Etf Series Solutions Etf Market Value
| MSTQ Etf | USD 33.74 0.19 0.57% |
| Symbol | ETF |
The market value of ETF Series Solutions is measured differently than its book value, which is the value of ETF that is recorded on the company's balance sheet. Investors also form their own opinion of ETF Series' value that differs from its market value or its book value, called intrinsic value, which is ETF Series' 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 ETF Series' market value can be influenced by many factors that don't directly affect ETF Series' 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 ETF Series' value and its price as these two are different measures arrived at by different means. Investors typically determine if ETF Series is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, ETF Series' 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.
ETF Series '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 ETF Series' 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 ETF Series.
| 12/08/2022 |
| 11/27/2024 |
If you would invest 0.00 in ETF Series on December 8, 2022 and sell it all today you would earn a total of 0.00 from holding ETF Series Solutions or generate 0.0% return on investment in ETF Series over 720 days. ETF Series is related to or competes with WisdomTree 9060, RPAR Risk, Cambria Tail, Aptus Defined, and AGFiQ Market. The fund is an actively-managed exchange-traded fund that seeks to achieve its objective principally by investing in equ... More
ETF Series 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 ETF Series' 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 ETF Series Solutions upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.21 | |||
| Information Ratio | (0.09) | |||
| Maximum Drawdown | 4.71 | |||
| Value At Risk | (2.40) | |||
| Potential Upside | 1.54 |
ETF Series Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for ETF Series' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as ETF Series' standard deviation. In reality, there are many statistical measures that can use ETF Series historical prices to predict the future ETF Series' volatility.| Risk Adjusted Performance | 0.0321 | |||
| Jensen Alpha | (0.07) | |||
| Total Risk Alpha | (0.13) | |||
| Sortino Ratio | (0.07) | |||
| Treynor Ratio | 0.0351 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of ETF Series' 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.
ETF Series Solutions Backtested Returns
Currently, ETF Series Solutions is very steady. ETF Series Solutions secures Sharpe Ratio (or Efficiency) of 0.0791, which denotes the etf had a 0.0791% return per unit of return volatility over the last 3 months. We have found twenty-eight technical indicators for ETF Series Solutions, which you can use to evaluate the volatility of the entity. Please confirm ETF Series' mean deviation of 0.7259, and Downside Deviation of 1.21 to check if the risk estimate we provide is consistent with the expected return of 0.0808%. The etf shows a Beta (market volatility) of 0.84, which means possible diversification benefits within a given portfolio. As returns on the market increase, ETF Series' returns are expected to increase less than the market. However, during the bear market, the loss of holding ETF Series is expected to be smaller as well.
Auto-correlation | 0.89 |
Very good predictability
ETF Series Solutions has very good predictability. Overlapping area represents the amount of predictability between ETF Series time series from 8th of December 2022 to 3rd of December 2023 and 3rd of December 2023 to 27th 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 ETF Series Solutions price movement. The serial correlation of 0.89 indicates that approximately 89.0% of current ETF Series price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.89 | |
| Spearman Rank Test | 0.8 | |
| Residual Average | 0.0 | |
| Price Variance | 3.52 |
ETF Series Solutions lagged returns against current returns
Autocorrelation, which is ETF Series 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 ETF Series' etf expected returns. We can calculate the autocorrelation of ETF Series returns to help us make a trade decision. For example, suppose you find that ETF Series 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 |
ETF Series 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 ETF Series etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if ETF Series etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in ETF Series etf over time.
Current vs Lagged Prices |
| Timeline |
ETF Series Lagged Returns
When evaluating ETF Series' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of ETF Series etf have on its future price. ETF Series 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, ETF Series autocorrelation shows the relationship between ETF Series etf current value and its past values and can show if there is a momentum factor associated with investing in ETF Series Solutions.
Regressed Prices |
| Timeline |
Pair Trading with ETF Series
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 ETF Series 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 ETF Series will appreciate offsetting losses from the drop in the long position's value.Moving together with ETF Etf
| 0.95 | ACIO | Aptus Collared Income | PairCorr |
| 0.95 | ADME | Aptus Drawdown Managed | PairCorr |
| 0.69 | SWAN | Amplify BlackSwan Growth | PairCorr |
| 0.76 | PHDG | Invesco SP 500 | PairCorr |
Moving against ETF Etf
The ability to find closely correlated positions to ETF Series could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace ETF Series 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 ETF Series - 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 ETF Series Solutions to buy it.
The correlation of ETF Series 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 ETF Series moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if ETF Series Solutions 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 ETF Series 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 ETF Series Correlation, ETF Series Volatility and ETF Series Alpha and Beta module to complement your research on ETF Series. You can also try the Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
ETF Series 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.