This portfolio is heavily weighted towards U.S. large-cap growth stocks, with a significant 78.29% allocation to a Schwab U.S. Large-Cap Growth ETF and the remainder in a Schwab U.S. Dividend Equity ETF. The diversification is low, focusing primarily on the stock asset class within the North American market. The sectoral distribution is tech-heavy, making up 42% of the portfolio, followed by consumer cyclicals and communication services. The portfolio's risk classification is growth-oriented, with a risk score of 5 out of 7, indicating a higher appetite for risk.
Historically, the portfolio has achieved a Compound Annual Growth Rate (CAGR) of 17.89%, with a maximum drawdown of -32.50%. The days contributing to 90% of returns number 39, highlighting that a few significant days have driven most of the portfolio's performance. This performance suggests high volatility but also the potential for substantial returns, fitting a growth profile.
Monte Carlo simulations, which use historical data to forecast a range of possible outcomes, predict a wide dispersion in future portfolio values. With all 1,000 simulations showing positive returns, the 50th percentile outcome indicates a 661.1% increase, underlining the portfolio's high growth potential. However, reliance on past performance and the inherent uncertainty in projections should be tempered with caution.
The portfolio is entirely invested in stocks, with no allocation to other asset classes like bonds or real estate. This singular focus on equities enhances growth potential but also increases risk, particularly in market downturns. Diversification across asset classes can mitigate risk while still allowing for significant growth opportunities.
A 42% allocation to technology sectors positions the portfolio for high growth but also exposes it to sector-specific risks, such as regulatory changes or market sentiment shifts. The presence of consumer cyclicals and communication services further skews the portfolio towards high-growth, high-volatility sectors. Balancing with more defensive sectors could reduce volatility.
The portfolio's geographic allocation is entirely to North America, missing out on potential growth and diversification benefits from developed European markets or emerging markets. This concentration increases exposure to region-specific economic and political risks.
With 51% in mega-cap stocks, the portfolio leans towards companies with large market capitalizations, which are typically less volatile but also offer lower growth rates than smaller companies. The mix of big, medium, and a small percentage in small-cap stocks suggests a moderate approach to balancing stability and growth potential.
This chart shows the Efficient Frontier, calculated using your current assets with different allocation combinations. It highlights the best balance between risk and return based on historical data. "Efficient" portfolios maximize returns for a given risk or minimize risk for a given return. Portfolios below the curve are less efficient. This is informational and not a recommendation to buy or sell any assets.
Click on the colored dots to explore allocations.
Considering the portfolio's current risk-return profile, optimizing along the Efficient Frontier could involve diversifying across more asset classes and geographic regions. This optimization aims to achieve the best possible risk-return ratio, potentially enhancing returns for the same level of risk or reducing risk for the same expected return.
The portfolio's overall dividend yield of 1.14% reflects a balance between the high-growth, low-yield large-cap growth ETF and the higher-yield dividend equity ETF. While dividends contribute to total returns, the primary focus here appears to be on capital appreciation rather than income generation.
The portfolio benefits from low costs, with total expense ratios (TER) averaging 0.04%. Low costs are crucial for long-term growth, as they allow more of the investment's return to compound over time. This efficient cost structure is a strong positive feature of the portfolio.
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