This portfolio is made up of eight holdings, mostly equity ETFs plus one sector mutual fund and one gold ETF. Around 90% sits in stocks and 10% in gold, so it’s clearly growth‑oriented with a small diversifier. A notable feature is the blend of factor strategies: momentum, quality, small‑cap value, and “core” large caps all appear. This kind of structure means returns are driven less by a single index and more by specific styles of investing. The mix creates several moving parts, which can behave differently across market cycles. Overall, the structure leans into return‑seeking equity risk, with gold acting as a modest ballast rather than a dominant defensive anchor.
Over the period from mid‑2020 to April 2026, $1,000 grew to about $3,169, which is a compound annual growth rate (CAGR) of 21.77%. CAGR is like your average yearly speed on a long road trip, smoothing out bumps along the way. This comfortably outpaced both the US market (16.74%) and global market (14.55%), while experiencing a similar maximum drawdown of around ‑24%. That drawdown took about nine months to bottom and ten months to fully recover, typical for an equity‑heavy portfolio. Only 39 days delivered 90% of the total return, highlighting how a handful of strong days can drive long‑term results. As always, past performance doesn’t guarantee similar future outcomes.
The Monte Carlo projection uses 1,000 simulated paths based on historical volatility and correlations to estimate a range of future outcomes. Think of it as running the next 15 years thousands of different ways, then seeing what’s common. The median result takes $1,000 to about $2,759, an implied annual return of 7.77% across all simulations, with a fairly wide possible range from roughly $1,046 to $6,991. About three‑quarters of simulations end positive, which is in line with a growth portfolio that carries real downside risk. These simulations are useful for framing expectations, but they are still only models built from the past, not forecasts or guarantees. Unexpected macro shocks or regime changes can make reality very different.
Asset‑class‑wise, this is straightforward: roughly 90% in equities and 10% in “other,” which here is primarily gold. That high equity share is consistent with a growth‑oriented risk profile, as stocks historically offer higher potential returns but larger swings. The 10% gold slice adds a different return driver that often behaves unlike stocks, especially around macro or inflation surprises. Compared with a broad global benchmark that might mix in more bonds or cash, this portfolio clearly prioritizes equity risk. The upside is strong participation in equity bull markets; the trade‑off is that in major stock downturns, only that relatively small gold portion may provide meaningful cushioning, so overall volatility remains elevated.
This breakdown covers the equity portion of your portfolio only.
Sector exposure is led by technology at 30%, followed by financials and industrials, with smaller but noticeable allocations across most remaining sectors. This overweight in technology, plus a dedicated semiconductor fund, makes the portfolio more sensitive to themes like innovation, earnings growth, and interest‑rate expectations. Tech‑heavy allocations can shine when growth and productivity stories dominate, but they can be hit harder when rates rise or sentiment turns against high‑growth names. The presence of financials, industrials, and other cyclical sectors helps broaden the economic footprint beyond pure tech. Overall, the sector split is reasonably diversified, yet the clear technology tilt means portfolio behavior will often be influenced by how that sector performs relative to the broader market.
This breakdown covers the equity portion of your portfolio only.
Geographically, about 70% of the portfolio sits in North America, with the rest spread mainly across developed Europe and Japan, plus small slices in other regions. That means portfolio fortunes are closely tied to the US and Canadian markets, currencies, and economic conditions. Compared with a global equity benchmark, which would typically have lower North American weight, this is a noticeable home‑region tilt. The 20% allocation to an international developed momentum ETF adds some non‑US diversification and exposure to different economic cycles and policy regimes. Still, if North American markets experience a prolonged slump or currency shift, the portfolio will feel it strongly, as most holdings ultimately draw their earnings and valuations from that region.
This breakdown covers the equity portion of your portfolio only.
