This portfolio is built from three ETFs, with one broad global equity fund making up about two‑thirds of the weight. A dedicated global semiconductor ETF is the second key building block at just under a third, and a small European defence ETF rounds it out. So structurally it’s mostly a plain global index, with a clear “booster” slice pointing at a specific industry, plus a small thematic add‑on. This kind of setup matters because overall behaviour is driven by those two big funds, while the third adds only a subtle twist. The mix gives a blend of wide diversification through the core ETF and concentrated growth exposure through the semiconductor sleeve.
Over the period shown, CHF1,000 grew to about CHF2,095, which is a very strong result in a relatively short time. The portfolio’s compound annual growth rate (CAGR) of 40.42% far exceeded both the US market and the global market, which were in the mid‑20% range. CAGR is like average speed on a road trip, smoothing out bumps to show typical yearly growth. Max drawdown, the largest peak‑to‑trough fall, was around ‑23.5%, similar to the benchmarks, and recovered within a few months. This mix of much higher return without noticeably deeper worst‑case falls reflects how powerful the semiconductor tilt has been in this particular window, but that effect may not repeat.
The forward projection uses Monte Carlo simulation, which is basically running thousands of “what if” market paths based on historical ups and downs. Here, CHF1,000 has a median outcome of about CHF2,839 after 15 years, implying an annualised return around 8.2% across all simulations. The likely middle band ranges from roughly CHF1,869 to CHF4,396, with more extreme but still plausible paths stretching from about CHF1,069 to CHF7,541. That wide spread shows how uncertain long‑term investing can be, even when the average looks attractive. Importantly, these projections lean on past behaviour and statistical patterns, so they’re more like weather forecasts than guarantees: helpful for context, but never precise promises.
On the asset‑class view, about 70% of the portfolio is clearly tagged as stocks, with the remaining 30% in a “no data” bucket where the system simply lacks classification detail. That doesn’t mean those positions are something exotic; it just reflects incomplete tagging. From what is visible, the equity share already puts this firmly in the growth‑oriented camp, matching the stated risk classification. High equity weight is relevant because stocks tend to drive both long‑term returns and short‑term swings. The visible allocation shows meaningful exposure to the global equity markets, which is typically where most of a long‑run growth profile comes from.
Sector data shows a clear tilt towards technology, at about 21%, with financials and industrials as the next largest buckets. This is in line with what you’d expect from a global equity fund plus an added semiconductor ETF, because chip companies mostly sit inside the technology category. Compared with a broad global benchmark, the technology share here is meaningfully higher, while areas like utilities and real estate are relatively small. Sector mix matters because different industries react differently to things like interest rates or economic slowdowns. A higher technology component often brings stronger growth potential but also more sensitivity to cycles in innovation spending and investor sentiment.
Geographically, the portfolio leans heavily into North America at 44%, with additional exposure to developed Europe, developed Asia, Japan, and smaller slices in emerging regions. This pattern is broadly consistent with many global equity indices, which are also dominated by North American companies, especially large US firms. The presence of allocations across Europe, Asia, and emerging markets supports the strong diversification score and helps spread risk across multiple economies and currencies. Compared with a pure US fund, this structure reduces dependence on a single region’s politics, regulations, and macro trends, while still capturing a big share of global corporate heavyweights that drive index returns.
By market capitalisation, around 35% of the portfolio sits in mega‑cap companies, with large‑caps at 24% and mid‑caps at 11%. Mega‑caps are the very largest listed firms, often familiar global brands; they tend to be more stable and liquid but can also dominate index behaviour. This split is very typical for global index‑based portfolios, where the biggest companies naturally take the largest weights. Having most exposure in mega and large‑caps means performance is closely tied to these corporate giants, while the smaller mid‑cap slice adds a bit of extra growth and volatility. Overall, the size mix looks well‑aligned with common global equity benchmarks.
Looking through the ETFs, a handful of big names account for a meaningful chunk of exposure: Nvidia, Broadcom, TSMC, Apple, Microsoft, AMD, ASML, Intel, Amazon, and Micron all feature. Because several of these appear in both the global equity fund and the semiconductor ETF, there is notable overlap that creates hidden concentration in key chip and tech platforms. For example, Nvidia alone is about 5% of the total portfolio from ETF holdings. It’s worth keeping in mind that this overlap is probably understated, since only each ETF’s top 10 positions are captured. Still, the pattern is clear: large technology and semiconductor leaders are central drivers here.
Risk contribution numbers show how much each holding adds to the portfolio’s overall ups and downs, which can differ a lot from simple weights. Here, the core global ETF is about 67% of the weight but contributes roughly 50% of risk, so it’s actually a bit less volatile than its size alone would suggest. The semiconductor ETF is around 30% of the weight yet drives over 47% of total risk, reflecting how punchy that segment can be. The small defence ETF adds only a few percent of both weight and risk. In effect, the semiconductor slice acts like a “volume knob,” disproportionately influencing day‑to‑day fluctuations.
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 risk vs return chart shows the current mix sitting on or very close to the efficient frontier, which is the curve of best achievable returns for each risk level using these three holdings. The current portfolio’s Sharpe ratio of 1.41 (a measure of return per unit of risk above cash) is solid and compares well with the minimum‑variance option, though the max‑Sharpe configuration would take on noticeably more risk to seek much higher returns. The key point is that, given these same ETFs, the weights are already making effective use of them. Any improvement would be more about personal risk appetite than inefficiencies in construction.
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