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 built from three broad stock ETFs, with 70% in a total US market fund, 20% in a total international fund, and 10% in an S&P 500 fund. So it is 100% in equities, with no bonds or cash assumed in the analysis. Structurally, it’s essentially “US core plus a slice of the rest of the world,” using very diversified index trackers. This kind of structure is easy to understand: one big building block for the home market, another for overseas, and a smaller extra tilt to large US companies. The result is a simple, transparent portfolio whose behaviour will largely follow global stock markets, with a noticeable emphasis on US equities.
From 2016 to 2026, a hypothetical $1,000 in this mix grew to about $3,569, a compound annual growth rate (CAGR) of 13.61%. CAGR is like average speed on a road trip: it smooths out bumps to show steady yearly progress. Over this period, the portfolio lagged a pure US market benchmark by about 1.19% per year but beat a global market benchmark by 1.42% per year. The worst peak‑to‑trough fall was about −34.6% during early 2020, recovering in roughly five months. This drawdown is very similar to the benchmarks, showing that the portfolio behaved like a standard diversified equity basket through a major stress event.
The forward projection uses a Monte Carlo simulation, which means the system takes the historical return and volatility patterns and generates many possible future paths at random. It’s like running 1,000 alternate timelines for the same portfolio. Over 15 years, the median outcome for $1,000 is about $2,786, with a wide “middle band” from roughly $1,868 to $4,342. There are also more extreme but still plausible results between about $965 and $8,117. The average simulated annual return is 8.23%. These numbers are not predictions; they’re statistical what‑ifs based on the past. Real markets can be better or worse, especially if future conditions differ from the historical period.
All of this portfolio is in stocks, with 0% in bonds, real estate funds, or cash. That makes the asset-class mix very straightforward but also means there’s no built‑in ballast from typically steadier assets. In asset allocation terms, it is a pure equity portfolio, even though the platform labels the risk category as “balanced.” Compared with a classic mixed stock‑bond blend, this structure should be more sensitive to market swings, both up and down. On the positive side, the portfolio spreads its equity exposure across both domestic and international markets, which helps diversify within the stock bucket, even though everything ultimately sits in the same asset class.
Sector exposure is broad, with technology the largest slice at 29%, followed by financials (14%), industrials (11%), consumer discretionary and healthcare (10% each), then telecoms and other smaller sectors. This pattern is quite close to major global and US indices, where tech has grown to a large share of total market value. Tech‑heavy allocations can boost returns in periods when innovative and growth‑oriented businesses lead, but they may also be more sensitive when interest rates rise or when sentiment shifts away from high‑growth companies. Overall, the sector mix looks well‑spread, and the alignment with common benchmarks is a strong indicator of solid diversification across different parts of the economy.
Geographically, the portfolio is strongly tilted to North America at 81%, with the remaining 19% spread across developed Europe, Japan, other developed Asia, and emerging regions. That US‑led profile is typical for “market‑cap weighted” portfolios, because the US makes up a large share of global stock market value. Compared with a truly global benchmark, this portfolio likely has a somewhat higher US share and a somewhat lower allocation to the rest of the world. This has helped over the past decade because US stocks have outperformed many regions, but it also ties a large part of outcomes to one economy, one currency, and one policy environment.
The market-cap breakdown shows a strong emphasis on very large companies: about 42% mega‑cap and 31% large‑cap, with the rest in mid, small, and a small slice of micro caps. Market capitalization simply means the total value of a company’s shares; bigger companies tend to be more stable and widely followed. This distribution is similar to broad total-market indices, which are naturally dominated by the largest firms. The presence of mid and small caps adds some diversification and potential for different growth drivers, but they are a minority of the portfolio. This large‑cap tilt generally leads to somewhat smoother behaviour than a portfolio heavily focused on smaller, more volatile companies.
Looking through the ETFs’ top 10 holdings, a handful of big names stand out: Nvidia, Apple, Microsoft, Amazon, Alphabet, Broadcom, Meta, Tesla, and Berkshire Hathaway together make up noticeable slices, with Nvidia alone around 5.24% and Apple 4.81% of the overall portfolio. These positions appear in multiple funds, so there is overlap that increases effective concentration in these giants. Because only top‑10 ETF positions are used, true overlap is likely understated; many of these companies also sit just outside top‑10 lists in various funds. This pattern is common in cap‑weighted index portfolios: a relatively small group of global leaders quietly drives a large share of total returns and risk.
Factor exposures here are all in the “neutral” zone for value, size, momentum, quality, yield, and low volatility. Factor exposure describes how much the portfolio leans into characteristics like cheap vs. expensive (value), large vs. small (size), or smooth vs. jumpy (low volatility) that research links to long‑term returns. A neutral reading around 50% means the portfolio behaves much like the overall market for that factor, without strong bets for or against any style. This balanced factor profile is typical of broad index funds and helps explain why the portfolio tracks general equity market behaviour closely rather than swinging dramatically with any single investing style.
Risk contribution shows how much each holding adds to the portfolio’s total ups and downs, which can differ from its weight. Here, the US total market ETF is 70% of the portfolio but contributes about 72.3% of overall risk, very close to proportional. The international fund is 20% of weight and 17.5% of risk, while the S&P 500 ETF is 10% of weight and 10.1% of risk. That means no single position is punching far above its size in terms of volatility. All three together account for 100% of the portfolio’s risk, and their risk‑to‑weight ratios are tightly clustered, indicating a straightforward link between size and impact on overall fluctuations.
Correlation looks at how often holdings move in the same direction, on a scale from −1 (always opposite) to +1 (always together). In this portfolio, the S&P 500 ETF and the total US stock market ETF are flagged as moving almost identically. That’s not surprising, because both track very similar sets of US companies, with only a small difference in coverage of mid and small caps. High correlation like this limits the diversification benefit between those two positions: for most market moves, they will rise and fall together. The overseas fund likely adds more diversification, but within US stocks, behaviour is very tightly linked.
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 vs. return analysis shows the current portfolio with a Sharpe ratio of 0.58, compared to 0.81 for the optimal (max‑Sharpe) mix and 0.65 for the minimum‑variance version. The Sharpe ratio measures risk‑adjusted return, like how much “extra” return you get per unit of volatility over a risk‑free rate. Here, the efficient frontier curve is built only from these three ETFs with different weights. The system indicates the current portfolio sits on or very close to that frontier, meaning that, given these holdings, the risk/return tradeoff is already reasonably efficient. Any potential improvements would likely be fine‑tuning rather than major structural changes.
The overall dividend yield is about 1.44%, blending roughly 1.10% from the US funds and 2.80% from the international fund. Dividend yield is the cash income from holdings divided by their price, similar to an interest rate on a savings account, though it can fluctuate. In this case, the yield is modest, which is typical for broad equity indices where many companies reinvest profits instead of paying out large dividends. For a total‑return equity portfolio, dividends are one component of gains alongside price changes. Over time, even relatively small yields can add up, especially when distributions are reinvested into more shares.
The portfolio’s costs are impressively low. The total expense ratio (TER) averages about 0.03%, with the US ETFs at 0.03% and the international fund at 0.05%. TER is the annual fee charged by the fund, taken directly out of returns, a bit like a small service fee. Keeping this number low helps more of the portfolio’s gross returns stay in the investor’s pocket. Compared with many actively managed funds or older index products, these costs are at the very low end of the spectrum. That’s a real structural strength: low ongoing charges support better long‑term outcomes, especially when compounded over many years.
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