Dimensional Etf Trust Etf Market Value
| DFNM Etf | USD 48.59 0.14 0.29% |
| Symbol | Dimensional |
Understanding Dimensional ETF Trust requires distinguishing between market price and book value, where the latter reflects Dimensional's accounting equity. The concept of intrinsic value - what Dimensional ETF's is actually worth based on fundamentals - guides informed investors toward better entry and exit points. Seasoned market participants apply comprehensive analytical frameworks to derive fundamental worth and identify mispriced opportunities. Market sentiment, economic cycles, and investor behavior can push Dimensional ETF's price substantially above or below its fundamental value.
It's important to distinguish between Dimensional ETF's intrinsic value and market price, which are calculated using different methodologies. Investment decisions regarding Dimensional ETF should consider multiple factors including financial performance, growth metrics, competitive position, and professional analysis. In contrast, Dimensional ETF's trading price reflects the actual exchange value where willing buyers and sellers reach mutual agreement.
Dimensional ETF '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 ETF'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 ETF.
| 12/05/2025 |
| 03/05/2026 |
If you would invest 0.00 in Dimensional ETF on December 5, 2025 and sell it all today you would earn a total of 0.00 from holding Dimensional ETF Trust or generate 0.0% return on investment in Dimensional ETF over 90 days. Dimensional ETF is related to or competes with Matthews International, ProShares Equities, WisdomTree Emerging, IShares MSCI, US Global, John Hancock, and MicroSectors Travel. Under normal market conditions, the Portfolio will invest at least 80 percent of its net assets in municipal securities ... More
Dimensional ETF 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 ETF'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 ETF Trust upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1099 | |||
| Information Ratio | (0.27) | |||
| Maximum Drawdown | 0.4129 | |||
| Value At Risk | (0.08) | |||
| Potential Upside | 0.1249 |
Dimensional ETF Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Dimensional ETF's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Dimensional ETF's standard deviation. In reality, there are many statistical measures that can use Dimensional ETF historical prices to predict the future Dimensional ETF's volatility.| Risk Adjusted Performance | 0.1432 | |||
| Jensen Alpha | 0.0133 | |||
| Total Risk Alpha | 0.0101 | |||
| Sortino Ratio | (0.19) | |||
| Treynor Ratio | 1.81 |
Dimensional ETF March 5, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.1432 | |||
| Market Risk Adjusted Performance | 1.82 | |||
| Mean Deviation | 0.0519 | |||
| Downside Deviation | 0.1099 | |||
| Coefficient Of Variation | 325.3 | |||
| Standard Deviation | 0.0768 | |||
| Variance | 0.0059 | |||
| Information Ratio | (0.27) | |||
| Jensen Alpha | 0.0133 | |||
| Total Risk Alpha | 0.0101 | |||
| Sortino Ratio | (0.19) | |||
| Treynor Ratio | 1.81 | |||
| Maximum Drawdown | 0.4129 | |||
| Value At Risk | (0.08) | |||
| Potential Upside | 0.1249 | |||
| Downside Variance | 0.0121 | |||
| Semi Variance | (0.02) | |||
| Expected Short fall | (0.06) | |||
| Skewness | (1.14) | |||
| Kurtosis | 4.37 |
Dimensional ETF Trust Backtested Returns
As of now, Dimensional Etf is very steady. Dimensional ETF Trust secures Sharpe Ratio (or Efficiency) of 0.33, which denotes the etf had a 0.33 % return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Dimensional ETF Trust, which you can use to evaluate the volatility of the entity. Please confirm Dimensional ETF's Mean Deviation of 0.0519, coefficient of variation of 325.3, and Standard Deviation of 0.0768 to check if the risk estimate we provide is consistent with the expected return of 0.0258%. The etf shows a Beta (market volatility) of 0.0075, which means not very significant fluctuations relative to the market. As returns on the market increase, Dimensional ETF's returns are expected to increase less than the market. However, during the bear market, the loss of holding Dimensional ETF is expected to be smaller as well.
Auto-correlation | 0.90 |
Excellent predictability
Dimensional ETF Trust has excellent predictability. Overlapping area represents the amount of predictability between Dimensional ETF time series from 5th of December 2025 to 19th of January 2026 and 19th of January 2026 to 5th of March 2026. 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 ETF Trust price movement. The serial correlation of 0.9 indicates that approximately 90.0% of current Dimensional ETF price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.9 | |
| Spearman Rank Test | 0.95 | |
| Residual Average | 0.0 | |
| Price Variance | 0.03 |
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Dimensional ETF 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.