This portfolio has only about 1 years of historical data, based on the youngest asset in the portfolio. Some metrics, projections, and AI insights may be less reliable and should be interpreted with caution.

Globally diversified growth portfolio with strong tech momentum tilt and moderate alternative asset exposure

Report created on Mar 24, 2026

Risk profile Info

4/7
Balanced
Less risk More risk

Diversification profile Info

4/5
Broadly Diversified
Less diversification More diversification

Positions

The portfolio is built mainly around global stocks, with roughly half in a broad all‑world fund and the rest split between a non‑US fund, an AI‑focused equity fund, and smaller slices in bitcoin, silver, and gold. That mix gives a strong growth core plus a speculative layer via crypto and metals. Structurally, this lines up well with a “balanced‑growth” mindset: equities dominate, but there is some diversification into alternative assets that behave differently from stocks. The equity core is well spread via large ETFs, which is a big positive, while the dedicated AI and bitcoin pieces add punch and higher risk. The key question is whether that extra risk is intentional and fits the time horizon.

Growth Info

Over the last year, the portfolio turned €1,000 into about €1,167, giving a compound annual growth rate (CAGR) of 16.95%. CAGR is like your average speed on a long road trip, smoothing out the bumps. That return meaningfully beats both the US market proxy (7.37% CAGR) and the global market proxy (9.73% CAGR) over the same period. Max drawdown, the worst peak‑to‑trough fall, was around -15.8%, similar to the benchmarks, which means the higher return did not come with dramatically worse downside in this window. Still, one year is a short period; strong recent returns can be driven by hot themes like AI and may not persist in the same way.

Projection Info

The Monte Carlo projection simulates 1,000 different 10‑year paths based on the portfolio’s recent return and volatility, like rerunning history with many slightly different dice rolls. It shows a very wide range: from a small loss at the 5th percentile to quite extreme gains at the higher percentiles, with an average simulated annual return above 25%. Those numbers look exciting but are built on less than two years of data and a period where AI and crypto have done very well. That makes the simulation less reliable than a long‑history analysis. It’s safer to treat these results as a rough illustration of risk and variability rather than as a forecast.

Asset classes Info

  • Stocks
    83%
  • Crypto
    8%
  • Other
    5%

Asset‑class wise, about 83% is in stocks, 8% in crypto, and roughly 5% in other assets like silver and gold. This is clearly an equity‑led allocation, which is appropriate for pursuing long‑term growth but means meaningful ups and downs along the way. The 8% crypto slice introduces extra volatility and tail risk, while the precious metals can sometimes act as a partial hedge during equity stress or inflation scares. Compared with many “balanced” allocations that include bonds, this setup is more growth‑oriented and more sensitive to equity cycles. Anyone using a structure like this typically needs a longer horizon and comfort with sizeable short‑term swings.

Sectors Info

  • Technology
    28%
  • Financials
    13%
  • Industrials
    11%
  • Crypto
    8%
  • Consumer Discretionary
    7%
  • Telecommunications
    6%
  • Health Care
    6%
  • Consumer Staples
    4%
  • Basic Materials
    3%
  • Energy
    3%
  • Utilities
    2%
  • Real Estate
    1%

Sector exposure is led by technology at 28%, followed by financials, industrials, and a broad spread across consumer, communication, healthcare, and other areas. A 28% tech share is noticeably above what a broad global equity benchmark would usually hold, especially when you add AI‑themed exposure on top. That tilt has been very rewarding in recent years as high‑growth and chip‑related companies have surged. The flip side is higher sensitivity to interest‑rate moves, regulation, and sentiment shifts in growth stocks. This sector mix is still broadly diversified and matches many best‑practice guidelines, but the tech edge makes the ride potentially bumpier than a perfectly neutral global basket.

Regions Info

  • North America
    44%
  • Europe Developed
    17%
  • Japan
    7%
  • Asia Developed
    7%
  • Asia Emerging
    3%
  • Australasia
    2%
  • Africa/Middle East
    2%
  • Latin America
    1%

Geographically, around 44% is in North America, with the rest spread across developed Europe, Japan, other developed Asia, and smaller slices in emerging regions and other areas. That is actually more globally balanced than many portfolios that heavily overweight North America. It lines up quite closely with global index practice, which is a strong sign of healthy diversification. The exposure to both developed and emerging Asia adds some future growth potential, while Europe and Japan broaden the economic mix. The main implication is that outcomes will be driven by global conditions rather than being overly tied to a single country or region.

