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 a 100% stock mix built entirely from seven equity ETFs, with no bonds or cash included in the analysis. About one‑third sits in a broad US large‑cap index, while the rest is spread across US and international value strategies, Japan, emerging markets, and developed ex‑US markets. The structure blends plain market exposure with more focused factor funds, especially in small‑cap and value styles. That combination means returns mainly depend on global stock markets, but not in the same proportions as a world index. The “Balanced” risk label and 4/7 score reflect this: risk is moderated by diversification across countries and company sizes, but stays meaningfully higher than a portfolio that mixes in bonds or cash.
From late 2021 to April 2026, a hypothetical $1,000 in this portfolio grew to $1,784, for a compound annual growth rate (CAGR) of 13.61%. CAGR is the “average speed” of growth per year, smoothing out the bumps. Over the same period, the US market grew at 11.93% and the global market at 10.22%, so this mix outpaced both references. The worst peak‑to‑trough fall, or max drawdown, was -21.5%, slightly milder than the benchmarks’ deeper drops. That combination—higher return with a somewhat smaller drawdown—is a positive sign for this window. Still, it’s one specific cycle; past performance doesn’t guarantee the same outcome in different interest‑rate or valuation environments.
The 15‑year Monte Carlo projection uses the portfolio’s past behavior to simulate many possible future paths. Monte Carlo is basically a big “what if” engine: it shakes returns around randomly, thousands of times, following historical patterns to see a range of outcomes. Here, the median scenario turns $1,000 into about $2,779, implying an annualized 8.18% across all simulations. The middle band (25th–75th percentile) runs from roughly $1,816 to $4,268, while extreme but plausible paths stretch from about $980 to $7,554. These numbers highlight how wide long‑term equity outcomes can be, even with the same starting portfolio. They’re useful for understanding risk, but they’re still models, not promises, and can’t capture unknown future events.
All of the portfolio is invested in stocks, with 0% allocated to bonds, cash, or alternative assets. That makes it straightforward to understand: returns and volatility are fully driven by global equities rather than interest income or bond price moves. Compared with a more mixed asset allocation, this leads to higher growth potential but also sharper swings, because there’s no cushion from defensive assets. Within equities, diversification comes from owning thousands of companies indirectly through broad ETFs rather than single stocks. This structure is consistent with the “Balanced” risk tag largely because of how widely those stocks are spread, not because of any fixed‑income stabilizer. In a severe equity downturn, the whole portfolio would still tend to move down together more than a stock‑bond blend.
Sector exposure is fairly well spread, with technology at about 20%, financials 18%, industrials 15%, and consumer discretionary 13%. Energy, telecom, health care, basic materials, and consumer staples each take mid‑single‑digit slices, while real estate and utilities are small at around 2% each. This balance is reasonably close to a typical global equity mix, which is often tech‑heavy but still broad. Such distribution helps avoid having the whole portfolio ride on a single industry’s fortunes. For example, a portfolio dominated by one growth sector might be more sensitive to interest‑rate changes, while this one would likely see different parts leading or lagging at different times. The spread across cyclicals, defensives, and growth areas supports the “broadly diversified” label.
Geographically, about 62% of exposure is in North America, with Japan at 15%, developed Europe around 9%, and developed Asia plus Australasia making up another chunk. Smaller pieces sit in Latin America, emerging Asia, emerging Europe, and Africa/Middle East. Compared with a purely global market index, this mix leans slightly more into Japan and keeps a large, but not extreme, home‑bias toward the US. That pattern broadens currency and economic drivers beyond a single region, reducing reliance on any one policy regime or macro story. It also means returns will be influenced by how different regions perform relative to each other—for example, if Japan or certain emerging markets have distinct cycles compared with North America.
By market cap, the portfolio spans the full spectrum: around 30% in mega‑caps, 23% in large‑caps, 20% in mid‑caps, 16% in small‑caps, and about 9% in micro‑caps. That’s a noticeably larger tilt to smaller companies than a typical global index, which is usually heavily dominated by mega and large caps. Smaller firms tend to be more volatile and sensitive to the economic cycle, but historically they have sometimes offered higher long‑term returns. Combined with the value focus of several ETFs, this size mix gives the portfolio a more “all‑terrain” equity flavor—less tethered to the biggest household names. It also means that a meaningful part of performance will come from less widely followed companies rather than just the global giants.
