Dimensional Equity Etf Market Value
| DFUS Etf | USD 65.48 0.20 0.30% |
| Symbol | Dimensional |
The market value of Dimensional Equity ETF is measured differently than its book value, which is the value of Dimensional that is recorded on the company's balance sheet. Investors also form their own opinion of Dimensional Equity's value that differs from its market value or its book value, called intrinsic value, which is Dimensional Equity'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 Dimensional Equity's market value can be influenced by many factors that don't directly affect Dimensional Equity'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 Dimensional Equity's value and its price as these two are different measures arrived at by different means. Investors typically determine if Dimensional Equity is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Dimensional Equity'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.
Dimensional Equity '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 Dimensional Equity'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 Dimensional Equity.
| 06/08/2023 |
| 11/29/2024 |
If you would invest 0.00 in Dimensional Equity on June 8, 2023 and sell it all today you would earn a total of 0.00 from holding Dimensional Equity ETF or generate 0.0% return on investment in Dimensional Equity over 540 days. Dimensional Equity is related to or competes with Vanguard Total, SPDR SP, IShares Core, Vanguard Dividend, Vanguard Large, Invesco SP, and IShares Russell. As a non-fundamental policy, under normal circumstances, the fund will invest at least 80 percent of its net assets in s... More
Dimensional Equity 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 Dimensional Equity'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 Dimensional Equity ETF upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.8446 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 4.27 | |||
| Value At Risk | (1.33) | |||
| Potential Upside | 1.19 |
Dimensional Equity Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Dimensional Equity's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Dimensional Equity's standard deviation. In reality, there are many statistical measures that can use Dimensional Equity historical prices to predict the future Dimensional Equity's volatility.| Risk Adjusted Performance | 0.1111 | |||
| Jensen Alpha | 0.002 | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.1175 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Dimensional Equity'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.
Dimensional Equity ETF Backtested Returns
Currently, Dimensional Equity ETF is very steady. Dimensional Equity ETF secures Sharpe Ratio (or Efficiency) of 0.2, which denotes the etf had a 0.2% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Dimensional Equity ETF, which you can use to evaluate the volatility of the entity. Please confirm Dimensional Equity's Downside Deviation of 0.8446, mean deviation of 0.5848, and Coefficient Of Variation of 693.88 to check if the risk estimate we provide is consistent with the expected return of 0.15%. The etf shows a Beta (market volatility) of 0.92, which means possible diversification benefits within a given portfolio. Dimensional Equity returns are very sensitive to returns on the market. As the market goes up or down, Dimensional Equity is expected to follow.
Auto-correlation | 0.72 |
Good predictability
Dimensional Equity ETF has good predictability. Overlapping area represents the amount of predictability between Dimensional Equity time series from 8th of June 2023 to 4th of March 2024 and 4th of March 2024 to 29th 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 Dimensional Equity ETF price movement. The serial correlation of 0.72 indicates that around 72.0% of current Dimensional Equity price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.72 | |
| Spearman Rank Test | 0.67 | |
| Residual Average | 0.0 | |
| Price Variance | 8.89 |
Dimensional Equity ETF lagged returns against current returns
Autocorrelation, which is Dimensional Equity 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 Dimensional Equity's etf expected returns. We can calculate the autocorrelation of Dimensional Equity returns to help us make a trade decision. For example, suppose you find that Dimensional Equity 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 |
Dimensional Equity 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 Dimensional Equity etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Dimensional Equity etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Dimensional Equity etf over time.
Current vs Lagged Prices |
| Timeline |
Dimensional Equity Lagged Returns
When evaluating Dimensional Equity's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Dimensional Equity etf have on its future price. Dimensional Equity 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, Dimensional Equity autocorrelation shows the relationship between Dimensional Equity etf current value and its past values and can show if there is a momentum factor associated with investing in Dimensional Equity ETF.
Regressed Prices |
| Timeline |
Thematic Opportunities
Explore Investment Opportunities
Check out Dimensional Equity Correlation, Dimensional Equity Volatility and Dimensional Equity Alpha and Beta module to complement your research on Dimensional Equity. You can also try the Equity Analysis module to research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities.
Dimensional Equity 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.