Concentrated growth portfolio combining broad market exposure with a bold artificial intelligence focused tilt
Report created on May 3, 2024Risk profile
5/7
Diversification profile
3/5
Positions
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SP SPDR S&P 500 UCITS ETF USD Acc EUR
SPYL - IE000XZSV718 50.00% -
XA Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
XAIX - IE00BGV5VN51 50.00%
The structure is very straightforward: two stock ETFs split 50/50, one tracking a broad large‑cap index and the other focused on artificial intelligence and big data. This keeps the lineup simple but creates a strong thematic tilt layered on top of a core market holding. Simplicity can be powerful because it is easier to monitor and stick with through market ups and downs. The key question is whether that 50% thematic slice matches the intended risk level, since it drives a lot of the extra volatility and return potential. Treating the broad index as the core and the AI ETF as a “satellite” position is a useful mental model here.
Growth
From late 2023 to March 2026, $1,000 grew to about $1,530, which is a strong outcome. The portfolio’s compound annual growth rate (CAGR) of 19.24% is only slightly behind both the U.S. and global market benchmarks over this short period. However, the max drawdown of around -25% was noticeably deeper than the benchmarks’ roughly -17% to -19% drops. CAGR shows the “average speed” of growth, while max drawdown shows the worst peak‑to‑trough fall. The takeaway is that the portfolio has delivered near‑benchmark returns but with a bumpier ride, which is consistent with a growth‑oriented, tech‑tilted approach.
Asset classes
- Stocks 100%
All capital is in stocks, with no allocation to bonds, cash, or alternatives. A 100% equity stance is firmly in growth territory and is usually most suitable for long horizons and investors who can tolerate big swings. The benefit is higher long‑term return potential compared with mixed stock‑bond portfolios. The trade‑off is sharper drawdowns, especially during market stress when there is no cushion from defensive assets. This all‑equity approach aligns with the growth risk classification and the relatively high risk score, but it does rely heavily on the investor’s ability to stay invested during double‑digit declines. Time horizon and emotional tolerance are critical here.
Sectors
- Technology 52%
- Telecommunications 13%
- Consumer Discretionary 10%
- Financials 9%
- Health Care 5%
- Industrials 4%
- Consumer Staples 3%
- Energy 2%
- Utilities 1%
- Real Estate 1%
- Basic Materials 1%
Sector exposure is heavily tilted toward technology at 52%, with the rest spread across telecom, consumer, financials, health care, and other areas in smaller slices. This is a much stronger tech focus than most broad market benchmarks, driven largely by the AI and big data ETF. Tech‑heavy portfolios often shine during innovation and growth cycles but can suffer larger setbacks when interest rates rise or sentiment shifts away from high‑growth names. The positive side is clear participation in major technological trends; the flip side is that the portfolio’s fate is closely linked to one sector’s fortunes, which can amplify volatility relative to a more sector‑balanced approach.
Regions
- North America 86%
- Asia Developed 8%
- Asia Emerging 3%
- Europe Developed 2%
- Japan 1%
Geographically, the portfolio leans very strongly toward North America at 86%, with modest allocations to developed and emerging Asia, Europe, and Japan. This is more U.S.‑centric than a typical global equity benchmark, which usually has a lower U.S. share and more balanced exposure to other regions. A high North American weight has been rewarding in recent years given strong performance of U.S. large‑cap growth stocks. The trade‑off is less diversification across different economic and policy environments. If North American markets experience a period of underperformance, there is limited offset from other regions, so portfolio returns would likely track that regional cycle closely.
Market capitalization
- Mega-cap 51%
- Large-cap 36%
- Mid-cap 12%
- Small-cap 1%
By market capitalization, the portfolio is dominated by mega‑cap and large‑cap companies, with more than 85% combined, and only a small slice in mid and small caps. Larger companies tend to be more stable, better diversified businesses with deeper liquidity, which can reduce company‑specific risk compared to very small stocks. However, this also means less exposure to the potentially higher growth (and higher risk) that smaller companies sometimes offer. This large‑cap tilt aligns with mainstream benchmarks and helps keep individual stock risk manageable, but it does concentrate the portfolio in the biggest global winners and their valuations, which can be sensitive to shifts in investor sentiment.
