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 setup looks like someone started with the cheat code (a target date fund) and then couldn’t stop “adding value.” Over half the money sits in a one-fund solution, and the rest is basically a pile of things that largely own the same stuff: total market, growth, world, tech, dividend, plus a tiny value and a random single stock mascot. It’s like ordering the sampler platter and then adding extra plates of the exact same appetizers. The structure isn’t disastrous, but it’s wildly redundant. A key takeaway: if one holding is already a complete portfolio, everything else should have a clear, distinct job — not just be more of the same with different tickers.
CAGR (Compound Annual Growth Rate — your average “speed” per year) at 13.48% since 2019 is solid, turning $1,000 into $2,273. You slightly lag the US market by about 1% per year but beat the global market by over 1%. That’s basically saying you chose “mostly US” and it worked as expected: not quite max throttle, but certainly not slow. Max drawdown of about -33% in 2020 was brutal but identical to the benchmarks — you rode the same roller coaster as everyone else. Past performance is useful context, but like yesterday’s weather, it doesn’t guarantee tomorrow’s storm schedule.
The Monte Carlo simulation is a fancy way of stress-testing your future by running 1,000 random “what if” paths using historical-like behavior. Median outcome of $2,685 from $1,000 in 15 years (about 7.7% annualized) is decent but nowhere near the historical 13% party you just experienced. The plausible range of roughly $1,014–$6,558 is basically the market saying, “Yeah, this could go okay, or it could be aggressively meh.” Positive 73% of the time is good but not life-changing certainty. Main idea: the future here is more modest and messy than the backward-looking chart suggests; planning on the high end is how dreams turn into regret.
Asset mix: 95% stocks, 5% bonds. That’s not “balanced”; that’s “I’ll sleep fine during a 40% crash, trust me bro.” For a growth-oriented profile with a long horizon, this level of equity isn’t crazy, but let’s not pretend the 5% bond “cushion” is doing anything heroic. It’s more decorative than functional. This is a portfolio that wants returns now and is willing to eat volatility for breakfast. Takeaway: if the goal is maximum long-term growth and you genuinely have decades plus a strong stomach, this mix lines up — but emotionally, it’s not built for someone who checks their balance daily.
This breakdown covers the equity portion of your portfolio only.
Sector-wise, you’re tilted heavily toward technology at 29%, with financials and industrials trailing well behind. Then you’ve got a 10% telecom chunk that’s basically your AT&T cosplay plus broad exposure. So you’re simultaneously chasing shiny tech growth and clinging to a stodgy telecom dinosaur for yield. That’s like wearing a gaming headset with a rotary phone on the desk. The rest of the sectors are fairly spread out, so it doesn’t scream disaster, just personality crisis. Takeaway: leaning into one big growth sector plus one lumbering income relic means your sector mix is a bit confused about whether it’s young and reckless or old and tired.
This breakdown covers the equity portion of your portfolio only.
Geographically, this is “America first, second, and third, and then we’ll see.” Around 79% in North America with tiny sprinkles everywhere else is basically home-country bias in full display. For a US-based investor this is super common, but that doesn’t make it optimal. You’re acting like the rest of the world is a small-cap side quest. The amusing part: you even hold a “total world” fund — just in such a tiny size it’s more a souvenir than a real allocation. Takeaway: if global diversification is the goal, 8–10% outside the US is more like a polite nod than a serious strategy.
This breakdown covers the equity portion of your portfolio only.
Market cap breakdown is mostly mega and large cap — about two-thirds of the portfolio — with mid, small, and a smidge of micro bringing up the rear. Basically, you own the household-name giants with a small side bet on the scrappy underdogs via small-cap value. Nothing extreme here, but don’t kid yourself that this is some bold small-cap play; it’s more like a garnish. The giants will drive the bus, the small caps are just noisy passengers. Takeaway: if your goal was “own the big stuff with a small spicy tilt,” you accidentally nailed it. If you thought you were ultra-tilted to small, you’re not.
