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 portfolio is basically three layers of the same global equity cake with some factor icing on top. Two broad market funds eat up 60% of the weight and then three factor ETFs are sprinkled in like someone discovered smart beta and couldn’t pick a favorite. It looks diversified at a glance, but most roads still lead back to the same big global companies. Structurally, it’s neat and tidy, but also a bit of a copy‑paste job. The result is less “thoughtful architecture” and more “semi-random ETF bundle” that just happens to work because global equity markets have been generous lately.
Historically this thing has absolutely flown: turning €1,000 into €1,685 in under three years with a 23.54% CAGR. That’s spicy growth, beating both the US market and global market by about 4.5 percentage points a year. Max drawdown of -20.11% is no joke, but it’s actually shallower than the benchmarks, and it recovered in about five months, which is fairly brisk. But this whole period includes a big tech-led surge and factor behavior that might not repeat. Past performance is basically yesterday’s weather: great for storytelling, terrible for prophecy, especially over such a short and unusually hot stretch.
The Monte Carlo simulation is the “what if machine” that reruns the future 1,000 different ways using past volatility and returns as rough inputs. Median outcome of €2,829 from €1,000 over 15 years and a central range of roughly €1,800–€4,400 screams “equity rollercoaster” more than “steady glide path.” The fact that one plausible outcome is barely breaking even (€958 at the 5th percentile) shows how easily timing and bad luck can wreck the story. Simulations are educated guesses dressed up in decimals; they reuse historic chaos to imagine future chaos, but they’re still just fancy guesswork with nicer charts.
Asset-class breakdown is extremely subtle here, because there is none: 100% stocks, 0% everything else. This is not a balanced portfolio; it’s an equity monolith wearing a “balanced investors” label like a joke name tag at a party. When the world is calm, this looks smart and efficient. When markets crack, there’s nothing here that historically zigged while stocks zagged. Being all-in on stocks can work out beautifully over long horizons, but it also means every punch the market throws lands directly on the portfolio’s face, with no bonds or alternatives to absorb impact.
Sector mix is basically “tech and friends.” Technology at 28% leads the show, with financials and industrials trailing respectfully behind. Nothing is absurdly concentrated, but it’s still a growth-and-cyclical-heavy lineup with relatively little in the “boring but steady” camp. It’s like a band where all the members are lead guitarists and nobody wants to play drums. In roaring bull markets, this sector profile looks inspired; in downturns, it tends to mean that everything exciting sells off together, and the supposedly defensive bits of the portfolio are more like slightly less reckless party guests.
Geographically, this is very “world market index, but please make it US-centric.” Around 55% in North America with 22% in developed Europe and only crumbs left for the rest of the planet. It’s not outrageous by global index standards, but it does quietly say “the US and some European sidekicks will decide my fate.” The tiny allocations to Latin America, Africa/Middle East, and emerging Europe are so small they’re basically garnish. That means if developed markets stumble together, this portfolio doesn’t have much truly independent engine room elsewhere to carry the load.
Market cap exposure is dominated by giants: 47% mega-caps and 38% large-caps, with just a polite 14% nod to mid-caps. This is classic index-style “own the winners of the last decade” behavior. It’s like shopping only from the top shelf because that’s where the famous brands live. Mega-caps can be stable, but they also drag the portfolio into whatever narrative drives big, crowded names. The near absence of smaller companies means less room for idiosyncratic growth stories and more dependence on a handful of global behemoths continuing to run the show without messing up.
The look-through holdings reveal the usual suspects: NVIDIA, Apple, Microsoft, TSMC, Amazon, Alphabet, Meta, Tesla — basically the “Magnificent Seven plus friends” fan club. They show up across multiple ETFs, so exposure compounds in the background. Even with only top-10 ETF data, NVIDIA alone sneaks up to 3.68%, and Apple isn’t far behind. Overlap is almost certainly higher than shown, because most of the portfolio beyond the top 10 holdings is invisible here. This hidden concentration means the portfolio is much more of a mega-tech bet than the calm-looking ETF list suggests at first glance.
Risk contribution is weirdly tidy: weights and risk contributions are almost one-to-one. The 30% S&P 500 ETF contributes 31.02% of risk, the 30% ACWI fund adds 29.83%, and the others sit very close to their weights. That means nothing is secretly blowing up volatility behind the scenes; the top three holdings simply dominate risk because they dominate the portfolio, together driving over 76% of total risk. This is not a chaotic structure, just a very top-heavy one. So when things move, it’s mostly those broad funds steering the ship while the factor ETFs quietly ride along.
The correlation section basically exposes the obvious: the S&P 500 ETF and the ACWI ETF move almost identically. Shocking, given that ACWI is about half US stocks and the other half things that broadly follow US behavior. High correlation means when one takes a hit, the other doesn’t heroically save the day; it joins in. Holding both is less “two strong pillars” and more “two versions of the same pillar with slightly different stickers.” It’s not disastrous, but it does mean the illusion of diversification is stronger than the actual shock-absorbing power.
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, this portfolio sits a bit awkwardly below where it could be. With a Sharpe ratio of 1.34 versus 1.81 for the max-Sharpe mix, it’s like showing up to the party underdressed despite having the right clothes in the same suitcase. The frontier says: using only these existing holdings, a different weighting could get either more return for the same risk or less risk for similar return. Being 2.45 percentage points below the frontier at current risk is basically the universe saying, “Nice ingredients, slightly clumsy recipe.”
Costs are the one area where this portfolio doesn’t embarrass itself. A total TER of 0.26% for an all-ETF lineup with factor tilts is actually respectable — almost suspiciously reasonable. Sure, some of the individual funds charge on the chunky side (0.40% and 0.45% aren’t exactly bargain-bin), but the overall blend doesn’t bleed too hard. It’s like paying economy-plus prices for a slightly fancier index experience. Fees aren’t the villain in this story; they’re just mildly annoying background noise compared to the much bigger narrative driven by equity risk and concentration.
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