This portfolio is very straightforward: three equity ETFs and nothing else, with a clear anchor position. Around half sits in a broadly diversified all‑equity fund, while the remaining half is split between US and international momentum strategies. That means every dollar is tied to stock markets rather than bonds or cash. A structure like this is simple to follow because each holding has a distinct role: broad market core plus momentum satellites. Simplicity helps when interpreting behaviour over time, since performance mainly reflects global equities and momentum effects rather than many moving parts. The trade‑off is that risk will closely track stock market ups and downs, without the dampening that bonds or other diversifiers can provide.
Over the period shown, a $1,000 investment grew to about $2,539, implying a compound annual growth rate (CAGR) of 28.44%. CAGR is like average speed on a road trip, smoothing out bumps along the way. This comfortably exceeded both the US market and broad global market, which sat just over 22% a year. The portfolio’s maximum drawdown, or worst peak‑to‑trough drop, was -16.72%, slightly smaller than the US market’s but similar to the global benchmark. That combination of higher return with comparable downside is a strong outcome historically. However, this period was particularly favourable for momentum and some growth areas, so it should not be assumed to repeat in the same way.
The Monte Carlo projection uses historical returns and volatility to simulate many possible future paths for $1,000 over 15 years. Think of it as rolling the dice 1,000 times using past patterns as a guide, then looking at the range of outcomes. The median result of about $2,816 implies moderate long‑term growth, with a wide “likely” band from roughly $1,757 to $4,350. There are also more extreme but less common outcomes at both ends. Importantly, the average annual return across all simulations, 8.33%, is much lower than the recent historical CAGR, illustrating how unusually strong the backtest period was. These simulations are illustrative, not predictions, and real markets can behave differently.
All of the portfolio is in stocks, with no bonds, cash, or alternative assets. Asset classes are broad buckets like equities, fixed income, and real assets, each reacting differently to economic conditions. Being 100% in equities typically increases long‑term return potential but also amplifies short‑term swings, since there is no built‑in stabiliser. Compared with many blended portfolios that mix stocks and bonds, this structure leans fully into growth assets. That can be rewarding in strong markets but means portfolio value will move more in line with equity cycles, both up and down. The balanced risk score reflects this: diversified within equities, but not diversified across asset classes.
Sector exposure is skewed toward Technology at 28%, followed by Financials and Industrials, with smaller allocations across other areas. Sectors group companies by business type, and different sectors react differently to interest rates, inflation, or growth surprises. A Technology tilt often brings higher growth sensitivity and more pronounced reactions to market sentiment, especially around innovation and earnings expectations. At the same time, there is representation in more defensive and cyclical sectors like Health Care, Consumer Staples, and Utilities, which can behave differently across the cycle. Overall, this mix is more growth‑oriented than a perfectly neutral global basket but still reasonably diversified across the economic spectrum.
Geographically, about 69% of exposure is in North America, with the rest spread mainly across developed Europe and Japan, plus smaller slices in other regions. Geography matters because local economies, currencies, and regulations influence company fortunes. Compared with a typical global equity benchmark, this portfolio has a noticeable US/North America tilt but still includes meaningful non‑US developed exposure. That provides some diversification across economic regions, though emerging markets remain a small component. This pattern aligns with many global portfolios that emphasise larger, more established markets while still drawing on international opportunities, which can smooth country‑specific shocks over long periods.
By market capitalisation, the portfolio leans toward larger companies: roughly 72% combined in mega‑ and large‑caps, with the rest in mid, small, and micro‑caps. Market cap is essentially company size on the stock market, and size affects risk and behaviour. Bigger firms usually have more stable earnings and deeper trading liquidity, which can reduce idiosyncratic risk, while smaller firms tend to be more volatile but can exhibit stronger swings in both directions. This blend, with a clear tilt to large and mega‑caps but still some exposure down the size spectrum, offers a balance between stability and growth potential. It also mirrors how most global equity indices are constructed.
Looking through the ETFs’ top holdings, several names repeat across funds, creating hidden concentration. For example, Micron, NVIDIA, and Broadcom together account for a notable portion of the portfolio, and mega‑cap tech and semiconductor firms feature prominently. Overlap means the same company can drive more of the portfolio’s behaviour than any single fund weight suggests. Because only top‑10 holdings are used, actual overlap is likely somewhat higher. This structure increases sensitivity to a relatively small group of large, growth‑oriented stocks, even though the headline allocation looks broadly diversified. It’s not inherently negative, but it does mean big news in those companies can move the overall portfolio more than expected.
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 exposure shows high tilts to both Value and Momentum, with other factors around neutral. Factors are characteristics like “cheap vs. expensive” (value) or “recent winners vs. losers” (momentum) that research links to long‑term return patterns. A high momentum tilt means the portfolio tends to hold stocks that have performed well recently, which can boost returns in trending markets but can be more vulnerable during sharp reversals. The high value tilt suggests a preference, on average, for companies priced attractively relative to fundamentals, which can help when markets favour cheaper stocks. Combining value and momentum is a common academic theme, as they tend to work at different times, adding a diversified return pattern on top of the market exposure.
Risk contribution analysis shows each ETF’s share of overall volatility. Even though the broad Avantis fund is 50% of the portfolio, it contributes about 46% of risk, slightly less than proportional, suggesting relatively moderate volatility. The US momentum ETF, at 30% weight, contributes over 34% of risk, meaning it punches a bit above its size in driving ups and downs. The international momentum ETF is close to its weight in risk terms. This indicates that the momentum sleeve, especially in the US, is a key driver of portfolio swings. The pattern is typical: more concentrated or style‑tilted funds often add more risk per dollar invested than broad, diversified holdings.
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 mix sits essentially on the efficient frontier, meaning that, given these three holdings, it delivers a strong balance of expected return for its level of volatility. The Sharpe ratio of 1.39 measures risk‑adjusted return by comparing excess return over the risk‑free rate to volatility; higher is better. The optimal portfolio on this frontier has a higher Sharpe of 1.7 but also higher risk, while the minimum‑variance portfolio slightly reduces risk and return with a similar Sharpe to the current mix. This suggests the existing weights already use the available building blocks efficiently, without obvious “dead weight” from a pure risk‑return perspective.
The overall dividend yield, around 1.6%, is modest and below that of many income‑focused equity portfolios. Yield measures how much cash is paid out annually relative to price, like rent from a property. The international momentum ETF has a higher yield, while the US momentum fund is relatively low, which is common for strategies targeting recent winners that often reinvest more earnings. Most of the portfolio’s expected return is therefore coming from price changes rather than cash distributions. That’s typical for growth‑tilted and momentum‑heavy equity mixes, where the emphasis is on capital appreciation rather than steady income streams.
The weighted average ongoing fee (TER) of about 0.20% per year is low for an all‑equity, style‑tilted portfolio. TER is like a small annual service charge that’s quietly deducted from returns. Keeping this number modest is helpful because costs compound over time just like returns do, but in the opposite direction. Here, the broad Avantis fund and the two momentum ETFs all charge relatively reasonable fees for their categories. Compared with many actively managed funds, this cost level is quite competitive. That creates a solid foundation where more of the portfolio’s gross performance flows through to the investor instead of being eroded by expenses.
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