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.
Aggressive Investors
This setup fits an investor who’s comfortable with substantial market swings and is aiming for strong long‑term growth rather than steady income. A typical profile might be someone with a long time horizon—10 years or more—who can ride out deep drawdowns without panicking. They may be focused on building wealth aggressively, possibly during peak earning years, and are willing to accept a concentrated tilt toward large US growth companies and a small speculative allocation. Short‑term portfolio value fluctuations, including double‑digit declines, would be acceptable as long as the long‑run growth trajectory stays intact and the strategy remains simple and low‑cost.
This portfolio is built almost entirely around broad US stocks plus a tech‑tilted index and a small bitcoin slice, with a sizable chunk sitting in a government money market fund. The big thing to notice is the heavy overlap: the S&P 500 fund and the total US stock fund hold many of the same companies, while the NASDAQ 100 fund also owns many of those same large names. That means the headline number of positions overstates true diversification. For someone targeting aggressive growth, tightening the lineup to fewer overlapping funds and defining a clear role for cash-like holdings can make the overall structure cleaner and easier to manage.
The reported historic performance stats look broken: a 129% compound annual growth rate (CAGR) with only a ‑1.77% max drawdown is not realistic for a stock‑heavy, aggressive portfolio. CAGR is the average yearly growth rate over time, like averaging your speed over a long road trip, while max drawdown shows the worst peak‑to‑trough loss. Real‑world equity portfolios regularly see drawdowns of 20–50% during bad markets. This mismatch strongly suggests data issues or an unrealistically short observation window. It’s safer to mentally “ignore” these numbers and instead assume typical stock‑market risk and return patterns when judging whether the setup fits long‑term goals.
The Monte Carlo simulation results are also clearly off, showing ‑100% in most scenarios and no positive outcomes, which simply doesn’t line up with how diversified stock ETFs behave. Monte Carlo analysis uses many random “what if” paths, based on past data, to estimate a range of future results—like running 1,000 alternate timelines for your portfolio. When the inputs are flawed, every simulated path becomes meaningless. Here, both the extreme negative projections and the unrealistic historical stats highlight that the model’s data or assumptions are mis-specified. It’s better to treat these projections as a technical glitch and rely on general expectations for aggressive equity investing instead.
By asset class, the portfolio is overwhelmingly in stocks, with a tiny slice in “other” (bitcoin) and nearly no true cash once you look past the labelled categories. This is exactly what you’d expect from an aggressive risk profile: high exposure to growth assets that can swing significantly in value. High stock weight can compound wealth over long periods but also leads to sharper ups and downs. The allocation is broadly in line with an aggressive stance, but the low diversification score signals that the equity exposure is clustered rather than spread. Broadening into different types of growth assets could keep the risk level similar while smoothing the ride a bit.
Sector exposure is dominated by technology, with meaningful allocations to communication services and consumer cyclical areas, and smaller pieces in healthcare, financials, and industrials. This is typical of portfolios built from major US index funds, and it lines up closely with well-known benchmarks, which is a positive sign for general balance. However, the added NASDAQ 100 tilt likely amplifies the tech and growth bias, which can be a double‑edged sword: strong in low‑rate, growth‑friendly environments, but more volatile when rates rise or sentiment turns. If the goal is to stay aggressive but avoid being overly tied to one type of company, dialing back the extra growth tilt could help.
Geographically, the portfolio is almost pure North America, with essentially no exposure to Europe or Asia. Many common benchmarks are heavily US‑weighted, so this home bias is not unusual for a US‑based investor and has been rewarding over the last decade. Still, relying almost fully on a single region means outcomes are tightly linked to that region’s economic and policy environment. Global diversification can help when different areas of the world move on different cycles. Someone happy with an aggressive posture could still consider gradually adding non‑US exposure over time as a way to keep growth potential while not betting quite so hard on one market.
The market‑cap mix is tilted toward mega and big companies, with only modest mid, small, and micro‑cap exposure. This is standard for index‑based portfolios: broad US funds and NASDAQ 100‑style funds naturally overweight the largest, most established firms. This tilt provides some stability compared with a pure small‑cap strategy, but it also means less exposure to the very smallest, potentially faster‑growing companies. The current balance mirrors common benchmarks reasonably well, which is generally positive. For someone who wants to go even more growth‑oriented, a controlled increase in smaller companies could boost long‑run potential, while a preference for smoother swings would argue for keeping the current size mix.
All major holdings, including the money market fund and the bitcoin ETF, are flagged as highly correlated, which in practice is almost certainly a data artifact. Normally, government money market funds move very little and have near‑zero correlation with stocks, while bitcoin often behaves erratically and not in lockstep with traditional markets. Correlation just measures how often things move together; when everything is highly correlated, diversification benefits shrink during market stress. Even ignoring the glitch, the three big equity ETFs clearly overlap a lot, so they’re likely to rise and fall together. Streamlining those overlapping pieces can improve clarity and reduce hidden concentration risk.
The portfolio’s total yield sits around 1%, coming mainly from the broad equity ETFs and the money market fund. Yield is the cash income you receive as a percentage of your investment, like interest on a savings account but from dividends or distributions. For an aggressive growth‑oriented setup, a modest yield is normal: the focus is usually on companies reinvesting profits for expansion rather than paying them out. This is well aligned with a growth mindset, especially for long horizons where reinvested earnings can snowball. Anyone needing more regular income, though, might find this level of yield on the low side and could explore slightly higher‑income components.
The overall cost level is impressively low, with a total expense ratio (TER) around 0.05%. The core index ETFs charge rock‑bottom fees, and even the bitcoin ETF, while higher, is still within a reasonable range for that niche exposure. TER is the annual fee taken by a fund, and shaving even a fraction of a percent can add up significantly over decades, like a small leak in a bucket that never quite stops. This cost structure is a strong point and is fully in line with best practices for long‑term investing. Keeping this low‑fee mindset while trimming redundant holdings can support better compounding over time.
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.
Efficient Frontier analysis suggests the same set of assets could be rearranged to target a similar or even better expected return for the same or lower risk. The Efficient Frontier is just the lineup of portfolios that give the best trade‑off between risk (volatility) and return, assuming only these assets and different weightings. Here, the tool points out that overlapping, highly similar funds add complexity without improving that trade‑off. The encouraging part is that, even with the current building blocks, there’s room to nudge the mix closer to the “efficient” line. That means clarifying how much growth, stability, and speculative exposure each holding should contribute.
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