The look-through shows the usual suspects — NVIDIA, Apple, Microsoft, Amazon, Alphabet, Meta, Tesla — all popping up through multiple funds, even though only ETF top-10s are counted. That means overlap is almost certainly worse under the hood. You’ve basically built a shrine to US megacap tech inside several different wrappers, then pretended they’re separate bets. Holding total market, world, growth, tech, and a target date fund is like buying five greatest hits albums from the same band. Takeaway: if the same names dominate across funds, you’re less diversified than the fund count wants you to believe.
Factor exposures are estimated using statistical models based on historical data and measure systematic (market-relative) tilts, not absolute portfolio characteristics. Results may vary depending on the analysis period, data availability, and currency of the underlying assets.
Factor profile is shockingly normal. Value, size, momentum, and quality all sit around “neutral,” meaning you basically get whatever the broad market is doing without big style bets. The only notable thing: low volatility is a bit higher than average, suggesting a mild preference for slightly steadier names, and yield is low, so you’re not chasing dividends. Think of factors as the hidden ingredients in your cereal; here, it’s close to the default recipe with a tiny “less crazy” tilt. Takeaway: this portfolio behaves like a fairly standard growth-leaning index setup, not some secret quant masterpiece or meme-infested roller coaster.
Risk contribution reveals who’s actually shaking the portfolio, not just sitting in it. Your top three positions — target date fund, total stock market, and growth ETF — are 87% of total risk. That’s a lot of power in a pretty small committee. Risk/weight ratios above 1.0 for growth, small-cap value, and tech show they’re punching slightly above their size, but nothing is totally unhinged. Still, when over half the portfolio is in a fund-of-funds plus another big broad index, you’re basically doubling down on the same engine. Takeaway: trimming overlapping giants and giving distinct roles to each holding can keep risk from being accidentally concentrated in the same flavor.
Your correlation list is basically shouting, “Why did you buy all these things that move together?” Total world, total US, target date, growth, and tech are all highly correlated. Translation: when one sneezes, the others catch the same cold at the same time. This doesn’t kill you in normal markets, but during a crash you’ll discover how little “diversification” you actually had. Different tickers don’t matter if they’re all dancing to the same song. Takeaway: diversification is about owning stuff that behaves differently, not just owning more line items that all trace the same roller coaster with slightly different ticket prices.
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.
On the efficient frontier, you’re actually… efficient. The Sharpe ratio (a “how much return per unit of risk” score) is 0.56 for the current setup, and the optimizer says you’re basically on the curve. Max Sharpe and minimum variance portfolios would reweight things for either higher return or lower risk, but they don’t magically leap to another universe; you’re already in the right neighborhood. That’s grudgingly impressive for such a Frankenstein mix. Takeaway: the ingredients are fine, and the proportions are surprisingly competent — you could likely clean up complexity without sacrificing this risk–return balance.
Total yield around 1.67% is firmly in the “we’re here for growth, not checks in the mail” zone. The only real yield flex is AT&T with its 3.9%, which feels more like a security blanket than a serious income plan. You’ve also sprinkled in “dividend appreciation,” but at such a small weight it’s not exactly printing rent money. For a long-term growth setup, a lower yield isn’t a sin; it just means you’re relying on price growth instead of payouts. Takeaway: if someone here thinks they’ve built an income machine, they’re going to be very confused when the distributions show up.
Costs are actually suspiciously good. A blended TER of 0.07% is “did I just out-cheap Vanguard at being Vanguard?” territory. Even the most expensive piece, the small-cap value ETF, is only 0.25%, which is hardly villain-level. The real joke is that you’re paying ultra-low fees to hold multiple versions of the same exposure. It’s like proudly using coupons to buy five copies of the same book. Takeaway: fees aren’t your problem; structure is. If you ever simplify this mess, you could keep these low costs and lose the redundancy — without giving up performance potential.
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