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.
Cautious Investors
This setup fits an investor who is generally cautious but still prioritizes long‑term growth over short‑term stability. They are comfortable with moderate volatility, including temporary drawdowns of around 20%, in exchange for higher return potential across decades. Typical goals might include retirement savings, college funding, or building multi‑generational wealth with a 10‑year‑plus horizon. They value diversification across regions, sectors, and company sizes, and appreciate low fees and tax‑aware bond choices. This personality is patient, not overly focused on short‑term headlines, and prefers a systematic, rules‑based structure rather than frequent trading or concentrated single‑stock bets.
Overall structure tilts clearly toward growth assets while still matching a “cautious” risk profile. Roughly 80% is in stocks, with the rest split between short‑term Treasuries and a state tax‑exempt bond fund. There is also a dedicated real estate sleeve, plus a mix of broad market and factor‑tilted equity ETFs. Compared with a typical cautious benchmark, this holds more equities but offsets that with very short‑term bonds and high diversification. This allocation is well-balanced and aligns closely with global standards for a growth‑oriented cautious investor, though anyone needing very stable principal might shift a bit more toward conservative fixed income.
Historically, this mix delivered a compound annual growth rate (CAGR) of about 9.65%. CAGR is like your portfolio’s average “speed” per year over a long trip, smoothing out bumps. A hypothetical 100,000 dollars invested and left alone would have grown meaningfully faster than most low‑risk benchmarks, while the max drawdown of about −21% stayed well below typical stock‑only crashes. That max drawdown still represents real temporary loss and shows what could happen in a sharp sell‑off. Past numbers are encouraging but not guaranteed; markets change, and future returns can be higher or lower than this backtested history suggests.
The Monte Carlo analysis runs 1,000 random “what if” market paths based on historical behavior to estimate future ranges. It shows a median (50th percentile) outcome of roughly 207% total growth, with the downside 5th percentile around 20.4% and an annualized average near 9.55%. In plain terms, most simulated futures are positive, and only a small slice are meaningfully disappointing. Still, Monte Carlo relies on past volatility and correlations, so it can miss extreme new scenarios or regime shifts. These projections are best used as rough guardrails rather than precise promises when deciding how much risk feels acceptable.
By asset class, about 80% sits in stocks, 11% in bonds, and 9% in cash‑like instruments. For a profile labeled cautious, that’s an assertive growth tilt, but the presence of short‑term Treasuries and high‑quality municipal bonds adds a stabilizing anchor. Compared with many cautious benchmarks that might hold 40–60% in bonds, this mix leans more toward long‑term growth and short‑term ups and downs. This structure works well for someone who can tolerate occasional double‑digit dips without panic selling. Anyone with a shorter horizon or low comfort with volatility might increase high‑quality bonds and cash‑like holdings to smooth the ride.
Sector exposure is very broad: technology, financials, real estate, industrials, consumer cyclical, healthcare, and more all appear meaningfully. Technology is the largest slice, but not overwhelmingly so, especially compared to typical US equity indices. The dedicated real estate ETF pushes property exposure to about 11%, which can add income and inflation sensitivity but also interest‑rate risk. Tech‑heavy allocations often swing more when interest rates move, while real estate can be pressured by higher borrowing costs. Here, sector composition matches benchmark data closely enough to support diversification, while the deliberate real estate tilt adds a distinct but manageable source of risk and income.
Geographically, just over half of the allocation is in North America, with the balance spread across Europe, Japan, other developed Asia, and emerging regions. This is more globally diversified than many US‑centric portfolios that sit 60–70% or more in domestic markets. The overseas and emerging positions help reduce reliance on a single economy and currency, which is valuable if US stocks underperform for a stretch. That said, non‑US markets can lag for long periods and carry different political and currency risks. This allocation is well-balanced and aligns closely with global standards, offering solid international exposure without being overly aggressive.
The mix by company size is nicely spread across mega, big, mid, small, and even some micro caps. Many investors end up unintentionally concentrated in mega caps because broad indices are size‑weighted. Here, the equal‑weight S&P and the small‑cap value ETFs deliberately push more toward mids and smalls. Smaller companies often swing more in the short run but historically have offered higher return potential over long stretches. This balanced size exposure supports long‑term growth and diversification, though it can mean periods where the portfolio lags mega‑cap‑heavy benchmarks during narrow, large‑cap‑driven rallies. Staying patient through those style cycles is key.
Correlation measures how often investments move together; a value of 1 is lockstep, 0 is independent, and −1 is opposite. The international core equity ETF and the international small‑cap value ETF are highly correlated, meaning they tend to rise and fall in similar conditions. That reduces the diversification benefit between those two positions. However, the broader portfolio holds many other uncorrelated or less‑correlated pieces, such as bonds, cash‑like instruments, and real estate, so overall diversification remains strong. If simplicity is a goal, trimming overlapping holdings while preserving the desired regional and style exposure could slightly streamline the structure without sacrificing risk control.
The overall yield of about 2.28% combines equity dividends, real estate distributions, and income from the bond and Treasury ETFs. That is a reasonable payout level for a growth‑tilted allocation and can help modestly support withdrawals or reinvestments. Dividends and interest are a meaningful part of total return, but price changes will still drive most long‑term growth here. The real estate and bond exposures boost the income side, while the equity components lean more toward capital appreciation. Anyone relying heavily on portfolio income might want a bit more high‑quality fixed income, but for balanced growth and income this level is quite sensible.
The blended ongoing cost (Total TER) of about 0.14% is impressively low for such a diversified, factor‑tilted lineup. TER, or total expense ratio, is the annual fee taken by funds; keeping it low is like paying less “toll” on your investing highway. Over decades, even a 0.3–0.5% difference can compound into a large gap. Here, broad ETFs and efficient active‑quant vehicles hold costs in check while still providing global, small‑cap, and value tilts. The costs are impressively low, supporting better long‑term performance, so there is no strong need to chase cheaper options at the expense of desired exposures.
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 looks for the mix of your existing holdings that gives the best trade‑off between risk and return. “Efficient” here means highest expected return for a chosen risk level, not necessarily the most diversified or simplest. The modeling suggests a more efficient mix of the same ingredients could slightly improve expected return at the same volatility, or similar return at lower volatility. However, these optimizations depend heavily on historical averages and may not hold in future regimes. Any shift toward the mathematically “optimal” allocation should be weighed against preferences for income, taxes, simplicity, and comfort with inevitable performance differences versus broad benchmarks.
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