FEBB vs. OSX4 - ETF Comparison
FEBB - First Trust Vest U.S. Equity Moderate Buffer UCITS ETF - February Class A Accumulation
The First Trust Vest U.S. Equity Moderate Buffer UCITS ETF - February Class A Accumulation is an actively managed ETF that tracks the performance of the S&P 500 while using put options to buffer investors against the first 15% of losses each year. The ETF has a total expense ratio of 0.85% and is domiciled in Ireland.
OSX4 - Ossiam Europe ESG Machine Learning UCITS ETF 1C (EUR)
The Ossiam Europe ESG Machine Learning UCITS ETF 1C (EUR) is an actively managed equity ETF that tracks companies from Eurozone countries selected according to environmental, social, and corporate governance (ESG) criteria. The fund uses machine learning techniques to select stocks and has an expense ratio of 0.65%. It is a small ETF with approximately €19 million in assets under management, domiciled in Luxembourg, and launched on February 3, 2012.
| FEBB | OSX4 | |
|---|---|---|
| Fund Name | First Trust Vest U.S. Equity Moderate Buffer UCITS ETF - February Class A Accumulation | Ossiam Europe ESG Machine Learning UCITS ETF 1C (EUR) |
| Fund Provider | First Trust | Ossiam |
| Index | First Trust Vest U.S. Equity Moderate Buffer | Ossiam Europe ESG Machine Learning |
| Asset Class | Equity | Equity |
| Listing | EU-listed | EU-listed |
| Expense Ratio | 0.85% | 0.65% |
| Inception Date | 2024-02-19 | 2012-02-03 |
| Currency | USD | EUR |
| Distribution Policy | Accumulating | Accumulating |
| Region | United States | Europe |
| Investment Style | Active | Active |
| 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.