PortfolioMetrics

E500 vs. CMOD - ETF Comparison

E500 - Invesco S&P 500 EUR Hedged UCITS ETF

The Invesco S&P 500 EUR Hedged UCITS ETF is a large, Ireland-domiciled equity fund that tracks the S&P 500 index, providing exposure to the largest US stocks with currency hedging to Euro. It has a low expense ratio of 0.05% and follows a long-only, accumulating strategy.

CMOD - Invesco Bloomberg Commodity UCITS ETF Acc

The Invesco Bloomberg Commodity UCITS ETF Acc is a commodity-focused exchange-traded fund that tracks the Bloomberg Commodity index, providing exposure to a broad range of commodities including energy, precious metals, industrial metals, livestock, and agriculture.

E500CMOD
Fund NameInvesco S&P 500 EUR Hedged UCITS ETFInvesco Bloomberg Commodity UCITS ETF Acc
Fund ProviderInvescoInvesco
IndexS&P 500 (EUR Hedged)Bloomberg Commodity
Asset ClassEquityCommodity
ListingEU-listedEU-listed
Expense Ratio0.05%0.19%
Inception Date2014-12-082017-01-09
CurrencyEURUSD
Distribution PolicyAccumulatingAccumulating
RegionUnited StatesGlobal
LeveragedNon-leveragedNon-leveraged
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Key Metrics

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Performance Metrics

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Risk Metrics

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Detailed Returns

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Benchmark Comparison

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Key Metrics

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Performance Metrics

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Risk Metrics

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Detailed Returns

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Benchmark Comparison

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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

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End of Year Returns Table

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End of Year Returns

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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

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Drawdowns Table

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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.

Monte Carlo Metrics

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Simulated Portfolio Prices

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