Two fund world tour with a secret small cap gambling habit hiding under the hood
Report created on Jun 25, 2026Risk profile
4/7
Diversification profile
3/5
Positions
-
WE Amundi Prime All Country World UCITS ETF Acc EUR
WEBN - IE0003XJA0J9 80.00% -
AV Avantis Global Small Cap Value UCITS ETF USD Acc EUR
AVWS - IE0003R87OG3 20.00%
Structurally this portfolio is the IKEA flat-pack of investing: one big “own the world” fund at 80% and a spicy 20% tilt in small cap value. It’s mechanically simple but not as boring as it looks. The problem is that almost everything ultimately hangs off global equities, so when stocks sneeze the whole portfolio catches pneumonia. With only 1.7 years of data, any neat narrative about how this mix “behaves” is mostly fan fiction. In reality, this is a plain global core with a very opinionated side bet that can both juice and wreck performance depending on which short window you stare at.
Growth
In this tiny 1.7‑year snapshot, the portfolio turned €1,000 into €1,336 and politely outpaced both the US and global markets. The CAGR of 18.32% looks heroic, but that’s like judging a marathon based on the first water station. Max drawdown was about -21.6%, so it can still punch you in the face when markets wobble. Ten days made up 90% of returns, which means the result is basically a handful of lucky (or unlucky) coin flips. Past data over such a short stretch is yesterday’s weather, not a climate model, so any “pattern” here is extremely provisional.
Projection
The Monte Carlo simulation is doing its best tarot-card impression with only 1.7 years of history to work with. It spits out a median €2,734 after 15 years from €1,000, with a very wide “maybe” range from €925 to €7,971. Monte Carlo just reruns different what-if paths using past volatility and returns, which here are based on a very young track record. So the portfolio looks like it has a 73% chance of ending positive, but that’s more “educated guess” than prophecy. Change the starting period and those pretty ranges could shift a lot.
Asset classes
- Stocks 100%
Asset class “diversification” here is basically a one-word answer: stocks, 100%. No bonds, no cash buffer, no anything-that-isn’t-equity. That’s fine if the goal is to surf the equity roller coaster, but calling this “balanced” is generous. It’s balanced in the same way a unicycle is a “balanced vehicle” — technically true, practically wobbly. With only equities, any market-wide shock hits everything at once, and there’s nowhere inside the portfolio that naturally dampens the blows. Over 1.7 years that looks fun; over a real cycle it just means living with full equity mood swings.
Sectors
- Technology 27%
- Financials 18%
- Industrials 11%
- Consumer Discretionary 11%
- Telecommunications 7%
- Health Care 7%
- Energy 6%
- Consumer Staples 5%
- Basic Materials 4%
- Utilities 2%
- Real Estate 1%
Sector-wise, this is a tech-forward world index with training wheels. Technology sits at 27%, clearly in the driver’s seat, while financials, industrials, and consumer discretionary trail behind. It’s basically a diversified portfolio that still quietly believes the future is built in code and semiconductors. That’s not unusual today, but it does mean a big part of the fate here rests on one broad theme: “growthy stuff keeps working.” A short 1.7-year window where mega-tech did well flatters this mix, but if leadership rotates hard, that nice performance story can age quickly.
Regions
- North America 66%
- Europe Developed 13%
- Japan 7%
- Asia Developed 6%
- Asia Emerging 4%
- Australasia 2%
- Africa/Middle East 1%
- Latin America 1%
Geographically, the portfolio screams “America first, everyone else gets the crumbs.” Roughly two-thirds sits in North America, with Europe, Japan, and the rest of the world awkwardly sharing the leftovers. This mirrors global market cap, so it’s not weird — just heavily dependent on one economic region behaving itself. The rest-of-world exposure is more side character than co-star. Over 1.7 years this US tilt has been a tailwind; in periods when other regions shine or the US stumbles, this setup can look very one-dimensional despite the impressive-sounding “All Country World” label.
Market capitalization
- Mega-cap 39%
- Large-cap 28%
- Mid-cap 16%
- Small-cap 10%
- Micro-cap 7%
The market cap mix is where things get more interesting. You’ve got 39% in mega-caps and 28% in large-caps doing the steady heavy lifting, but then 33% combined in mid, small, and even micro-caps adds a distinct wobble. That 20% small-cap value fund is clearly dragging the portfolio down-cap. This is like owning a stable blue-chip core and then sneaking in a bar-fight-prone cousin. Over 1.7 years, smaller names might look exciting or irrelevant depending on timing, but structurally they guarantee more noise and sharper moves relative to a pure mega/large-cap index.
True holdings
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NV NVIDIA Corporation 3.85%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
AA Apple Inc 3.49%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
MS Microsoft Corporation 2.58%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
AM Amazon.com Inc 2.03%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
GO Alphabet Inc Class A 1.73%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
AV Broadcom Inc 1.62%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
GO Alphabet Inc Class C 1.49%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
23 Taiwan Semiconductor Manufacturing Co. Ltd. 1.41%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
-
TS Tesla Inc 1.14%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
- LS 1x Tesla Tracker ETP Securities GBP
-
ME Meta Platforms Inc. 1.08%
Part of fund(s):- Amundi Prime All Country World UCITS ETF Acc EUR
- Top 10 total 20.40%
Look-through holdings reveal the usual suspects running the show: NVIDIA, Apple, Microsoft, Amazon, Alphabet, and friends. Even with only top-10 ETF data covering ~22% of the portfolio, it’s obvious the same giants are being worshipped repeatedly. That 3.85% in NVIDIA and 3.49% in Apple are poster children for hidden concentration inside “broad” funds. Overlap is likely higher than reported because we only see the tip of the iceberg. Short-term, that’s been a gift; longer term, it just means a lot of supposedly diversified money is betting on very few mega-stories.
Risk contribution
-
Amundi Prime All Country World UCITS ETF Acc EUR
Weight: 80.00% 79.0% -
Avantis Global Small Cap Value UCITS ETF USD Acc EUR
Weight: 20.00% 21.0%
Risk contribution is refreshingly straightforward: the 80% core fund does about 79% of the risk heavy lifting, and the 20% small-cap value slice contributes roughly 21%. So the side bet is pulling slightly more than its weight in volatility terms — not shocking for smaller, value-tilted stocks. Risk contribution is basically asking, “Who’s actually shaking the portfolio?” Here, nothing absurd stands out, which is almost disappointing. It’s just a textbook case where the “spicy” sleeve is proportionally responsible for extra bumpiness, without yet proving it deserves its drama in only 1.7 years of data.
Risk vs. return
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 stats are mildly annoying in how competent they look. The current portfolio sits basically on the frontier, with a Sharpe ratio of 0.95 versus 1.16 for the optimal mix using the same ingredients. The minimum variance version barely changes risk and still looks strong. In plain English, given these two funds and this short 1.7-year history, the weights are already pretty efficient. That’s the good news. The less sexy truth: these “optimal” curves lean on a very young dataset, so their precision is more cosplay than science. Still, for now, the math grudgingly approves.
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