DFGR vs. DFAR - ETF Comparison
DFGR - Dimensional Global Real Estate ETF
The Dimensional Global Real Estate ETF is an actively managed fund that invests in a diversified portfolio of global real estate companies, aiming to provide long-term capital appreciation and income.
DFAR - Dimensional US Real Estate ETF
The Dimensional US Real Estate ETF is an actively managed fund that invests in a diversified portfolio of US real estate companies, aiming to provide long-term capital appreciation and income.
DFGR | DFAR | |
---|---|---|
Fund Name | Dimensional Global Real Estate ETF | Dimensional US Real Estate ETF |
Fund Provider | Dimensional | Dimensional |
Index | Active (No Index) | Active (No Index) |
Asset Class | Equity | Equity |
Listing | US-listed | US-listed |
Expense Ratio | 0.22% | 0.19% |
Inception Date | 2022-12-06 | 2022-02-23 |
Number Of Holdings | 443 | 133 |
Currency | USD | USD |
Region | Global | United States |
Investment Style | Active | Active |
Market Cap | Blend | Blend |
Sector | Real Estate | Real Estate |
Leveraged | Non-leveraged | Non-leveraged |
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Key Metrics
Performance Metrics
Risk Metrics
Detailed Returns
Benchmark Comparison
Key Metrics
Performance Metrics
Risk Metrics
Detailed Returns
Benchmark Comparison
Performance Analysis
The performance analysis examines historical data to assess the returns of the investment strategy, including key metrics such as Cumulative returns, End of Year (EoY) returns, and risk-adjusted returns like the Sharpe ratio or the Sortino ratio.
Cumulative Returns
End of Year Returns Table
End of Year Returns
Risk Analysis
The risk analysis refers to an assessment of potential negative events that could lead to a loss of capital. Conducting a risk analysis can help in deciding whether an investment should be made. This is done using risk metrics such as drawdowns, volatility and beta which reflect stakeholders' confidence in the consistency of an investment strategy.
Drawdowns
Drawdowns Table
Monte Carlo Simulation
The Monte Carlo simulation is a statistical method used to forecast portfolio returns by generating a wide range of potential outcomes through random sampling from historical asset price data. It helps investors assess the potential risk and return of a portfolio under various market conditions. The simulation takes into account the initial investment and optionally simulates cash flow scenarios like fixed contributions, fixed withdrawals, or percentage withdrawals.
IMPORTANT: The forecast generated through Monte Carlo simulations is purely hypothetical and does not guarantee future returns. Investment decisions should be made with consideration of various factors, and past performance is not indicative of future results.