Webs Defined Volatility Etf Market Value
| DVQQ Etf | 25.32 0.01 0.04% |
| Symbol | WEBs |
The market value of WEBs Defined Volatility is measured differently than its book value, which is the value of WEBs that is recorded on the company's balance sheet. Investors also form their own opinion of WEBs Defined's value that differs from its market value or its book value, called intrinsic value, which is WEBs Defined'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 WEBs Defined's market value can be influenced by many factors that don't directly affect WEBs Defined'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 WEBs Defined's value and its price as these two are different measures arrived at by different means. Investors typically determine if WEBs Defined is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, WEBs Defined'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.
WEBs Defined '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 WEBs Defined'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 WEBs Defined.
| 05/11/2025 |
| 08/09/2025 |
If you would invest 0.00 in WEBs Defined on May 11, 2025 and sell it all today you would earn a total of 0.00 from holding WEBs Defined Volatility or generate 0.0% return on investment in WEBs Defined over 90 days. WEBs Defined is related to or competes with FT Vest, Northern Lights, Dimensional International, Matthews China, Davis Select, Dimensional ETF, and First Trust. More
WEBs Defined 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 WEBs Defined'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 WEBs Defined Volatility upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.29 | |||
| Information Ratio | 0.1342 | |||
| Maximum Drawdown | 6.34 | |||
| Value At Risk | (1.43) | |||
| Potential Upside | 2.47 |
WEBs Defined Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for WEBs Defined's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as WEBs Defined's standard deviation. In reality, there are many statistical measures that can use WEBs Defined historical prices to predict the future WEBs Defined's volatility.| Risk Adjusted Performance | 0.1848 | |||
| Jensen Alpha | 0.1744 | |||
| Total Risk Alpha | 0.0999 | |||
| Sortino Ratio | 0.1296 | |||
| Treynor Ratio | 0.2981 |
WEBs Defined Volatility Backtested Returns
WEBs Defined appears to be very steady, given 3 months investment horizon. WEBs Defined Volatility retains Efficiency (Sharpe Ratio) of 0.23, which attests that the etf had a 0.23 % return per unit of volatility over the last 3 months. We have found twenty-nine technical indicators for WEBs Defined, which you can use to evaluate the volatility of the etf. Please utilize WEBs Defined's Standard Deviation of 1.25, market risk adjusted performance of 0.3081, and Mean Deviation of 0.9129 to validate if our risk estimates are consistent with your expectations. The entity owns a Beta (Systematic Risk) of 0.94, which attests to possible diversification benefits within a given portfolio. WEBs Defined returns are very sensitive to returns on the market. As the market goes up or down, WEBs Defined is expected to follow.
Auto-correlation | 0.77 |
Good predictability
WEBs Defined Volatility has good predictability. Overlapping area represents the amount of predictability between WEBs Defined time series from 11th of May 2025 to 25th of June 2025 and 25th of June 2025 to 9th of August 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of WEBs Defined Volatility price movement. The serial correlation of 0.77 indicates that around 77.0% of current WEBs Defined price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.77 | |
| Spearman Rank Test | 0.68 | |
| Residual Average | 0.0 | |
| Price Variance | 0.27 |
WEBs Defined Volatility lagged returns against current returns
Autocorrelation, which is WEBs Defined 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 WEBs Defined's etf expected returns. We can calculate the autocorrelation of WEBs Defined returns to help us make a trade decision. For example, suppose you find that WEBs Defined 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 |
WEBs Defined 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 WEBs Defined etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if WEBs Defined etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in WEBs Defined etf over time.
Current vs Lagged Prices |
| Timeline |
WEBs Defined Lagged Returns
When evaluating WEBs Defined's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of WEBs Defined etf have on its future price. WEBs Defined 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, WEBs Defined autocorrelation shows the relationship between WEBs Defined etf current value and its past values and can show if there is a momentum factor associated with investing in WEBs Defined Volatility.
Regressed Prices |
| Timeline |
Pair Trading with WEBs Defined
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 WEBs Defined 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 WEBs Defined will appreciate offsetting losses from the drop in the long position's value.Moving together with WEBs Etf
Moving against WEBs Etf
| 0.97 | VIXY | ProShares VIX Short | PairCorr |
| 0.89 | VXX | iPath Series B | PairCorr |
| 0.81 | YCL | ProShares Ultra Yen | PairCorr |
The ability to find closely correlated positions to WEBs Defined could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace WEBs Defined 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 WEBs Defined - 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 WEBs Defined Volatility to buy it.
The correlation of WEBs Defined 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 WEBs Defined moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if WEBs Defined Volatility 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 WEBs Defined 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 WEBs Defined Correlation, WEBs Defined Volatility and WEBs Defined Alpha and Beta module to complement your research on WEBs Defined. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
WEBs Defined 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.