This portfolio is built entirely from equity ETFs, with three broad global building blocks at 25% each and two more focused thematic positions making up the remaining 25%. The core funds target global developed markets, momentum, value, and non‑US stocks, while the satellites focus on semiconductors and European defence. Structurally, this is a “core plus satellites” mix: a diversified base with concentrated overlays in specific themes. Because everything is in stocks, portfolio behaviour is driven mainly by equity markets rather than bonds or cash. The short 1.1‑year data window means the current structure has only been tested through a limited market environment, so any patterns seen so far might not hold across a full market cycle.
Over roughly 1.1 years, a hypothetical CHF1,000 grew to CHF1,708, implying a compound annual growth rate (CAGR) of about 64.8%. CAGR is like an average yearly “speed” over the period. This very high figure reflects an unusually strong run, helped by the semiconductor and momentum exposures. The maximum drawdown, or worst peak‑to‑trough drop, was -8.5%, slightly deeper than the US and global benchmarks but still relatively modest. The portfolio outpaced both benchmarks by over 25 percentage points in CAGR, but such outperformance over a short window can be heavily path‑dependent. With only a bit more than a year of history, these numbers show what happened recently, not what’s typical over the long term.
The Monte Carlo projection uses the limited past returns and volatility to simulate 1,000 possible 15‑year paths for CHF1,000. Monte Carlo is like running many “what if” market histories where returns vary randomly based on recent patterns. The median outcome of about CHF2,870 corresponds to an annualised return around 8.1%, with a wide possible range from roughly CHF1,037 to CHF7,661 (5th–95th percentiles). Around three‑quarters of simulations end positive. Because the input data covers only 1.1 years—and a very strong one at that—these projections can be biased upward and are less reliable than if decades of history were available. They illustrate uncertainty and dispersion, but not a firm forecast.
All holdings are equity ETFs, so the asset‑class split is 100% stocks and 0% bonds or cash. This gives clear, undiluted exposure to equity market growth and volatility. In more mixed portfolios, bonds can dampen swings; here, any shock to global stocks flows through directly. Compared to broad multi‑asset benchmarks that blend equities with fixed income, this portfolio will typically experience larger short‑term ups and downs. The short lookback period, which has been mostly favourable for equities, may understate how sharp those swings can be in tougher environments. The benefit is straightforward participation in equity returns; the trade‑off is the absence of built‑in stabilisers from other asset classes.
Sector exposure is tilted heavily toward technology at 35%, with notable allocations to industrials (22%) and financials (15%), and smaller slices across the remaining sectors. This pattern reflects both the semiconductor ETF and the defence ETF, which sit inside technology and industrials. In many global indices, technology is large but not always at this level, and industrials are typically smaller, so the portfolio leans into these economic areas. Sector tilts matter because different sectors react differently to interest rates, economic cycles, and innovation trends. A tech‑heavy, industrial‑tilted portfolio may benefit strongly in innovation‑driven or rearmament cycles, but it can be more sensitive when regulation, demand cycles, or capital spending reverse.
Geographically, about 44% of the portfolio is in North America, 38% in developed Europe, and 13% in Japan, with small exposure to other developed regions and a minimal slice in Africa/Middle East. This is more internationally balanced than a typical global index that is often dominated by North America. The explicit “world ex‑USA” ETF shifts weight toward non‑US markets, while the defence ETF increases European exposure. Such a spread reduces dependence on a single economy or currency, which can be helpful when regional cycles diverge. However, the short historical window has mostly favoured certain regions and sectors, so the observed performance impact of this geographic mix may not represent a full economic cycle.
The portfolio is dominated by mega‑cap and large‑cap companies, together making up about 87% of exposure, with the rest in mid‑caps. This is broadly in line with mainstream global equity indices, where the biggest firms account for most market value. Large and mega caps often have more diversified businesses, stronger balance sheets, and deeper trading liquidity, which can make their price moves somewhat smoother than smaller companies. However, because the themed ETFs focus on specific industries, many of these large names still behave cyclically. The relatively small mid‑cap slice offers some additional growth potential and differentiation, but the risk and return profile will largely reflect the behaviour of global blue‑chip stocks.
Looking through ETF top‑10 holdings, a cluster of large semiconductor names—Micron, Intel, Broadcom, NVIDIA, ASML, AMD, TSMC, and Lam Research—appear prominently, plus defence‑related firms like Thales and BAE Systems. These overlaps mean the underlying exposure to certain companies is higher than any single ETF weight might suggest. For example, Micron alone totals about 4.2% of the portfolio when aggregating across funds. Since coverage only includes ETF top‑10 positions, hidden concentration is likely understated; additional holdings beyond the top‑10 could reinforce similar themes. This pattern shows how a few influential companies can drive a meaningful share of returns and risk even in a portfolio that appears diversified at the fund level.
Risk contribution shows how much each holding adds to overall portfolio ups and downs, which can differ from its weight. Here, the 15% semiconductor ETF contributes about 27.6% of total risk, nearly double its size, giving it the highest risk/weight ratio. The momentum ETF, at 25% weight, adds about 26.2% of risk, while value and ex‑US ETFs contribute less risk than their weights. The top three holdings together account for roughly 73.5% of portfolio risk, signalling concentrated risk in a few components despite diversified holdings. This means headline allocation percentages understate how much the portfolio’s behaviour is shaped by the semiconductor and momentum exposures, particularly during sharp moves in those areas.
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‑return optimization chart shows the current portfolio below the efficient frontier, with a Sharpe ratio of 2.85 versus 3.79 for the optimal mix using the same funds. The Sharpe ratio compares excess return to volatility, like measuring how much “bang for your risk buck” you get. Being 11.2 percentage points below the frontier at the current risk level indicates that, historically, a different weighting of these exact ETFs could have produced higher returns for similar risk. The minimum‑variance portfolio lies at lower risk and lower return but still with a respectable Sharpe. Because these metrics are based on a very strong short year, the apparent efficiency gap may be exaggerated compared with what would appear over longer periods.
Reported costs are low, with a total expense ratio (TER) around 0.12% and the factor ETFs at 0.25%. TER is the ongoing annual fee charged by funds; it comes out of returns automatically, so you never see a separate bill. These levels are competitive for global and factor‑based ETFs and compare favourably with many active funds charging significantly more. Over just a year, the difference between 0.12% and, say, 0.8% doesn’t look dramatic, especially in a strong market. But over 10–15 years, even small fee savings compound and can meaningfully increase the share of market returns that stays in the portfolio. The low‑cost structure here is a clear positive foundation.
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