Portfolio report
The briefing
Your biggest drivers of day‑to‑day movement are a small group of mega‑cap tech and growth names that appear across multiple ETFs. When they rally, the whole portfolio feels it, and when they stumble, the pullback can be noticeable. It’s helpful to know that headlines about …
Almost all of your diversification happens within stocks rather than across different asset classes. That’s why the drawdown history includes a roughly 28% drop that took more than a year to recover from. If you’re ever surprised by big swings, it’s worth remembering that this …
The efficient frontier analysis shows your current three‑fund mix is already using these holdings in a very efficient way for its risk level. In plain terms, there isn’t obvious “wasted” risk here given the ingredients you’ve chosen. That gives you a solid structural base, so …
Highlights from the assessment. Explore the analysis below for context and assumptions.
The starting point
This portfolio is a simple three‑ETF mix that is 100% in stocks. About 60% sits in a broad US total market fund, 20% in a NASDAQ 100 fund, and 20% in a broad international fund. Structurally, that means a clear tilt toward US equities, with an extra layer of large growth companies via the NASDAQ exposure. A concentrated lineup like this is easy to follow because each ETF covers a large slice of the market. The simplicity also makes it clearer where risks and returns are coming from, since there are no bonds, alternatives, or niche strategies hiding in the background.
From late 2020 to late 2026, a hypothetical $1,000 in this portfolio grew to about $2,260. That works out to a Compound Annual Growth Rate (CAGR) of 14.72%, which is like asking “what steady yearly rate would get me to the same endpoint?” Over the same period, it slightly lagged the US market but beat the global market. The maximum drawdown, or worst peak‑to‑trough drop, was about -27.7%, deeper than cash but similar to broad equities. It took over a year to fully recover, showing that stock‑only portfolios can experience long stretches of discomfort even when long‑term returns look strong.
The Monte Carlo projection uses many simulated paths based on historical volatility and returns to show a range of possible futures. Think of it as rolling the dice 1,000 times on how markets could behave over 15 years, then summarizing the outcomes. Here, the median simulation turns $1,000 into about $2,813, with most results falling between roughly $1,868 and $4,302. The wide $1,020 to $8,217 range highlights how uncertain markets can be. The average simulated return of 8.39% per year is lower than recent history, which is common when using long‑run assumptions. These are modelled outcomes, not promises, and real results can fall outside any band.
All of this portfolio sits in one asset class: stocks. There are no bonds, cash substitutes, or alternative assets, so all risk and return comes from equity markets. Being 100% in stocks typically means larger swings in value, but it also gives full exposure to equity growth. Compared with many blended portfolios that mix in bonds, this setup will usually move more sharply with market news. The diversification here comes from owning thousands of companies across funds rather than from mixing asset classes. That’s an important distinction: it’s well‑spread within equities, but it doesn’t use bonds to dampen volatility.
Sector‑wise, the portfolio leans heavily into technology at 38%, which is higher than many broad global benchmarks. Financials, industrials, consumer discretionary, telecom, and health care together create a solid base of non‑tech exposure, while smaller slices in staples, energy, materials, utilities, and real estate round it out. Tech‑heavy allocations often benefit during periods of innovation and low interest rates, but they can feel more painful when growth stocks fall out of favor or when rates rise. This sector mix is a big driver of the portfolio’s growth tilt and likely helped past performance, while also amplifying sensitivity to tech‑specific cycles and regulation.
Geographically, about 81% of the portfolio is in North America, with relatively small allocations to Europe, Japan, developed Asia, emerging Asia, and other regions. That’s a clear US tilt, stronger than what you’d see in a fully global market‑cap index, where the US is big but not this dominant. This alignment with the US market has been beneficial over the last decade, given US outperformance, and it keeps currency risk simpler for a US‑based holder. At the same time, it means economic, policy, and market shifts in North America have an outsized impact, while many global opportunities are represented only modestly.
The market capitalization breakdown shows 45% in mega‑caps and 31% in large‑caps, with smaller portions in mid, small, and micro‑caps. This is broadly in line with standard market‑cap weighted equity indices, which naturally place more weight on the largest companies. The heavy mega‑cap exposure helps explain why big, well‑known names dominate the look‑through list. Large companies tend to be more stable and widely researched, while smaller companies can be more volatile and idiosyncratic. The modest allocation to mid and small caps adds some diversification and potential for different growth patterns without overwhelming the portfolio’s behavior.
Looking through the ETFs, the top underlying positions show a strong concentration in a handful of familiar large tech and growth names such as NVIDIA, Apple, Microsoft, Amazon, Alphabet, Meta, Tesla, and Broadcom. Several of these appear in multiple funds, so their combined portfolio weights are higher than they might look inside each ETF individually. For instance, NVIDIA and Apple together make up over 11% of the covered slice, despite only examining top‑10 holdings. Because only ETF top‑10s are used, overlap is likely understated, but the pattern is clear: the portfolio’s day‑to‑day moves will be heavily influenced by the performance of a relatively small group of mega‑cap growth companies.
The factor exposure profile is very even across value, size, momentum, quality, yield, and low volatility, all sitting in the neutral band around 50%. Factor exposure describes how much the portfolio leans into specific characteristics that research links to returns, like cheapness (value) or recent winners (momentum). Here, the readings indicate a market‑like mix with no strong tilts toward or away from any factor. That means performance is likely to resemble broad market behavior rather than swinging wildly with any specific style cycle. This balanced factor setup is a nice complement to the more noticeable tilts in geography and sector exposure.
Risk contribution measures how much each holding adds to the portfolio’s overall ups and downs, which can differ from its weight. The total US market ETF is 60% of assets and contributes about 59% of risk, almost perfectly in line. The NASDAQ ETF is 20% of assets but adds nearly 25% of risk, showing that it’s a bit more volatile than its size alone suggests. The international ETF contributes slightly less risk than its 20% weight. This pattern is quite typical: growth‑heavy, tech‑tilted funds tend to punch above their weight in driving volatility. Overall, risk is concentrated in just three broad funds, which keeps the structure easy to understand.
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 optimization chart shows the current mix sitting on or very close to the efficient frontier. The efficient frontier is the curve that represents the best achievable return for each risk level using only the existing holdings in different proportions. The portfolio’s Sharpe ratio of 0.66 is lower than both the optimal portfolio (0.83) and the minimum variance version (0.78), but that’s because those are theoretical best points using different weights. Being on the frontier signals that, for this risk level and these three funds, the allocation is already quite efficient. It’s making good use of what’s in the lineup.
The blended dividend yield is about 1.2%, combining a very low yield from the NASDAQ ETF, a modest yield from US total market, and a higher yield from international stocks. Dividends are the cash payouts companies share with shareholders, and they can be a meaningful piece of total return over long periods, even if they look small year to year. In this case, the portfolio leans more toward growth and capital appreciation than income, given the low yield. That’s consistent with the strong tech and mega‑cap growth exposure. Dividend income still adds a steady, if modest, component alongside price changes.
The overall cost level is impressively low, with a blended Total Expense Ratio (TER) of about 0.06% per year. TER is the annual fee charged by funds to cover management and operations, taken directly out of returns. In dollar terms, that’s roughly $0.60 per year on a $1,000 investment, which is very efficient by industry standards. Keeping costs this low helps more of any gross return stay in the portfolio, and the benefit compounds over time. Using broad, low‑cost index ETFs from established providers is a key reason costs sit at this level. This cost structure is a real strength of the portfolio.
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