Looking through ETF top‑10 holdings, a handful of big names show up repeatedly: Apple, NVIDIA, Microsoft, Amazon, Samsung Electronics, Meta, Alphabet, TSMC, Broadcom, and SK Hynix. Together, these account for only a few percent of the total portfolio, which is modest given their dominance in many indices. Because only top‑10 ETF holdings are captured, actual overlap is somewhat understated, but the available data suggests hidden concentration in these mega‑cap tech and semiconductor leaders is limited. That’s consistent with the portfolio’s stronger exposure to smaller and value‑oriented stocks. It means the portfolio still participates in the performance of the major global growth companies, but they don’t fully drive overall risk and return the way they might in a pure cap‑weighted index portfolio.
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 show clear tilts: value is high at 71%, quality at 60%, and yield at 61%, while size, momentum, and low volatility sit around neutral. Factors are like underlying “themes” that help explain stock behavior—value favors cheaper companies, quality emphasizes stronger balance sheets, and yield leans a bit toward higher dividends. A strong value tilt often behaves differently from growth‑heavy markets: it may lag during speculative booms but can hold up relatively better when investors rotate toward earnings and cash flows. The quality and yield tilts can add a stabilizing influence, since profitable, dividend‑paying businesses have sometimes been more resilient in downturns. Overall, the factor mix is meaningfully distinct from a plain market index, with a clear value‑quality identity.
Risk contribution shows how much each ETF drives the portfolio’s ups and downs, which can differ from its simple weight. Here, the S&P 500 ETF is 30% of the portfolio and contributes about 29% of total risk—almost one‑for‑one. The US small‑cap value ETF is 20% by weight but contributes a higher 24.5% of risk, reflecting its greater volatility; its risk/weight ratio of 1.22 highlights that extra punch. The emerging markets ETF, at 10% weight and about 10% risk share, lines up closely with its size. The top three positions together account for roughly 63% of overall risk, which is a notable but not extreme concentration. This pattern shows that position sizing generally matches risk impact, with one slightly “louder” holding in small‑cap value.
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 with a Sharpe ratio of 0.62, compared with 1.04 for the “optimal” mix of the same holdings and 0.84 for the minimum variance blend. The Sharpe ratio measures return per unit of risk, using a 4% risk‑free rate, like asking how much extra reward you’re getting for each unit of volatility. The current setup sits about 3.97 percentage points below the efficient frontier at its risk level, meaning there are alternative weightings of these same ETFs that would historically have given a better balance. The minimum variance portfolio reaches broadly similar expected returns with lower risk, while the max‑Sharpe mix boosts expected return with only slightly more volatility. This highlights room for efficiency purely through reweighting.
The overall dividend yield clocks in around 1.77%, with individual ETFs ranging from roughly 1.1% to 3.4%. Yield is the cash income from dividends as a percentage of current value, separate from price changes. The higher‑yielding pieces come mainly from international and Japan exposures, which traditionally distribute more cash than many US growth stocks. Combined with the portfolio’s value and yield factor tilts, this suggests that dividends are a meaningful, though not dominant, part of total return. In strong markets, price appreciation will likely overshadow this income component; in flatter periods, dividends can play a bigger psychological and financial role by providing some return even when prices are not moving much.
The weighted ongoing fee, or TER, for this portfolio is about 0.17% per year, with individual ETF costs ranging from 0.03% to 0.49%. TER (Total Expense Ratio) is the annual management cost baked into the fund, quietly deducted before returns are reported. A 0.17% average is impressively low for a mix that includes factor, small‑cap, and emerging markets strategies, which are often pricier. Lower fees matter because they compound: every dollar not spent on costs stays invested to potentially grow over time. Compared with many actively managed options, this structure keeps cost drag modest while still accessing a range of styles and regions. That provides a solid base for long‑term compounding from the underlying assets rather than from the fee structure.
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