This portfolio is built almost entirely from equities, with broad index ETFs forming the core and a handful of handpicked single stocks around them. The largest position is a global equity ETF at nearly 40%, which acts like the “spine” of the portfolio. Around it, there are regional ETFs, small and mid-cap funds, a thematic AI fund, a healthcare fund, plus a small allocation to gold. This structure mixes very broad exposure with a few targeted tilts. It means most returns will be driven by overall global stock markets, while the satellites can create differences versus standard indices, both on the upside and the downside.
Over the period since mid‑2021, €1,000 in this portfolio grew to about €1,778, which is a compound annual growth rate (CAGR) of 12.61%. CAGR is like your average speed on a long car trip, smoothing out bumps along the way. The portfolio very slightly lagged the US market but clearly beat the global market benchmark, while also suffering a smaller maximum drawdown than both. The sharpest drop was about ‑18.5%, recovering in around six months. This mix of strong growth with smaller drawdowns suggests a good balance between capturing equity upside and limiting extreme downside moves, though past results never guarantee similar future outcomes.
The Monte Carlo projection uses thousands of simulated paths based on historical behaviour to imagine many possible futures. Think of it as rerunning market history with the numbers shuffled each time. For a €1,000 starting point over 15 years, the median outcome lands around €2,694, with a wide but informative range from roughly €978 to €7,577 in most simulations. The average simulated annual return is about 8.02%. These numbers show that, over long periods, outcomes tend to cluster in a positive area but can still vary a lot. Simulations depend heavily on past data and assumptions, so they provide a rough map rather than a precise forecast.
Asset‑class exposure is very straightforward: about 96% in stocks and roughly 3% in “other,” mainly physical gold. A stock‑heavy mix like this usually means returns will be driven overwhelmingly by company earnings and equity market sentiment, not by bonds or cash. The small gold sleeve adds a different type of asset that often behaves differently from shares, especially around crises or inflation scares. Relative to many mixed portfolios that hold sizable bonds, this one intentionally stays in the higher‑risk, higher‑return part of the spectrum, while gold offers only a modest counterweight if equity markets experience sharp shocks.
This breakdown covers the equity portion of your portfolio only.
Sector exposure is spread across financials, technology, industrials, telecoms, healthcare, staples, materials, and others. Financials and technology stand out as the biggest slices, together making up about 45% of the portfolio. That’s a bit more tilted to financials than many global indices, which can influence how the portfolio reacts to interest rates and credit conditions. A meaningful allocation to healthcare and consumer staples adds some defensive flavour, as these sectors often hold up better in economic slowdowns. The AI thematic ETF and big tech names also inject growth potential but can add sensitivity to policy changes, regulation, and shifts in innovation cycles.
This breakdown covers the equity portion of your portfolio only.
Geographically, the portfolio is clearly global but with a strong North American tilt at about 60%, followed by developed Europe at 18% and developed Asia plus Australasia making up much of the rest. Emerging markets are present but relatively small. This structure is broadly in line with many global equity indices, which are also dominated by North American companies. The alignment with global market weights is a positive sign for diversification, because it reduces the chance that a single region dominates unexpectedly. At the same time, it means performance will still be heavily influenced by North American economic conditions and currency moves against the euro.
This breakdown covers the equity portion of your portfolio only.
By market capitalization, the portfolio leans toward larger companies: roughly half in mega‑caps and about a third in large‑caps. Mid‑caps and small‑caps together make up a meaningful minority, with a small allocation to micro‑caps. Large and mega‑cap companies often bring more stable earnings, established business models, and deeper trading liquidity. Mid and small‑caps, on the other hand, tend to be more volatile but can offer stronger growth in certain periods. This blend is quite typical for diversified global equity portfolios and helps smooth the ride: the big names provide an anchor, while the smaller ones add some extra growth potential and diversification.
This breakdown covers the equity portion of your portfolio only.
Looking through the ETFs, the largest individual exposures are mainly the handpicked single stocks like Berkshire Hathaway, Linde, DBS, Microsoft, Alphabet, Schneider Electric, Procter & Gamble, and Walmart. These appear almost entirely as direct positions, not repeated significantly inside ETF top‑10 holdings. The main overlaps visible are with mega‑cap US names such as NVIDIA and Apple, which show up through the global index ETFs. This suggests hidden concentration from overlap is present but not extreme based on the top‑10 data. Since only ETF top‑10 holdings are captured, additional overlap in smaller positions is likely understated but still seems well spread across many companies.
Risk contribution shows how much each holding drives the portfolio’s overall ups and downs, which can differ from its weight. The core MSCI World ETF is 38.81% of the portfolio but contributes around 42.71% of total risk, so it slightly dominates the risk picture. In contrast, Berkshire Hathaway’s risk share is a bit lower than its weight, suggesting it behaves somewhat more steadily than the typical equity in this mix. The AI and mid‑cap ETFs contribute more risk than their weights would suggest, reflecting their higher volatility. Overall, the top three positions account for about 56% of total risk, highlighting a meaningful but not extreme concentration around the core holdings.
The correlation data highlights that the world small‑cap ETF and the US mid‑cap ETF move almost identically. Correlation is a measure of how often two assets move in the same direction; when it is very high, holding both gives less diversification than the number of positions might suggest. Here, having both small‑cap and mid‑cap exposure still broadens the opportunity set, but in practice they will likely surge and dip together in many market conditions. This doesn’t make them bad holdings; it just means they collectively behave like a single risk bucket in stressful times, rather than two fully independent diversifiers.
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.
The efficient frontier analysis compares the current mix to the best possible combinations of the same holdings. The current portfolio has a Sharpe ratio of 0.8, meaning its return per unit of risk is decent but not optimal. The optimal and minimum‑variance portfolios on the frontier show meaningfully higher Sharpe ratios at similar or even lower risk levels. Being about 11.9 percentage points below the frontier at the current risk level suggests that simply reweighting these existing holdings—without adding anything new—could improve the balance between risk and return. Still, the portfolio already achieves attractive returns, so this is more about fine‑tuning than a structural issue.
The portfolio’s costs are impressively low. The individual ETFs mostly sit in the 0.18–0.35% total expense ratio (TER) range, and the overall blended TER comes out around 0.15%. TER is the annual fee charged by a fund, and while it looks small, it compounds over time. Being this low means less performance is eaten by ongoing charges each year, supporting better long‑term outcomes compared with higher‑fee products tracking similar markets. This is a strong alignment with cost‑efficient investing principles. With such a globally diversified equity mix, low costs are especially helpful because they are one of the few factors investors can reliably control.
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