Dimensional Core Equity Etf Market Value
DFAC Etf | USD 36.27 0.25 0.68% |
Symbol | Dimensional |
The market value of Dimensional Core Equity 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 Core's value that differs from its market value or its book value, called intrinsic value, which is Dimensional Core'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 Core's market value can be influenced by many factors that don't directly affect Dimensional Core'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 Core's value and its price as these two are different measures arrived at by different means. Investors typically determine if Dimensional Core is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Dimensional Core'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 Core '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 Core'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 Core.
04/05/2025 |
| 07/04/2025 |
If you would invest 0.00 in Dimensional Core on April 5, 2025 and sell it all today you would earn a total of 0.00 from holding Dimensional Core Equity or generate 0.0% return on investment in Dimensional Core over 90 days. Dimensional Core is related to or competes with Freedom Day, Davis Select, IShares MSCI, SmartETFs Dividend, Tidal ETF, Listed Funds, and Principal Value. The fund is designed to purchase a broad and diverse group of securities of U.S More
Dimensional Core 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 Core'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 Core Equity upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.94 | |||
Information Ratio | 0.0335 | |||
Maximum Drawdown | 12.89 | |||
Value At Risk | (2.21) | |||
Potential Upside | 2.08 |
Dimensional Core Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Dimensional Core's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Dimensional Core's standard deviation. In reality, there are many statistical measures that can use Dimensional Core historical prices to predict the future Dimensional Core's volatility.Risk Adjusted Performance | 0.1538 | |||
Jensen Alpha | 0.1724 | |||
Total Risk Alpha | 0.048 | |||
Sortino Ratio | 0.032 | |||
Treynor Ratio | (1.99) |
Dimensional Core Equity Backtested Returns
Dimensional Core appears to be very steady, given 3 months investment horizon. Dimensional Core Equity secures Sharpe Ratio (or Efficiency) of 0.21, which denotes the etf had a 0.21 % return per unit of risk over the last 3 months. We have found thirty technical indicators for Dimensional Core Equity, which you can use to evaluate the volatility of the entity. Please utilize Dimensional Core's Mean Deviation of 1.07, downside deviation of 1.94, and Coefficient Of Variation of 1068.85 to check if our risk estimates are consistent with your expectations. The etf shows a Beta (market volatility) of -0.0825, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Dimensional Core are expected to decrease at a much lower rate. During the bear market, Dimensional Core is likely to outperform the market.
Auto-correlation | 0.85 |
Very good predictability
Dimensional Core Equity has very good predictability. Overlapping area represents the amount of predictability between Dimensional Core time series from 5th of April 2025 to 20th of May 2025 and 20th of May 2025 to 4th of July 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 Dimensional Core Equity price movement. The serial correlation of 0.85 indicates that around 85.0% of current Dimensional Core price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.85 | |
Spearman Rank Test | 0.87 | |
Residual Average | 0.0 | |
Price Variance | 0.48 |
Dimensional Core Equity lagged returns against current returns
Autocorrelation, which is Dimensional Core 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 Core's etf expected returns. We can calculate the autocorrelation of Dimensional Core returns to help us make a trade decision. For example, suppose you find that Dimensional Core 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 Core 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 Core etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Dimensional Core etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Dimensional Core etf over time.
Current vs Lagged Prices |
Timeline |
Dimensional Core Lagged Returns
When evaluating Dimensional Core's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Dimensional Core etf have on its future price. Dimensional Core 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 Core autocorrelation shows the relationship between Dimensional Core etf current value and its past values and can show if there is a momentum factor associated with investing in Dimensional Core Equity.
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.VREX | Varex Imaging Corp | |
ENPH | Enphase Energy | |
BDC | Belden Inc |
Check out Dimensional Core Correlation, Dimensional Core Volatility and Dimensional Core Alpha and Beta module to complement your research on Dimensional Core. You can also try the Positions Ratings module to determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Dimensional Core 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.