Ft Vest Equity Etf Market Value
| DHDG Etf | USD 30.81 0.06 0.20% |
| Symbol | DHDG |
The market value of FT Vest Equity is measured differently than its book value, which is the value of DHDG that is recorded on the company's balance sheet. Investors also form their own opinion of FT Vest's value that differs from its market value or its book value, called intrinsic value, which is FT Vest'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 Vest's market value can be influenced by many factors that don't directly affect FT Vest'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 Vest's value and its price as these two are different measures arrived at by different means. Investors typically determine if FT Vest is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, FT Vest'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 Vest '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 Vest'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 Vest.
| 11/30/2023 |
| 11/24/2024 |
If you would invest 0.00 in FT Vest on November 30, 2023 and sell it all today you would earn a total of 0.00 from holding FT Vest Equity or generate 0.0% return on investment in FT Vest over 360 days. FT Vest is related to or competes with Northern Lights, Dimensional International, First Trust, EA Series, FT Cboe, FT Cboe, and ProShares Short. It seeks to achieve its investment objective by investing primarily in equity securities of issuers in developed markets... More
FT Vest 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 Vest'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 Vest Equity upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.5409 | |||
| Information Ratio | (0.17) | |||
| Maximum Drawdown | 2.01 | |||
| Value At Risk | (0.68) | |||
| Potential Upside | 0.5323 |
FT Vest Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for FT Vest's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as FT Vest's standard deviation. In reality, there are many statistical measures that can use FT Vest historical prices to predict the future FT Vest's volatility.| Risk Adjusted Performance | 0.0947 | |||
| Jensen Alpha | 0.0209 | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.14) | |||
| Treynor Ratio | 0.2173 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of FT Vest'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 Vest Equity Backtested Returns
At this point, FT Vest is very steady. FT Vest Equity retains Efficiency (Sharpe Ratio) of 0.13, which denotes the etf had a 0.13% return per unit of price deviation over the last 3 months. We have found twenty-nine technical indicators for FT Vest, which you can use to evaluate the volatility of the entity. Please confirm FT Vest's Standard Deviation of 0.4263, market risk adjusted performance of 0.2273, and Downside Deviation of 0.5409 to check if the risk estimate we provide is consistent with the expected return of 0.0549%. The etf owns a Beta (Systematic Risk) of 0.22, which means not very significant fluctuations relative to the market. As returns on the market increase, FT Vest's returns are expected to increase less than the market. However, during the bear market, the loss of holding FT Vest is expected to be smaller as well.
Auto-correlation | 0.00 |
No correlation between past and present
FT Vest Equity has no correlation between past and present. Overlapping area represents the amount of predictability between FT Vest time series from 30th of November 2023 to 28th of May 2024 and 28th of May 2024 to 24th of November 2024. 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 Vest Equity price movement. The serial correlation of 0.0 indicates that just 0.0% of current FT Vest price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.0 | |
| Spearman Rank Test | 0.0 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
FT Vest Equity lagged returns against current returns
Autocorrelation, which is FT Vest etf's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting FT Vest's etf expected returns. We can calculate the autocorrelation of FT Vest returns to help us make a trade decision. For example, suppose you find that FT Vest has exhibited high autocorrelation historically, and you observe that the etf is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
FT Vest regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If FT Vest etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if FT Vest etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in FT Vest etf over time.
Current vs Lagged Prices |
| Timeline |
FT Vest Lagged Returns
When evaluating FT Vest's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of FT Vest etf have on its future price. FT Vest autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, FT Vest autocorrelation shows the relationship between FT Vest etf current value and its past values and can show if there is a momentum factor associated with investing in FT Vest Equity.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
When determining whether FT Vest Equity offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of FT Vest's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Ft Vest Equity Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Ft Vest Equity Etf:Check out FT Vest Correlation, FT Vest Volatility and FT Vest Alpha and Beta module to complement your research on FT Vest. You can also try the Balance Of Power module to check stock momentum by analyzing Balance Of Power indicator and other technical ratios.
FT Vest 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.