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 someone who is unapologetically growth-focused, intellectually curious, and has zero interest in financial hand-holding. It suggests a long time horizon, a fairly high risk tolerance, and a willingness to sit through ugly drawdowns in exchange for better long-run odds. There’s a clear appreciation for evidence-based strategies like indexing and factor tilts, with minimal tolerance for fluff or complexity-for-show. Short-term stability or predictable income is clearly not the priority here; long-term wealth-building is. This would suit someone who can watch a 30–40% drop, mutter something unprintable, and still not touch the sell button — ideally with at least a decade (and preferably more) before major withdrawals.
Structurally this thing is shockingly sensible: four ETFs, all equity, mostly broad market, with a small-cap value obsession layered on top. It’s like a plain vanilla index portfolio that snuck out at night and got a couple of factor tattoos. Compared to a classic “total US plus total international” 75/25 mix, the extra 25% in small value tilts the whole thing toward bumpier but potentially higher-return territory. The setup is clean and easy to manage, but it leans heavily on one asset class and a single style bet. Consider whether adding even a token ballast (bonds or cash-like options) would make riding out crashes psychologically survivable.
The look-through basically confirms what we already suspect: this rides the same mega-cap tech train as everyone else, just with an intellectual small-value side quest. NVIDIA, Apple, Microsoft, Amazon, Alphabet, Meta, Tesla… all the usual suspects show up in the top exposures. Because coverage only uses ETF top-10 holdings, overlap is actually understated; the FAANG-ish crowd probably has more influence than listed. The good news: these are highly liquid, widely followed giants. The bad news: when the market mood swings against growth or tech, this thing will absolutely feel it. Balancing that hidden mega-cap growth engine with your explicit small-value tilt is key to not ending up unintentionally overexposed to one style regime.
A 14.1% CAGR is eye-watering, especially for something that looks this boring on the surface. Using simple math, $10,000 growing at 14.1% for 10 years ends up around $37,000, which would make most people feel like geniuses. But that max drawdown of -36.6% is the punch in the face behind the trophy. CAGR (compound annual growth rate) is like your average speed on a road trip; max drawdown is the biggest pothole you hit. Against a plain global equity benchmark, this is likely slightly spicier and likely ahead, but past data is yesterday’s weather, not a prophecy. The real job is making sure such drops won’t cause panic selling.
The Monte Carlo results basically say: “Expect a wild ride with great odds of coming out ahead if you stay strapped in.” Monte Carlo is just a fancy way of running thousands of “what if the market behaved like history, but slightly shuffled” scenarios. Median outcome of +440% and an annualized 14.9% is stellar, but that 5th percentile at +40% is the rude reminder: in a bad path, a decade could feel disappointingly average. Simulations rely on historical return and volatility patterns, which is like predicting future traffic from last month’s commute — helpful, but hardly guaranteed. The key here is psychological: if the worst-case path happens to you, will you actually stay invested or fold?
Asset classes here are basically a one-trick pony: 99% stock, 1% cash, and 0% everything else. This is not a “balanced” portfolio; it’s an “I believe in capitalism and Advil” portfolio. When stocks do well, this flies. When stocks tank, there is nowhere to hide. No bonds, no real diversification across return drivers, just different flavors of equity risk. That can be completely fine for long horizons and strong stomachs, but it’s brutal if money is needed within 5–10 years. If stability or spending is even slightly on the radar, sprinkling in something less dramatic than pure equities would smooth the ride without necessarily destroying long-run outcomes.
Sector exposure screams “default global equity” with a bit of extra cyclicality: tech at 22%, financials 16%, industrials 14%, consumer cyclicals 11%. This is not outrageously distorted, but it is clearly geared toward the growth-and-business-cycle-sensitive part of the economy. No obvious “tech addiction” beyond what broad indexes already give you, which is both a relief and a mild disappointment for anyone hoping for a fun villain. Still, if tech or financials get kneecapped, this portfolio will feel it more than a more defensive setup with bigger healthcare or staples weight. If sleep quality matters, nudging sector balance toward slightly more boring, recession-resilient areas via fund choice could help.