True holdings
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NV NVIDIA Corporation 5.78%
Part of fund(s):- SPDR S&P 500 UCITS ETF USD Acc EUR
- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
AA Apple Inc 5.49%
Part of fund(s):- SPDR S&P 500 UCITS ETF USD Acc EUR
- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
00 Samsung Electronics Co Ltd 4.07%
Part of fund(s):- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
AM Amazon.com Inc 3.78%
Part of fund(s):- SPDR S&P 500 UCITS ETF USD Acc EUR
- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
GO Alphabet Inc Class A 3.78%
Part of fund(s):- SPDR S&P 500 UCITS ETF USD Acc EUR
- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
ME Meta Platforms Inc. 3.41%
Part of fund(s):- SPDR S&P 500 UCITS ETF USD Acc EUR
- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
MU Micron Technology Inc 2.63%
Part of fund(s):- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
00 SK Hynix Inc 2.51%
Part of fund(s):- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
-
MS Microsoft Corporation 2.47%
Part of fund(s):- SPDR S&P 500 UCITS ETF USD Acc EUR
-
BA Alibaba Group Holding Ltd 2.21%
Part of fund(s):- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
- Top 10 total 36.11%
Looking through the ETFs’ top holdings, the biggest underlying exposures are well‑known mega‑cap technology and internet names like NVIDIA, Apple, Amazon, Alphabet, Meta, and Microsoft, plus major Asian chip and platform companies. Several of these appear in both the broad index ETF and the AI ETF, so their true influence is larger than the simple top‑10 list might suggest. This kind of overlap creates hidden concentration: if a few big names stumble, the impact can be felt across both funds at once. It is not inherently bad, but it does mean portfolio fortunes are closely tied to a small group of dominant technology‑related companies.
Factors
Factor exposures are estimated using statistical models based on historical data and measure systematic (market-relative) tilts, not absolute portfolio characteristics. Results may vary depending on the analysis period, data availability, and currency of the underlying assets.
Factor exposure shows a very high tilt toward low volatility and high tilts toward size and momentum, with neutral value and yield and relatively low quality. Factors are like the underlying “character traits” of investments that research links to returns. A strong low‑volatility tilt usually means holdings that historically moved less than the market, which can help cushion downturns. The high momentum tilt means many positions have been recent strong performers, which can boost returns in trending markets but may hurt when trends reverse. Lower quality exposure suggests less focus on balance sheet strength or profitability metrics, which can matter in tougher economic conditions. Overall, this mix suits a trend‑following growth style with some volatility dampening.
Risk contribution
-
Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR
Weight: 50.00% 64.1% -
SPDR S&P 500 UCITS ETF USD Acc EUR
Weight: 50.00% 35.9%
Although both ETFs have equal 50% weights, the AI and big data ETF contributes about 64% of total portfolio risk, while the broad index contributes only 36%. Risk contribution measures how much each holding adds to overall ups and downs, and here the thematic ETF punches above its weight. This means most of the volatility and potential drawdowns come from the AI sleeve, even though it is only half the capital. If that’s intentional, it’s functioning as a high‑octane growth engine. If not, slightly trimming its weight or pairing it with more stabilizing holdings would be typical ways to bring risk contribution closer to the desired balance.
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.
On the risk‑return chart, the portfolio sits on or very near the efficient frontier, meaning that for its risk level, the mix of the two ETFs is already delivering close to the best achievable risk‑adjusted return using just these holdings. The Sharpe ratio of 0.94 is slightly below the optimal and minimum‑variance points, but the differences are small. The “optimal” versions would use somewhat lower risk and return with better Sharpe, mainly by dialing back volatility. Since the current setup is already efficient, any future tweaks are more about aligning the ride (risk level and drawdown comfort) with personal preferences than about fixing a structural inefficiency.
Ongoing product costs
- Xtrackers Artificial Intelligence &Big Data UCITS ETF 1C EUR 0.35%
- Weighted costs total (per year) 0.18%
Costs look impressively low, with a blended total expense ratio (TER) around 0.18%. TER is the annual fee charged by funds, and while fractions of a percent sound small, they compound over decades. Keeping fees under control leaves more of the returns in the investor’s pocket, which is especially important for high‑growth strategies where compounding is powerful. This fee level is competitive with many broad index solutions despite including a specialized AI ETF, which is a positive sign. Low costs also create more flexibility: if future returns are lower than the recent past, having minimal drag from fees becomes even more valuable for long‑term outcomes.
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