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 is a pure equity portfolio built entirely from five broad ETFs, with no bonds or cash buffer. The largest slice is a dedicated Korea ETF at just over 31%, followed by roughly equal weights in US and European broad-market funds, plus smaller sleeves in global and emerging markets funds. That structure makes growth the clear priority over stability or income. Having everything in stocks is powerful for long-term compounding but can feel rough during deep market drops. For someone using this as a core investment, the key takeaway is to be very comfortable with equity-level volatility and to manage short‑term cash needs outside this portfolio.
From mid‑2019 to early 2026, the initial €1,000 would have grown to about €2,119, a compound annual growth rate (CAGR) of 13%. CAGR is like average speed on a long road trip, smoothing out bumps along the way. This result slightly trails the US market but beats the global market, which is a solid outcome given the non‑US tilt. The worst historical drop, or max drawdown, was about ‑34%, in line with major equity indices. That shows this portfolio behaves like a full‑risk stock allocation; it has been rewarded with strong long‑term growth but demands tolerance for sharp temporary losses.
The Monte Carlo simulation projects many possible 10‑year paths by remixing historical return and volatility patterns. Think of it as running 1,000 “what if” market histories to see a range of outcomes, not a single forecast. In this case, the median scenario roughly quadruples the money, while even the pessimistic 5th percentile still shows a modest gain. That’s encouraging and reflects the historically strong equity performance. But simulations rely on the past being at least somewhat similar to the future, which is never guaranteed. The practical takeaway: long‑term growth potential looks high, but actual results could be much better or worse than the central estimate.
All of the money sits in stocks, with no allocation to bonds, cash, or alternatives. Asset classes are like different engines in a car; here, you’ve got only the high‑speed, high‑revving one. This structure maximizes exposure to equity growth but does not offer the usual risk‑dampening role that bonds or cash can play during market stress. Compared with many broad benchmarks that include some defensive assets, this is more aggressive. The key implication is that stability must come from outside this portfolio, for example via emergency savings or separate lower‑risk holdings, rather than from internal diversification across asset classes.
Sector-wise, the portfolio is dominated by technology at 34%, with financials and industrials making up another chunky share. Consumer and healthcare exposure is moderate, while defensive areas like utilities and real estate are relatively small. This tech‑heavy tilt is quite common in modern equity markets but still represents a conscious bias toward sectors that tend to move strongly with economic cycles and interest‑rate expectations. When growth and innovation are in favor, this kind of profile can outperform. During tech downturns or sharp rate hikes, swings can be more pronounced. A simple takeaway: sector diversification is decent, but growth‑sensitive areas clearly lead the story.
Geographically, there is a strong tilt to Asia Developed at 37%, driven largely by Korea, while North America and Europe Developed together make up just over half. Exposure to emerging Asia, Latin America, Africa, and Japan is quite small. This structure is noticeably different from a typical global index, which usually has the US as the dominant weight. That Korea/Asia tilt introduces both opportunity and concentrated country risk, especially given the large Samsung and SK Hynix exposures. When that region does well, the portfolio can shine versus global peers; when it struggles, returns may lag more diversified world allocations.
By market capitalization, the portfolio leans heavily into mega and large companies, with nearly 90% in those brackets and only a small slice in mid caps. Market cap is simply the total value of a company’s shares; bigger companies tend to be more stable and widely researched. This large‑cap focus means the portfolio should behave similarly to mainstream indices in terms of liquidity and volatility, without the extra bumpiness that small caps often bring. On the flip side, it forgoes the potential higher long‑term returns that smaller, more nimble firms sometimes deliver. Overall, the size mix is conventional and aligns closely with common benchmarks.
Looking through the ETFs, the biggest underlying exposure is Samsung Electronics at just over 10%, followed by SK Hynix near 6%. Several global tech leaders like NVIDIA, TSMC, Apple, Microsoft, and ASML also appear, some likely in multiple ETFs. Because only top‑10 ETF holdings are captured, true overlap is probably higher than it looks. Hidden overlap matters: if the same company appears in different funds, the portfolio is more concentrated than the ticker list suggests. The clear takeaway is that a meaningful chunk of risk is tied to a small group of large tech‑heavy names, especially in Korea and global semiconductors.
Factor exposure shows a strong tilt toward momentum and a smaller tilt toward size. Momentum means favoring stocks that have been recent winners; historically, these can continue to outperform in trending markets but can reverse sharply when sentiment turns. Size exposure here indicates a mild bias away from the very largest names toward somewhat smaller ones, though the portfolio is still mostly big caps overall. Factor investing is like choosing ingredients in a recipe: certain mixes can enhance flavor but also change how the dish reacts under heat. The key implication is that this portfolio may do particularly well in persistent uptrends but could be more vulnerable during sudden shifts.
Risk contribution highlights that the Korea ETF, at about 31% weight, is responsible for over 42% of overall portfolio volatility. Risk contribution measures how much each holding adds to the portfolio’s ups and downs, which can diverge from its pure weight. The top three funds together drive nearly 77% of risk, showing that a few building blocks effectively control the experience. This concentrated risk is not automatically bad if it matches the intended strategy, but it is important to be aware of. Adjusting position sizes is the main lever for bringing risk contributions more in line with desired emphasis across regions and styles.
The correlation data shows that the US large‑cap ETF and the global all‑world ETF move very closely together. Correlation measures how often and how strongly assets move in the same direction; highly correlated holdings provide less diversification, especially in market sell‑offs when everything tends to drop at once. Here, the overlap between broad global and US exposures means adding both doesn’t dramatically smooth volatility, even though it increases the number of tickers. That’s not a flaw, but it limits the benefit of holding both funds. Being mindful of correlation can help when thinking about whether each ETF truly brings something distinct to the mix.
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 risk‑return chart, the current portfolio sits on the efficient frontier, meaning that given these five ETFs, the overall mix is already structured efficiently. The efficient frontier represents the best possible return for each level of risk using different weight combinations. The Sharpe ratio, which measures return per unit of risk, is good but not the highest possible with these holdings. An alternative mix could deliver a higher Sharpe or higher return at different risk levels, but would involve rebalancing between the existing ETFs, not adding new ones. That’s encouraging: the building blocks are sound, and only fine‑tuning weights would be needed for potential improvement.
The overall total expense ratio (TER) of roughly 0.23% is impressively low for a globally diversified equity basket. TER is the annual fee charged by the funds, taken directly from assets; in practice it’s like a small drag on performance each year. Keeping costs down is one of the few things investors can reliably control, and the difference of even half a percent compounds significantly over decades. Here, the use of broad, low‑cost index ETFs is a real strength and aligns well with best practices. Cost levels are not an area that needs much improvement given this current structure.
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