This portfolio is a simple three‑ETF mix fully invested in global equities. Around 70% sits in a broad global equity fund, with 15% in global small‑cap value and 15% in emerging markets. So most risk and return come from global stocks, with smaller but meaningful tilts toward cheaper smaller companies and developing economies. This kind of structure is easy to understand and manage because there are only a few moving parts. It’s also broadly diversified by design, which reduces reliance on any single company or country. Because the history is only about 1.4 years, the way this mix behaves in harsher or very different market conditions is still largely unknown.
Over roughly 1.4 years, €1,000 in this portfolio grew to about €1,225, a Compound Annual Growth Rate (CAGR) of 15.5%. CAGR is like average speed on a road trip: it smooths out bumps along the way. Over this short period the portfolio outpaced both the US market and the global market, but with a similar maximum drawdown around -21%. That drawdown took two months to the bottom and about five months to recover, which is a normal equity‑like pattern. Only seven days accounted for 90% of returns, showing how a handful of strong days drive results. Because the sample is so short, it’s risky to treat this performance as a stable long‑term pattern.
The Monte Carlo projection uses the limited historical data to simulate many possible 15‑year paths for €1,000 invested. Monte Carlo is essentially a “what if” engine: it shuffles returns in thousands of ways based on past behaviour to show a range of future outcomes. Here, the median outcome is about €2,812, with most simulations landing between roughly €1,793 and €4,336. There are also less likely but more extreme results on both the upside and downside. The overall average simulated annual return is about 8.1%. Because all this is built on only 1.4 years of history, the projections are fragile and should be viewed as rough illustrations, not reliable forecasts.
All of this portfolio is in stocks, with 0% in bonds, cash, or other asset classes. That makes the structure straightforward: returns mainly follow the ups and downs of global equity markets, without the cushion that bonds or cash can sometimes provide in downturns. A 100% equity mix usually has higher long‑term return potential but also bigger swings along the way. The portfolio’s risk score of 4/7 and “Balanced” label likely reflect how it behaved in this short window, not a full cycle. Over a longer period, a pure equity mix would typically behave more like a growth‑oriented portfolio than a classic balanced one.
Sector exposure is spread across many parts of the economy, with technology at 22%, financials at 19%, and industrials at 14%. The rest is split across consumer‑related sectors, energy, telecoms, health care, materials, utilities, and real estate, each in single‑digit percentages. This is a broadly diversified sector mix and looks reasonably aligned with typical global equity benchmarks, which is helpful because it avoids extreme bets on any single area. A moderate tech tilt means the portfolio may be somewhat sensitive to changes in interest rates and innovation cycles, while the meaningful weight in financials can respond more to credit and economic conditions. Overall, sector balance here is a clear positive.
Geographically, the portfolio is strongly global but with a clear lean toward North America at 62%. Europe developed markets make up 13%, with Japan, developed Asia, and emerging regions filling out the rest. This is broadly in line with many global equity indices, which are also dominated by North American stocks, so it aligns well with common global market weights. The emerging markets sleeve adds exposure to faster‑growing but more volatile economies, which can behave very differently from developed markets. While that can boost diversification, the short history means the portfolio hasn’t yet been tested through a full emerging‑market stress cycle in this exact configuration.
By market size, the portfolio is spread across the spectrum: 29% in mega‑caps, 24% in large‑caps, 24% in mid‑caps, 15% in small‑caps, and 7% in micro‑caps. That’s a much broader size distribution than a typical market‑cap‑weighted global index, which is usually dominated by mega and large companies. The extra exposure to small and micro‑caps comes mainly from the dedicated small‑cap value ETF and can add both diversification and additional volatility. Smaller companies often move more sharply in both directions and can behave differently from large household names. This spread across sizes is a deliberate feature and helps explain some of the portfolio’s factor tilts and recent return pattern.
Looking through the ETFs’ top holdings, the biggest underlying exposures include familiar global giants like NVIDIA, Apple, Amazon, Microsoft, Alphabet, Meta, and Taiwan Semiconductor. Together, the top 10 look‑through names account for only a small slice of the overall portfolio, and there are no direct single‑stock positions. That suggests no obvious hidden concentration in a single company from the data we can see. However, ETF coverage here is limited to each fund’s top 10, capturing only about 18% of the ETFs’ assets. That means any overlap in smaller positions isn’t fully visible, so true concentration may be slightly higher than reported.
Risk contribution shows how much each holding drives the portfolio’s overall ups and downs, which can differ from its weight. A holding can be a small slice of the pie but still dominate volatility if it’s especially jumpy. Here, the broad global equity ETF is 70% of the portfolio and contributes about 69.6% of total risk, so its impact on volatility is almost exactly proportional. The small‑cap value fund is 15% of the weight but about 16.2% of the risk, slightly punching above its size, while emerging markets are 15% weight and 14.1% risk. That pattern suggests the portfolio’s risk is well spread across the three funds without any single one dominating disproportionately.
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 chart compares this portfolio’s risk and return to the best possible combinations of the same three ETFs. The current mix has a Sharpe ratio of 0.75, where Sharpe measures risk‑adjusted return (how much excess return you get per unit of volatility). The optimal simulated mix shows a higher Sharpe of 1.47, and even the minimum‑variance blend has a Sharpe of 1.01. The current portfolio sits about 3.6 percentage points below the frontier at its risk level, meaning that, based on this short history, a different weighting of these same funds could have delivered a better risk/return balance. Because the sample period is so brief, this optimisation result should be treated as illustrative rather than definitive.
The total ongoing cost, or TER (Total Expense Ratio), of the portfolio is about 0.26% per year. TER is the annual fee charged by the funds to cover management and operating expenses, deducted inside the ETF. For a fully active or factor‑tilted global equity mix, this level is quite competitive and helps keep more of the gross return in the portfolio. Over long horizons, even small fee differences compound, so having costs this low is a structural strength. For example, on €10,000, a 0.26% TER is €26 a year before compounding effects. Importantly, the cost advantage doesn’t guarantee better returns, but it removes one persistent drag.
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