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.
Growth Investors
This setup fits an investor who is comfortable with meaningful ups and downs in pursuit of strong long‑term growth. They likely have a multi‑decade horizon, such as saving for retirement far in the future, and can tolerate seeing significant temporary losses without abandoning the plan. Capital appreciation matters more than steady income, and they’re okay with a relatively low dividend stream today. They trust broad, rules‑based index strategies and don’t feel the need to pick individual stocks. This type of investor is usually disciplined about staying invested through cycles, willing to accept tech and US tilts, and open to periodic fine‑tuning rather than constant tinkering.
This portfolio is built almost entirely from three broad stock ETFs, with about three quarters tracking a major US index, a noticeable tilt toward technology, and a smaller slice in international stocks. Compared with a typical growth benchmark that often mixes in some bonds or defensive assets, this setup is more aggressively tilted toward equities. That matters because being almost 100% in stocks can boost long‑term growth but also amplifies swings during market stress. To keep this on track, it can help to decide on a target equity mix and stick to a simple rebalancing schedule, especially if future goals call for adding more stability as time horizons shorten.
Historically, this mix has delivered very strong results, with a compound annual growth rate (CAGR) above 17%. CAGR is like the average yearly “speed” of growth over time, smoothing out the bumps. For context, that’s substantially higher than long‑run stock market averages, helped by a powerful run in large US and technology names. But the portfolio also saw a maximum drawdown of about -33%, meaning a one‑third drop from peak to trough. Since past performance doesn’t guarantee future results, it’s useful to stress‑test your comfort with similar or even deeper temporary losses before committing to keep riding out volatility.
The Monte Carlo analysis, which runs 1,000 simulated futures based on historical patterns and randomness, shows a wide range of potential outcomes. In simple terms, Monte Carlo tries to answer, “What might happen if markets behave like they have in the past, but in different sequences?” The median (50th percentile) result is a several‑fold increase, while even the lower 5th percentile still shows modest growth. That’s encouraging, but simulations rely on historical data and assumptions that may not hold, especially after unusually strong tech‑led periods. Using these projections as rough guardrails, not promises, can help set expectations and plan around best‑, base‑, and worst‑case scenarios.
Asset‑class exposure is almost entirely in equities, with about 99% in stocks and essentially nothing in bonds, cash, or alternatives. Compared with many growth benchmarks that still keep a small slice in lower‑volatility assets, this is firmly on the aggressive side. A pure‑stock approach maximizes long‑run growth potential but also makes the portfolio more sensitive to market crashes and interest‑rate shocks. This allocation is well‑aligned with a long time horizon and strong risk tolerance. Still, it can be useful to think ahead about when to gradually introduce more defensive assets so that large drawdowns are less disruptive as key financial milestones approach.
Sector exposure is meaningfully tilted toward technology at roughly 44%, with financials, consumer areas, communication services, and healthcare making up most of the rest. This tech emphasis is even stronger than many broad benchmarks, which already lean toward tech. That’s helped returns in recent years but can backfire if high‑growth names fall out of favor or if rising rates hurt valuations. On the positive side, the rest of the portfolio still touches multiple sectors, which softens but doesn’t remove concentration risk. Periodically checking how much total return is driven by a single sector and capping it at an intentional range can keep this tilt purposeful rather than accidental.
Geographically, the portfolio is about 90% in North America, mainly the US, with relatively small allocations to Europe, Japan, and other developed and emerging markets. Many common benchmarks are also US‑heavy, but this goes a bit further, leaving only a modest slice in international stocks. A US focus has been rewarded over the last decade, particularly due to mega‑cap tech names, and this alignment with US benchmarks has been beneficial. Still, returns from different regions can rotate over time. Keeping at least some international exposure, and deciding on a target global split in advance, can help smooth country‑specific risks and policy shocks.
Market‑cap exposure is dominated by mega and large companies, with nearly 80% in mega and big caps, and smaller slices in mid and small caps. This mirrors many broad market benchmarks, which are naturally top‑heavy, and it’s a strong indicator of diversification across leading global businesses. Large caps tend to be more stable and liquid, while smaller companies can be more volatile but sometimes offer higher growth potential. Since this mix is already closely aligned with global norms, any tweaks here are more about preference: for example, deciding whether to intentionally tilt a bit more toward smaller companies or simply stick with the current broad, large‑cap‑driven structure.
The overall dividend yield of around 1.2% is relatively modest, which is typical for a growth‑oriented, tech‑tilted stock portfolio. Yield simply measures the cash paid out each year as a percentage of the portfolio value. Tech companies often reinvest profits into growth instead of paying high dividends, boosting potential price appreciation rather than current income. For investors who don’t need much cash flow today and care more about long‑term compounding, this setup is well‑aligned. If income needs rise later, it can be helpful to gradually shift a portion toward higher‑yielding assets rather than trying to overhaul the entire structure all at once.
Costs are impressively low, with a total expense ratio around 0.04%. The expense ratio is like a small yearly “membership fee” taken as a percentage of invested assets. Keeping this number low is one of the easiest ways to improve long‑term results, because every fraction of a percent saved each year keeps compounding in your favor. This cost profile is well‑aligned with best practices and supports better long‑term performance. The main ongoing task here is simply to monitor for any unexpected fee increases or trading costs, while resisting the urge to chase more expensive, complex products that may not reliably add value after fees.
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.
From a risk‑return standpoint, this portfolio already sits in a high‑return, high‑volatility corner of the Efficient Frontier for stock‑only mixes. The Efficient Frontier is the set of allocations that give the best possible trade‑off between risk and return using a given set of assets. Within these three ETFs, shifting slightly more toward international or away from technology could modestly change the ride but probably wouldn’t transform overall risk. Efficiency here is about getting the most expected return per unit of volatility, not about covering every asset type. Deciding whether to stay this aggressive or slide slightly down the risk curve depends mainly on tolerance for future large drawdowns.
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