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 two flavours of the same global equity smoothie split 50/50 for no obvious reason. One fund holds the whole investable stock market, the other holds the whole world minus one big region and then the first one quietly adds that region back. It’s like buying a “no cheese” pizza and then ordering extra cheese on the side. The result is fine, just needlessly fiddly. Takeaway: if two holdings end up giving almost the same broad global exposure, you’re not being clever, you’re just adding extra moving parts for almost no change in outcome.
Performance-wise, this thing has actually behaved like a grown-up. A 10.81% CAGR over the period means €1,000 became €1,235, slightly beating both the US market and the global market. CAGR (compound annual growth rate) is basically your average speed on a road trip, ignoring the potholes. Max drawdown of about -19% is very normal for a 100% equity portfolio, and better than both benchmarks. Just remember: this is a short, unusually strong window, not a prophecy. Past data is like last year’s weather — helpful, but it doesn’t sign a contract for the future.
The Monte Carlo projection is the part where a computer plays 1,000 alternate futures with your money and averages the chaos. Median outcome of €2,899 from €1,000 in 15 years at 8.45% annualised is decent, but the range is wide: from about “barely grew” to “nice early retirement weekend upgrade.” This method throws random shocks at the portfolio based on past volatility and returns, but it can’t predict crises we haven’t seen before. Think of it as a flight simulator, not a crystal ball. Takeaway: accept the range, not the exact number — the band is the message.
Asset class “diversification” here is easy: there isn’t any. It’s 100% stocks, 0% anything else. That’s like going to a buffet and only eating fries — delicious in bull markets, but not great when things turn. For a “balanced investor” label, this is straight-up aggressive risk: no bonds, no cash buffer, no stabilisers. Takeaway: being all-equity can be totally fine with a long time horizon and strong stomach, but emotionally it has to be treated as high risk, whatever the risk score system claims.
Sector mix is surprisingly sane: financials, tech, and industrials lead, with everything else sprinkled in. No single sector is completely hijacking the show, and nothing is absurdly neglected either. Technology at 17% is meaningful but not full-blown “AI cult” territory. This is basically what happens when you stop trying to be clever and just hold the whole market. The hidden catch: when the global market has a blind spot or bubble in any sector, this portfolio obediently inherits it. Takeaway: you’re not overbetting on a theme, but you are handcuffed to whatever the world market is obsessed with.
Geographically, this looks like someone actually read a book once. Roughly 38% North America, 35% developed Europe, then Japan and other developed regions, with a tiny pinch of emerging markets. For a European-based investor, this is a pleasantly global look instead of the usual “home country plus a vague global ETF” mess. That said, emerging exposure at 2% is more like a seasoning than a real bet. Takeaway: global diversification is not the problem here — in fact, it’s one of the few areas that doesn’t need an eye roll.
The market cap breakdown is textbook: almost half in mega-caps, a solid chunk in large caps, and a long tail down to micro-caps. In other words, this is basically a love letter to massive global corporations with a polite nod to everyone smaller. Nothing extreme, no weird “tiny companies only” obsession, no “only giants allowed” dictatorship. This is the standard “own the whole market, just weighted by size” setup. Takeaway: the portfolio will behave like the global stock market’s big-name index, not a wild small-cap roller coaster.
The look-through holdings scream “closet tech nerd in denial.” NVIDIA, Apple, Microsoft, ASML, Amazon, Alphabet, TSMC, Broadcom — the usual mega-cap suspects are all hiding in the top exposures. Because we only see ETF top 10s, the overlap is actually understated, but it’s already clear you’re riding a very similar group of giant names twice. Hidden concentration like this means you think you own thousands of companies equally, but a small group of mega-stars quietly call the shots. Takeaway: broad index funds still have favourites, and they’re mostly the same ones.
Risk contribution tells you who’s actually shaking the portfolio, not just who looks big on paper. Here it’s almost comically simple: one ETF contributes ~52% of the risk, the other ~48%. No tiny position secretly behaving like a maniac, no concentrated single-name landmine. The only “issue” is that both funds are basically different wrappers on global equities, so they rise and fall together. Trimming risk here wouldn’t be about picking a villain; it’d be about accepting that 100% stocks is always going to move a lot, no matter how you slice it.
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 risk–return chart, this portfolio sits right on or very near the efficient frontier, which is frankly annoying because it leaves less to roast. The efficient frontier is the curve of best possible return for each risk level using the current ingredients. Sharpe ratio of 0.55 vs 0.8 for the optimal setup says you could squeeze a bit more efficiency out just by reweighting, but you’re already in the “not dumb” zone. Takeaway: the mix is basically fine; any improvements would be tuning, not surgery. For a two-ETF mashup, that’s impressively untragic.
Costs are almost insultingly normal. A blended TER around 0.20% is low enough that it doesn’t deserve drama. One fund charges 0.40%, which isn’t heroic, but the overall mix ends up cheap thanks to the other one. TER (total expense ratio) is the annual fee the fund quietly skims — like a tiny subscription you can’t cancel. Here, you’re not lighting money on fire. Takeaway: fees are under control — which, given how random the two-fund combo looks, is a pleasantly lucky outcome rather than design genius.
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