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.
The portfolio is built from five equity ETFs, with no bonds or cash, so it’s a fully stock-based mix. About 40% sits in a broad US large-cap core fund, giving exposure to many well-known companies. Another 30% is in US small-cap value and 25% in international small- and large-cap value, adding a noticeable tilt toward smaller and cheaper stocks outside the main index. The remaining 10% targets a momentum strategy on US large caps. This structure combines a simple core with a few focused “satellites.” That design can keep things understandable while still adding distinct return drivers beyond a plain market index.
Over the period from late 2021 to mid-April 2026, a hypothetical $1,000 in this portfolio grew to about $1,812. That works out to a compound annual growth rate (CAGR) of 14.04%, meaning the value increased roughly 14% per year on average, like checking the average speed over a long trip. This outpaced both the US market (13.02%) and the global market (11.18%) over the same window. The worst peak‑to‑trough fall, or max drawdown, was about -23%, similar to the benchmarks. The fact that stronger returns came without deeper drawdowns suggests the mix of factors and size exposures has been additive historically, though past performance can’t guarantee similar results.
The Monte Carlo projection uses historical return and volatility patterns to simulate many possible future paths for a $1,000 investment over 15 years. Think of it as running the same movie 1,000 different ways, each time shuffling the good and bad years. The median outcome ends around $2,724, with a wide central range from about $1,807 to $4,259. Extreme scenarios stretch from roughly flat to strong growth. The average annualized return across simulations is 8.28%, with about three-quarters of paths ending positive. These numbers are not promises; they just show what could happen if the future rhymes with the past, which it often doesn’t perfectly.
All of the portfolio sits in stocks, with 0% in bonds, cash, or alternatives. So diversification is achieved within the equity bucket rather than by mixing different asset classes. This can lead to higher long-term growth potential but also more pronounced ups and downs because there’s no explicit ballast from safer assets. Compared to a multi-asset benchmark that includes bonds, this mix would typically ride equity market cycles more directly. The balanced risk classification likely reflects the spread across regions, sizes, and styles within stocks rather than cross‑asset cushioning. For someone evaluating risk, the key point is that short‑term swings are driven almost entirely by equity markets.
Sector exposure is fairly spread out, with technology the largest at 20%, followed by meaningful allocations to financials, industrials, and consumer discretionary. No single sector dominates in the way tech often does in broad US benchmarks, which helps avoid overreliance on one area of the economy. Smaller weights to utilities and real estate mean less exposure to traditionally defensive sectors that sometimes hold up better in downturns. A layout like this tends to behave more like a diversified economic snapshot, where different industries drive returns at different times. It also means sector-level risk is more about broad market cycles than one hyper-concentrated theme.
Geographically, about 73% of the portfolio is in North America, with the rest spread mainly across developed Europe and Japan and small slices in other regions. That’s a clear US tilt compared with a global stock index, where the US is big but not typically this dominant. The international small- and large-cap value funds help bring in non-US exposure, but the core driver remains the US market. This structure often tracks US economic and policy conditions closely, while still getting diversification from foreign currencies and business cycles. Over time, that mix can smooth country-specific shocks somewhat, even though the home region still sets the tone.
The portfolio covers the full spectrum of company sizes, from mega-cap down to micro-cap. Mega- and large-caps together make up just over half of the exposure, while mid-, small-, and micro-caps account for the rest. That’s a stronger tilt toward smaller companies than broad market indices, where giants dominate. Smaller firms often show more price volatility and can be more sensitive to economic swings, but they also bring different growth and recovery patterns than the largest names. Having meaningful exposure across the size range helps diversify sources of return, with big companies providing stability and smaller ones adding more punch to both upside and downside moves.
Looking through ETF top holdings, a handful of well-known US growth names appear prominently, like NVIDIA, Apple, Microsoft, and Alphabet. NVIDIA alone adds up to nearly 4% of the portfolio via ETF exposure, while several other mega-cap tech and communication names each sit around 1–3%. Because only top-10 positions are visible, actual overlap is likely higher than shown. This means that even though the portfolio has value and small-cap components, a slice of performance is still tied to a familiar group of large growth companies. Hidden overlap like this can concentrate risk in particular business models or themes more than the fund list suggests.
Factor exposure shows a notable tilt toward value at 70%, while size, momentum, quality, yield, and low volatility all sit near neutral. Factors are like underlying traits — cheapness (value), recent performance (momentum), stability (low volatility), and so on — that research has linked to long-term returns. A high value tilt means the portfolio leans toward stocks trading at lower prices relative to fundamentals, which can behave differently from broad market indices that are often growth-heavy. Historically, value has gone through long stretches of underperformance and catch-up phases. So this factor mix may lag in strong growth-led rallies but can shine when cheaper, more cyclical companies come back into favor.
Risk contribution shows how much each holding drives the portfolio’s overall ups and downs, which can differ from its weight. The core S&P 500 ETF is 40% of the assets and contributes about 39% of total risk, so its impact is roughly proportional. The US small-cap value fund, at 20% weight, contributes over 24% of risk, meaning each dollar there adds a bit more volatility than average. The two international Avantis funds contribute slightly less risk than their weights, while the momentum ETF is almost exactly proportional. With the top three holdings responsible for about 77% of total risk, most day-to-day movement comes from that core-plus-US-small-cap combination.
The correlation view highlights that the two international Avantis funds move almost identically. Correlation measures how often assets move in the same direction; a very high reading means they behave similarly, reducing diversification benefits between those two pieces. While they cover different segments (small-cap value and large cap), they likely respond to many of the same global and regional drivers. That doesn’t negate their role in diversifying away from the US, but it does mean they act more like a single international block during market stress. True diversification relies on combining things that don’t always rise and fall together, especially in turbulent periods.
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 vs. return chart, the current portfolio sits below the efficient frontier, which is the curve showing the best expected return for each risk level using the same ingredients. Its Sharpe ratio — a measure of return per unit of volatility — is 0.64, compared with 1.0 for the optimal mix and 0.83 for the minimum variance portfolio. Being about 3 percentage points below the frontier at the current risk level suggests that a different weighting of these same five ETFs could, in theory, deliver either higher return at similar risk or similar return with less volatility. That’s an efficiency observation rather than a judgment on the overall structure.
The blended dividend yield is about 1.62%, with the higher-yielding pieces coming from the international value funds around 2.8%. Yield here means the annual cash distributions as a percentage of current value, ignoring price changes. The US small-cap and momentum funds offer lower yields, consistent with their focus on other characteristics. A modest yield like this means most of the portfolio’s historical growth has come from price appreciation and factor exposures rather than income. For someone tracking total return, dividends still matter because they can be reinvested, but this setup is more about capital growth than building a large regular cash payout.
The portfolio’s total expense ratio (TER) averages around 0.17%, which is low by equity fund standards. TER is the ongoing annual fee charged by the funds, taken out of returns before they reach the investor — a bit like a small built-in service charge. The cheapest piece is the broad S&P 500 ETF at 0.03%, and even the more specialized factor and international funds stay well under 0.40%. Lower costs mean less drag compounding over time, so more of any gross return is kept. This cost profile is impressively lean given the use of active factor strategies, and it supports better long-term compounding versus higher-fee alternatives.
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