PortfolioMetrics

JPST vs. JQUA - ETF Comparison

JPST - JPMorgan Ultra-Short Income ETF

The JPMorgan Ultra-Short Income ETF is an actively managed fund that invests in short-term investment-grade debt, aiming to provide a relatively safe way to generate yield for investors. It capitalizes on JPMorgan's reputation for cash management and offers a low-cost solution.

JQUA - JPMorgan U.S. Quality Factor ETF

The JPMorgan U.S. Quality Factor ETF is an equity fund that tracks a proprietary index, selecting large- and mid-cap U.S. stocks based on quality, profitability, and solvency. The fund provides investors with a quality tilt on top of a core allocation to U.S. markets.

JPSTJQUA
Fund NameJPMorgan Ultra-Short Income ETFJPMorgan U.S. Quality Factor ETF
Fund ProviderJPMorgan ChaseJPMorgan Chase
IndexActive (No Index)JP Morgan US Quality Factor Index
Asset ClassBondsEquity
ListingUS-listedUS-listed
Expense Ratio0.18%0.12%
Inception Date2017-05-172017-11-08
Number Of Holdings572276
CurrencyUSDUSD
RegionUnited StatesUnited States
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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