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 straightforward, fully equity mix built from five broad stock ETFs. Around two thirds sits in US large caps, split between growth and value, while the rest spreads across US mid and small caps plus a single global ex‑US fund. The structure is simple and easy to understand: one big engine in US large growth, a meaningful diversifier in international stocks, and smaller allocations to size segments. This kind of setup makes performance mainly driven by stock markets rather than bonds or cash. It also means ups and downs will closely track global equity cycles, with a particular sensitivity to what happens in large US companies.
From 2016 to 2026, a $1,000 hypothetical investment grew to about $3,783, which translates to a 14.3% compound annual growth rate (CAGR). CAGR is like the average speed of a car on a long trip, smoothing out bumps along the way. This was slightly behind the US market benchmark but comfortably ahead of the global benchmark, showing the US tilt has historically helped. The worst peak‑to‑trough drop was about –34.5% during early 2020, similar to broad markets. Only 33 trading days generated 90% of the total return, underlining how a handful of strong days can shape long‑term results and why staying invested matters for capturing them. Past performance, of course, doesn’t guarantee future outcomes.
The Monte Carlo projection uses 1,000 simulated paths based on historical patterns to estimate how $1,000 might evolve over 15 years. Think of it as running the portfolio’s past behavior through a thousand “what if” futures to see a range of outcomes. The median result lands around $2,792, about an 8.2% annualized return across simulations, with a wide possible band from roughly $995 to $7,986. About 73.5% of simulations end positive, but there’s still a meaningful chance of flat or negative results. These numbers are not forecasts or promises; they simply show what could happen if markets behaved similarly to history, which they rarely do perfectly.
The portfolio is 100% in stocks, with no bonds, cash, or alternatives in the mix. That makes it clearly growth‑oriented and more sensitive to market swings than a blended stock‑bond portfolio. All return potential comes from company earnings and valuation changes rather than fixed income coupons. Compared to a classic “balanced” portfolio, this structure typically experiences larger drawdowns but also higher long‑term return potential. Relative to global equity benchmarks, being fully in stocks is aligned with a pure growth approach, but it also means there is no built‑in cushion from more defensive asset classes during major market downturns.
Sector exposure is led by technology at about 30%, with meaningful allocations to financials, industrials, consumer discretionary, telecom, and health care. Smaller slices go to staples, materials, energy, real estate, and utilities. This looks reasonably similar to broad equity benchmarks, though the higher tech share stands out and likely reflects the large‑cap growth component. A tech‑tilted portfolio can benefit when innovation‑driven and growth‑oriented companies are in favor, but it may feel sharper moves when interest rates rise or when investors rotate toward more defensive or value‑oriented segments. The presence of all major sectors still gives a solid baseline of diversification across different parts of the economy.
Geographically, about 77% of the portfolio sits in North America, with the remainder spread across Europe, Japan, developed Asia, emerging Asia, Australasia, Latin America, and Africa/Middle East. Global equity indexes today usually have something like 60% exposure to the US, so this portfolio’s North America share is meaningfully higher than “world market weight.” That has helped over the past decade, since US stocks outperformed many regions, which shows up in the strong returns versus the global benchmark. The trade‑off is a heavier dependence on the US economy, policy, and dollar movements, while still having a decent but secondary exposure to the rest of the world.
By market capitalization, the portfolio leans toward larger companies: around 42% in mega caps and 26% in large caps, with the remainder in mid (19%), small (10%), and micro caps (2%). This pattern is close to a typical global equity breakdown but with a slightly more noticeable presence in the smaller segments thanks to dedicated mid‑ and small‑cap funds. Larger companies generally bring more stability and liquidity, while smaller ones can be more volatile but sometimes offer stronger growth spurts. This mix provides exposure to well‑established names that drive broad indexes, while still leaving room for company‑specific growth stories further down the size spectrum.
Looking through the ETFs, the largest underlying exposures include NVIDIA, Apple, Microsoft, Amazon, Alphabet (both share classes), Broadcom, Meta, Tesla, and Eli Lilly. Each of these sits around 1–5% of the overall portfolio once overlap is combined. Many appear in multiple funds, which increases their effective weight and creates hidden concentration: for instance, the same mega‑cap tech name can be held across growth, value, and international funds. Coverage is based only on ETF top‑10 holdings, so overall overlap is likely understated. This pattern is typical for index‑based portfolios but is still useful to recognize, because a handful of big companies can drive a significant share of total returns and volatility.
Factor exposure is broadly neutral across all measured dimensions: value, size, momentum, quality, low volatility, and yield all cluster near 50%. Factor exposure is like checking what “traits” the portfolio leans into, such as cheapness (value) or trendiness (momentum). A neutral profile suggests it behaves similarly to a broad market index rather than expressing strong tilts toward specific styles. In practice, that means the portfolio is likely to track general equity market cycles fairly closely, without major outperformance or underperformance that’s systematically tied to any one factor. This kind of balance is quite aligned with a core, index‑style approach, where the goal is to capture broad market behavior.
Risk contribution shows how much each holding drives overall ups and downs, which can differ from its simple weight. The Schwab US Large‑Cap Growth ETF is 45% of the portfolio but contributes about 50.5% of total risk, so it punches slightly above its size. The international fund carries 25% of the weight but about 21% of risk, and the large‑cap value ETF is similar, each adding a bit less risk than their weights. Mid and small caps roughly match or slightly exceed their allocations in risk terms. Altogether, the top three holdings account for 84% of total risk, reflecting a concentrated core where one main position is the key driver of volatility.
The correlation view highlights that the Schwab US Small‑Cap and Mid‑Cap ETFs move almost identically. Correlation measures how often assets move in the same direction; a value close to 1 means they tend to rise and fall together. When two holdings are highly correlated, owning both doesn’t add much diversification benefit, even if they target different size segments. Here, the separate mid‑ and small‑cap slices still diversify away from the largest companies, but within that part of the portfolio their return patterns are strongly linked. This helps explain why their risk contribution is roughly proportional to their weights despite being separate positions.
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.
On the risk‑return chart, the current portfolio sits very close to the efficient frontier, which is the curve showing the best return achievable for each risk level using only these holdings. The Sharpe ratio, which measures return per unit of volatility above the risk‑free rate, is 0.58 for the current mix, compared with 0.83 for the optimal and 0.62 for the minimum‑variance portfolio. Being on or near the frontier means the chosen weights already make efficient use of the building blocks: there isn’t a big gap where a simple reweighting would obviously improve risk‑adjusted returns. That’s a strong structural sign that the combination hangs together well.
The overall dividend yield is about 1.32%, with the highest yields in the international and US large‑cap value ETFs, and lower yields in the growth and small‑cap funds. Dividend yield is the annual cash payout as a percentage of the investment value, like rent from owning shares. In this portfolio, most of the expected return still comes from price appreciation rather than income. That’s typical for a growth‑leaning, equity‑heavy mix. The moderate yield can still meaningfully contribute to total returns over time, especially if dividends are reinvested, but it won’t behave like a high‑income portfolio where payouts are a primary feature.
Costs are impressively low across the board. Each Schwab ETF charges a total expense ratio (TER) of 0.04%, and the Vanguard international ETF charges 0.05%, leaving the weighted portfolio TER at roughly 0.04%. TER is the annual fee, expressed as a percentage, that quietly comes out of fund assets. Over long horizons, small differences in fees can compound into meaningful gaps in investor outcomes. In this case, the cost structure aligns with some of the cheapest index funds available, providing a strong foundation where more of the portfolio’s gross returns can show up as net returns. This is a clear structural strength of the setup.
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