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 really two overlapping US stock rockets dressed up as diversification. Eighty percent in the S&P 500 and twenty percent in the NASDAQ 100 is basically saying, “I like big US companies and I will only buy them.” It’s simple, sure, but it’s diversification the way a pizza with two toppings is “varied cuisine.” Everything rises and falls with one engine: US large-cap growth. The upside is you’re not pretending to be balanced with random filler. The downside is one theme dominates everything. Takeaway: this isn’t balanced; it’s a concentrated growth bet wearing a balanced-investor name tag.
The past decade has treated this setup like royalty: €1,000 growing to €4,182 with a 15.36% CAGR is straight-up stellar. CAGR, by the way, is your “average speed” over the whole trip, potholes and all. Max drawdown of -32.68% in 2020 was ugly but not worse than the benchmarks, and you bounced back fast. Also, only 45 days created 90% of returns — miss a few good days and this looks less heroic. But remember: this is the golden era of US mega-cap growth. Past data is yesterday’s weather: helpful, but it doesn’t promise another decade of sunshine.
Monte Carlo simulation is basically “what if we ran history 1,000 slightly different ways and saw how your money ends up?” Median outcome of €2,783 after 15 years on €1,000 is decent, but the range is wide: from around €966 to €7,668. That’s “break-even-ish” on the low side and “I’m a genius” on the high side. The average simulated return of 8.15% per year is solid but noticeably lower than the historical 15% party you just enjoyed. Translation: the model is politely telling you not to expect the last decade on repeat. This ride can still pay, just with more reality and less fairy tale.
Asset allocation: 100% stocks, 0% everything else. That’s not “balanced,” that’s “I heard bonds exist and chose violence instead.” Being all-equity is fine if the time horizon is long and nerves are made of steel, but the label “balanced investor” doesn’t match what’s actually happening. When markets tank, there’s nowhere to hide here; all the lights go red at once. Takeaway: if the goal is growth at any cost, this fits. If the goal is smoother rides and better sleep, the asset mix is about as subtle as a meme-stock Discord server.
Sector profile: Technology 38%, then telecom and consumer discretionary, with the rest sprinkled around like garnish. This is basically a growth-tech leaning portfolio that occasionally remembers other sectors exist. “Tech addiction detected” is fair — when tech and growth are on fire, returns look heroic; when they de-rate, you feel every downgrade headline. You’re not totally ignoring other sectors, but they’re clearly secondary characters. Takeaway: you’re making a bet on innovation and future earnings stories, not on boring, steady-every-year types. Just don’t pretend this is sector-neutral; it very much isn’t.
Geography: 99% North America, 1% Europe. This is not a global portfolio; this is “USA or bust” with a token European souvenir. For a European-based investor, that’s quite a currency and policy bet, whether intentional or not. You’re effectively saying the rest of the world’s markets are background noise. When the US leads, this is great. When other regions outperform or the dollar swings, you’re chained to one engine. Takeaway: calling this geographically diversified is like calling a burger “Mediterranean cuisine” because it has lettuce. It’s one country, one story.
Market cap split screams “only the big kids allowed”: 47% mega-cap, 36% large-cap, 17% mid-cap, and small-cap at a lonely 1%. This is pure love for the giants. The upside: these companies are more stable, more liquid, and tend to survive crises. The downside: you’re paying up for popularity and skipping the potential higher long-term returns (and chaos) in smaller names. This tilt means your performance is chained to how a handful of giants behave, not the broader business universe. Takeaway: this isn’t a market democracy; it’s rule by a mega-cap monarchy.
The look-through reads like a who’s-who of “things everyone already owns too much of.” NVIDIA 7.84%, Apple 6.71%, Microsoft, Amazon, Alphabet twice, Meta, Tesla, Berkshire — basically the market’s celebrity table. And you own many of them via both funds, so overlap is real, even if the numbers understate it. This is hidden concentration: different tickers, same underlying names doing the heavy lifting. It works great when the mega-cap darlings are winning; it feels awful when sentiment turns. Takeaway: this isn’t broad exposure to thousands of independent ideas — it’s the Magnificent Few running the show.
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 exposure: very low size and high momentum — classic “hot growth stock chaser” profile. Factors are the hidden ingredients that explain why your portfolio acts the way it does. Very low size means you’re heavily tilted away from smaller companies and deep into giants. High momentum means you love what’s been going up recently — great in strong markets, brutal in sudden reversals. Leaning hard into momentum while ignoring size diversification is like flooring the gas in a sports car and never driving in the slow lane. Takeaway: expect fast swings and trend-following behavior, not calm, steady compounding.
Risk contribution shows who’s actually shaking the portfolio, not just who’s taking space. Your S&P 500 ETF is 80% of the weight and about 77% of the total risk — very on-brand. The NASDAQ 100 is 20% weight but contributes nearly 23% of risk, so it’s punching slightly above its size in volatility. Nothing wildly disproportionate, but it confirms the obvious: that 20% “growth turbo” is what makes drawdowns sting more. Takeaway: trimming or boosting that NASDAQ slice is basically how you control the portfolio’s mood swings without changing the ingredients too much.
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 thing actually behaves like it did its homework. A Sharpe ratio of 0.69 for the current mix is below both the optimal Sharpe 0.93 and the minimum variance 0.84, but the note says you’re very close to the frontier given the holdings. Translation: for these two ETFs only, your weights are reasonably efficient for the risk level you’ve chosen. You’re not leaving huge performance on the table purely through bad mixing. Takeaway: the problem isn’t structure efficiency — it’s that the entire setup is one big concentrated growth bet. Efficient, but narrow.
Costs are actually one of the few grown-up things here. Total TER around 0.17% is nicely low — you’re not lighting money on fire in fees. Given that you’re basically buying broad, liquid, boringly efficient indices, anything much higher would be a crime. “Fees are under control — you must have clicked the right ETF by accident” applies perfectly. Still, low fees don’t magically fix concentration or factor risk; they just mean you’re getting your rollercoaster at a discount. Takeaway: cost side is solid, so any future improvements should focus on what you own, not how much it charges.
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