Etf Series Solutions Etf Market Value
| DSMC Etf | USD 38.02 0.05 0.13% |
| 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.
| 02/09/2023 |
| 11/30/2024 |
If you would invest 0.00 in ETF Series on February 9, 2023 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 660 days. ETF Series is related to or competes with Distillate Fundamental, ETF Series, Fairlead Tactical, VanEck ETF, and Pacer Small. The fund is an actively managed exchange-traded fund that seeks to achieve its investment objective by investing in equi... 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 | 1.03 | |||
| Information Ratio | (0.02) | |||
| Maximum Drawdown | 5.91 | |||
| Value At Risk | (1.40) | |||
| Potential Upside | 1.82 |
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 | 0.0827 | |||
| Jensen Alpha | (0.05) | |||
| Total Risk Alpha | (0.08) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.0876 |
ETF Series Solutions Backtested Returns
At this point, ETF Series is very steady. ETF Series Solutions secures Sharpe Ratio (or Efficiency) of 0.15, which denotes the etf had a 0.15% return per unit of return volatility over the last 3 months. We have found thirty technical indicators for ETF Series Solutions, which you can use to evaluate the volatility of the entity. Please confirm ETF Series' mean deviation of 0.845, and Downside Deviation of 1.03 to check if the risk estimate we provide is consistent with the expected return of 0.16%. The etf shows a Beta (market volatility) of 1.25, which means a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, ETF Series will likely underperform.
Auto-correlation | 0.34 |
Below average predictability
ETF Series Solutions has below average predictability. Overlapping area represents the amount of predictability between ETF Series time series from 9th of February 2023 to 5th of January 2024 and 5th of January 2024 to 30th 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 0.34 indicates that nearly 34.0% of current ETF Series price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.34 | |
| Spearman Rank Test | 0.36 | |
| Residual Average | 0.0 | |
| Price Variance | 1.21 |
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 |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether ETF Series Solutions is a strong investment it is important to analyze ETF Series' competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact ETF Series' future performance. For an informed investment choice regarding ETF Etf, refer to the following important reports: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 Price Ceiling Movement module to calculate and plot Price Ceiling Movement for different equity instruments.
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.