By market cap, the portfolio holds a healthy spread: roughly 29% mega‑cap, 25% large‑cap, 19% mid‑cap, 13% small‑cap, and 5% micro‑cap. This means exposure ranges from global giants to much smaller, more nimble companies. Larger firms often bring stability and deeper resources, while smaller caps can be more volatile but have more room to grow. The explicit small‑cap value fund plus the mid‑cap momentum ETF help push the portfolio down the size spectrum compared with pure large‑cap benchmarks. This size mix can add diversification because small and mid caps don’t always move in lockstep with mega‑caps, though in stressed markets, they can amplify both downside and upside swings more than the very largest companies.
This breakdown covers the equity portion of your portfolio only.
Looking through ETF top‑10 holdings, a few big names repeat across multiple funds: NVIDIA, Alphabet, Apple, Meta, Microsoft, Broadcom, and AMD. Even with only 21% look‑through coverage, these overlaps already account for more than 1% each of the portfolio, indicating hidden concentration in leading tech and communication names. Overlap can be useful when those companies are strong performers, but it also means that bad news for a single mega‑cap can echo across several funds at once. Because this analysis only uses ETF top‑10 lists, it likely understates the true amount of overlap. Still, it clearly shows that a meaningful chunk of risk traces back to a relatively small group of dominant US technology‑related companies.
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 is broadly balanced, with all listed factors sitting in the “neutral” band relative to the market. Size stands out modestly at 61%, a mild tilt toward smaller companies compared with a pure large‑cap benchmark. Factors are like investing “ingredients” such as value, momentum, or quality that help explain why portfolios behave the way they do. Here, there’s no extreme leaning toward any single factor, which can help avoid being overly tied to one style regime, such as pure value or pure momentum. The slight size tilt, plus the specific funds used, suggests this portfolio may behave a bit differently than a standard index, but without a strong bias that dominates performance across all environments.
Risk contribution shows how much each holding adds to overall ups and downs, which can differ from its weight. The semiconductor fund stands out: it’s 10% of the portfolio but contributes about 19% of total risk, almost double its size. That reflects the high volatility typical of a focused sector strategy. By contrast, the two 20% factor ETFs each contribute around 17% of risk, slightly under their weights, suggesting they’re relatively more balanced or diversified. The small‑cap value and quality GARP funds each add around 11% of risk, in line to modestly above their 10% weights. Overall, the bulk of risk is concentrated in just three positions, mainly driven by the sector fund’s punchy behavior.
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 0.98, below both the optimal portfolio (1.44) and minimum‑variance mix (1.3). The Sharpe ratio measures return per unit of risk, similar to how many miles you get from a gallon of gas. Being 4.53 percentage points below the efficient frontier at today’s risk level means that, using only these existing holdings, there’s a mathematically more efficient mix that could deliver higher expected return or lower risk. The minimum‑variance and max‑Sharpe portfolios both sit on the frontier, representing the best historical trade‑offs from reweighting. The current allocation is decent, but it’s not squeezing the maximum possible risk‑adjusted benefit out of the same building blocks.
The portfolio’s total dividend yield is about 2.46%, coming from a mix of income‑oriented and growth‑oriented holdings. One highlight is the semiconductor fund’s reported 11.70% yield, which is unusually high for that segment and may reflect special distributions or specific fund policies. Yields between 0.3% and 3.6% across other holdings show a blend of modest income with a focus on capital appreciation. Dividends can be an important part of long‑term returns, especially when reinvested, but in a portfolio like this, they’re clearly a secondary driver compared with price gains. It’s also worth remembering that dividend yields can change over time as prices move and companies adjust their payout policies.
Total annual costs, measured by the weighted TER of roughly 0.20%, are impressively low given the specialized factor and sector strategies involved. TER, or Total Expense Ratio, is like a management fee taken from fund assets each year, quietly reducing returns in the background. Individual fund fees range from 0.10% for gold to 0.62% for the semiconductor mutual fund, which is the priciest component. Keeping overall costs near 0.20% supports better long‑term compounding, especially compared with more expensive active products. The fee structure here is a strong positive: it allows the portfolio to pursue factor tilts and sector exposure without giving up too much return to ongoing costs over time.
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