The risk profile, derived from past market volatility, reflects the level of risk the portfolio is exposed to. This assessment helps align your investments with your financial goals and comfort with market fluctuations.
The diversification assessment evaluates the spread of investments across asset classes, regions, and sectors. This ensures a balanced mix, reducing risk and maximizing returns by not concentrating in any single area.
This portfolio is very straightforward: three US-listed stock ETFs, with 75% in a broad US large-cap fund, 20% in a growth-heavy large-cap fund, and 5% in a more diversified iShares ETF that includes some bonds. That creates a mostly equity portfolio with a small stabilizing bond sleeve. Simple structures like this are easy to understand and track, which is useful for staying disciplined over time. The main implication is that portfolio behavior will largely mirror US stock markets, especially big household-name companies, with only a slight dampening effect from the bond piece and the broader exposure in the smallest ETF.
Over the period from mid‑2020 to April 2026, a $1,000 investment in this portfolio grew to about $2,534. That implies a compound annual growth rate (CAGR) of 17.17%, which means the portfolio grew on average 17.17% per year, smoothing out ups and downs. This slightly beat both the US market benchmark and the global market benchmark. The deepest peak‑to‑trough fall, or max drawdown, was about ‑25.9%, broadly in line with major equity markets. This behavior shows the portfolio captured strong equity returns but didn’t avoid the meaningful swings that come with stock-heavy exposure.
The forward projection uses a Monte Carlo simulation, which basically runs 1,000 “what if” scenarios using patterns from past returns and volatility. It shows a median outcome of about $2,808 from $1,000 over 15 years, with a wide range from around $1,057 to $7,507 (5th–95th percentile). The average annualized return across simulations is 8.17%, much lower than recent historical returns, emphasizing that future results may differ. Monte Carlo doesn’t predict a single future; it illustrates a range of possible paths so you can see how sensitive outcomes are to market swings, especially for a stock-heavy portfolio like this.
Asset allocation is heavily tilted to stocks at 95%, with a small 5% bond allocation. Stocks are generally the main drivers of long-term growth but tend to be more volatile. Bonds often act like a cushion, helping to reduce the size of drawdowns, though they usually grow slower. Compared with typical “balanced” mixes, which often have much higher bond allocations, this portfolio leans more toward growth than stability. That means its results will be more closely tied to equity market cycles, with limited ballast from fixed income in sharp downturns, but also more upside participation during strong equity rallies.
This breakdown covers the equity portion of your portfolio only.
Sector exposure is notably skewed toward technology at 35%, above what many broad equity benchmarks show, with additional weight in telecommunications and consumer discretionary. These sectors tend to be more sensitive to changes in interest rates, innovation cycles, and investor sentiment, which can increase volatility. Other sectors like financials, health care, and industrials have meaningful but smaller roles, while defensive areas such as utilities and consumer staples are modest. This pattern suggests the portfolio is tilted toward growth-oriented parts of the economy, which can support strong returns in favorable environments but may amplify drawdowns when sentiment turns against high-growth areas.
This breakdown covers the equity portion of your portfolio only.
Geographically, the portfolio is overwhelmingly focused on North America at 94%, with only a small slice in developed Europe and essentially no exposure elsewhere. This close alignment with US markets has helped in the recent decade, when US equities often outpaced many other regions. However, it also means performance is tightly tied to one economic region, currency, and policy environment. Relative to global benchmarks that spread more across regions, this portfolio accepts less geographic diversification. If US markets outperform, this concentration helps; if they lag other areas, the portfolio won’t benefit much from those foreign market advances.
This breakdown covers the equity portion of your portfolio only.
By market capitalization, the portfolio is dominated by mega‑cap and large‑cap stocks, together about 78%, with smaller slices in mid‑caps and very little in small‑caps. Large and mega‑caps tend to be more established companies with broad analyst coverage and, often, more stable business models. They can still be volatile, but typically less so than very small companies. On the other hand, smaller-cap stocks can sometimes provide different return patterns and diversification benefits. Here, the strong tilt toward the biggest companies means portfolio behavior is likely to track well-known indices, with less influence from smaller, more niche firms.
Looking through ETF top holdings, a handful of big names account for a meaningful portion of total exposure: for example, NVIDIA at 7.45%, Apple at 6.45%, and Microsoft at 4.78%, with several other tech and mega‑cap names close behind. These companies appear across multiple ETFs, creating “hidden” concentration where the same stock shows up in different wrappers. Since only ETF top‑10 holdings are used, overlap is likely understated. This means the portfolio’s fortunes are significantly tied to a small group of giant companies, which has been beneficial in recent years but also increases dependence on their continued strong performance.
Factor exposures are estimated using statistical models based on historical data and measure systematic (market-relative) tilts, not absolute portfolio characteristics. Results may vary depending on the analysis period, data availability, and currency of the underlying assets.
Factor exposures are generally close to neutral across value, momentum, quality, yield, and low volatility, meaning the portfolio behaves broadly like the overall market on these dimensions. Factor exposure describes how much a portfolio leans into styles such as value (cheap vs. expensive) or momentum (recent winners). The one notable tilt is size, with a low score of 40%, reflecting a mild tilt away from smaller companies and toward larger ones. This aligns with the market cap data and suggests returns will be driven more by large-cap dynamics than by size-related factor effects often seen in small‑cap heavy strategies.
Risk contribution measures how much each holding drives the portfolio’s overall ups and downs, which can differ from simple weight. Here, the Vanguard S&P 500 ETF is 75% of assets and contributes about 74% of risk, closely aligned. The QQQ position is 20% of assets but contributes roughly 26% of the risk, meaning it is somewhat more volatile than its weight alone suggests. The small iShares position currently shows negligible risk contribution. Overall, risk is effectively shared between the two big equity funds, with QQQ adding an extra kick to volatility beyond its size, consistent with its growth-heavy profile.
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.
The risk‑return chart shows the current portfolio sitting on or very near the efficient frontier, which is the curve representing the best expected return for each risk level using only the existing holdings. The Sharpe ratio, a measure of risk‑adjusted return comparing excess return to volatility, is 0.78 for the current mix and 0.96 for the mathematically optimal mix using the same components. That suggests only modest improvements are possible through reweighting. This alignment indicates the portfolio is already quite efficient for its chosen risk level, with no obvious structural inefficiencies in how the three holdings are combined.
The portfolio’s overall dividend yield is about 1.10%, with the broad S&P 500 ETF around that level, QQQ at a lower 0.40%, and the iShares holding providing a higher 3.90%. Dividend yield reflects how much cash income you get each year as a percentage of the investment value. Here, income plays a smaller supporting role, with most of the total return historically coming from price changes rather than payouts. That’s consistent with a growth‑oriented, large‑cap US equity focus. For investors who reinvest dividends, these steady, if modest, cash flows can quietly compound over time alongside capital gains.
Costs are impressively low, with a total expense ratio (TER) around 0.07%. TER is the annual fee charged by funds, expressed as a percentage of assets, and it comes out of returns automatically. Low costs matter because they compound over long periods; paying less in fees means more of the portfolio’s gross performance stays in the account. The largest holding uses one of the lowest‑cost broad market ETFs available, and even the growth‑oriented fund’s 0.20% fee is reasonable by industry standards. This cost structure is a strong foundation that supports better long‑term performance relative to higher‑fee alternatives.
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