Coefficient Of Variation of 543.45 to check if the risk estimate we provide is consistent with the expected return of 0.0327%. The etf owns a Beta (Systematic Risk) of -0.0073, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning FT Cboe are expected to decrease at a much lower rate. During the bear market, FT Cboe is likely to outperform the market.
Auto-correlation | 0.51 |
Modest predictability
FT Cboe Vest has modest predictability. Overlapping area represents the amount of predictability between FT Cboe time series from 3rd of November 2025 to 18th of December 2025 and 18th of December 2025 to 1st of February 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 0.51 indicates that about 51.0% of current FT Cboe price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.51 | |
| Spearman Rank Test | 0.73 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Pair Trading with FT Cboe
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if FT Cboe position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in FT Cboe will appreciate offsetting losses from the drop in the long position's value.Moving together with FAPR Etf
| 0.77 | INOV | Innovator ETFs Trust | PairCorr |
| 0.85 | BUFR | First Trust Cboe | PairCorr |
| 0.85 | BUFD | FT Cboe Vest | PairCorr |
| 0.98 | PSEP | Innovator SP 500 | PairCorr |
| 0.99 | PJAN | Innovator SP 500 | PairCorr |
Moving against FAPR Etf
The ability to find closely correlated positions to FT Cboe could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace FT Cboe when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back FT Cboe - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling FT Cboe Vest to buy it.
The correlation of FT Cboe is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as FT Cboe moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if FT Cboe Vest moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for FT Cboe can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out FT Cboe Correlation, FT Cboe Volatility and FT Cboe Performance module to complement your research on FT Cboe. You can also try the Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
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.