Geography says: “America first, but we’ll let the rest of the world sit at the kids’ table.” About 68% North America and 32% rest-of-world is not outrageous for a US-based investor, but it is still a clear home bias compared to the global market (which is closer to 60/40). The upside: heavy exposure to US mega-cap dominance, innovation, and deep capital markets. The downside: if the US has a lost decade while other regions run, this setup just shrugs and takes it. The existing international slice is a good start, but anyone genuinely aiming for global diversification might push closer to global weights over time.
Market cap exposure is where the quiet spice hides: 32% mega, 24% big, 23% medium, 17% small, 3% micro. Translation: broad market base with a noticeable lean toward smaller companies. That tilt is intentional via the small-cap value funds and can pay off over decades, but small and micro caps are like the toddlers of the market — lots of potential, lots of falling over. Compared to a vanilla total-market-only approach, this will probably be more volatile and more sensitive to economic cycles. If the extra bumpiness causes panic or second-guessing, dialing down the small-cap share slightly could make the ride more livable without killing the factor story.
The factor profile is where things go full finance-nerd: huge tilts to value (85%) and size (85%), with decent momentum (59%) and low volatility (55%). Factor exposure is basically the ingredient list behind your returns: value = cheap stuff, size = smaller companies, momentum = recent winners, low vol = smoother names. Here, you’re piling into cheap smaller stocks while also riding some trend and not going full maniac on volatility. The missing quality and yield data is annoying, but the picture still says “deliberate quant-ish tilt,” not accidental chaos. Just remember factor returns are painfully cyclical; when value and small lag, this can underperform markets for years and demand irritating levels of patience.
Risk contribution shows who’s actually rocking the boat, and surprise: the 50% Vanguard Total Stock Market piece contributes 51.3% of risk — almost exactly proportional. The more interesting bit is the small-cap value slice: 15% weight but 17.6% of risk, meaning it’s punching above its weight in the volatility department. Risk contribution is just a way of asking: “Which holdings are making this thing swing?” not just “What’s largest?” Top three positions driving 91% of risk is expected with only four ETFs. If the small-cap bumpiness ever feels like too much, trimming that slice a little and shifting toward broader equity would tame some drama.
A 1.91% total yield is basically “don’t quit your day job” income. The international and Avantis small-cap value funds carry the yield, while US total market drags the average down like a growth-obsessed teenager. Dividends are nice for psychological comfort and cash flow, but they’re not free money — higher yield often means slower growth or more risk. This setup isn’t a dividend hunter’s dream; it’s a growth-first engine with a side of pocket change. Anyone chasing income would need either a higher-yield tilt or a separate income sleeve. For long-term compounding, reinvesting these modest dividends is still doing quiet, unglamorous work in the background.
Costs are where this portfolio decides to be annoyingly competent. A 0.07% total expense ratio is basically couch-cushion money relative to what many investors pay. The Avantis fund is the “expensive” one at 0.36%, which is still cheap for an active-ish small-cap value strategy. The rest are bargain-bin index fees that barely move the needle. TER (total expense ratio) is the cut taken each year; here, that cut is a gentle tap, not a punch. There’s nothing to roast hard on fees — you clearly avoided the usual “1% advisor, 1% fund” bloodletting. Just keep it that way and don’t get cute with high-cost, shiny products.
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 efficiency angle, this portfolio is kind of a beast but not exactly “efficient frontier poster child.” The efficient frontier is just the curve of best tradeoffs between risk and return — not magic, just math saying “for this risk, you could do this well.” You’re sitting firmly in the “high risk, high expected return” corner, with almost no effort to reduce volatility via other assets. That’s okay if maximizing long-term growth is the only priority and volatility is just background noise. But you’re probably leaving some comfort on the table by skipping any stabilizers. A small allocation to something less correlated could push you closer to that ideal curve without sacrificing the growth story.
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