Market capitalization Info

  • Mega-cap
    41%
  • Large-cap
    27%
  • Mid-cap
    13%
  • Small-cap
    1%

By market size, the portfolio leans heavily into mega and large companies: about 41% in mega caps and 27% in big caps, with only modest mid and very little small‑cap exposure. Large firms tend to be more stable, diversified businesses with better access to financing, which can reduce idiosyncratic risk compared with a portfolio loaded with smaller stocks. However, strong dominance of mega caps also means performance is closely linked to how a relatively small list of global giants behaves. That large‑cap tilt has matched the recent decade’s trends well, but historically there have been stretches when smaller companies did better, so it shapes future return patterns.

True holdings Info

  • NVIDIA Corporation
    3.24%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
    • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
  • Apple Inc
    1.88%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
  • Broadcom Inc
    1.82%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
    • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
  • Alphabet Inc Class A
    1.63%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
    • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
  • Microsoft Corporation
    1.42%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
  • Amazon.com Inc
    0.98%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
  • SK Hynix Inc
    0.90%
    Part of fund(s):
    • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
  • Taiwan Semiconductor Manufacturing
    0.88%
    Part of fund(s):
    • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
  • Taiwan Semiconductor Manufacturing Co. Ltd.
    0.76%
    Part of fund(s):
    • Vanguard FTSE All-World UCITS ETF USD Accumulation
  • Lam Research Corp
    0.75%
    Part of fund(s):
    • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
  • Top 10 total 14.27%

Looking through the ETFs, the biggest underlying positions are familiar mega‑cap growth names such as NVIDIA, Apple, Broadcom, Alphabet, Microsoft, Amazon, and major chip makers. These appear across multiple funds, especially the global and AI strategies, which creates hidden concentration even with only top‑10 data. Overlap is likely understated because a large part of each ETF is beyond the top‑10 holdings. This means the portfolio is more exposed to a small group of tech and semiconductor leaders than the headline ETF list suggests. That overlap helps when these firms outperform but can hurt if sentiment turns against them all at once.

Factors Info

Value
Preference for undervalued stocks
No data
Data availability: 0%
Size
Exposure to smaller companies
Very low
Data availability: 66%
Momentum
Exposure to recently outperforming stocks
Neutral
Data availability: 100%
Quality
Preference for financially healthy companies
No data
Data availability: 0%
Yield
Preference for dividend-paying stocks
No data
Data availability: 0%
Low Volatility
Preference for stable, lower-risk stocks
No data
Data availability: 0%

The factor snapshot shows strong exposure to momentum and some tilt to size, based on the data available. Factor exposure is like checking which “traits” the portfolio leans into: momentum means owning what has been going up recently, and size here suggests some bias away from the very largest names toward somewhat smaller ones. A momentum‑heavy profile often does well in strong, trending markets but can get hit hard during sharp reversals when recent winners fall out of favor. Coverage is incomplete, so these readings are only a partial picture, yet they fit with the AI, tech, and crypto flavor. Anyone holding such tilts should be ready for performance to swing more than a plain index.

Risk contribution Info

  • Vanguard FTSE All-World UCITS ETF USD Accumulation
    Weight: 48.02%
    40.8%
  • iShares AI Innovation Active UCITS ETF USD (Acc) EUR
    Weight: 17.22%
    28.8%
  • iShares MSCI World ex-USA UCITS ETF USD (Acc)
    Weight: 17.68%
    12.8%
  • iShares Bitcoin ETP
    Weight: 8.05%
    10.4%
  • Invesco Physical Silver ETC
    Weight: 5.19%
    6.0%
  • Top 5 risk contribution 98.9%

Risk contribution shows how much each holding drives total portfolio volatility, which can differ from its weight. The global all‑world ETF is nearly half the portfolio but contributes about 41% of risk, so it’s actually slightly stabilizing relative to its size. The AI innovation ETF is 17% by weight yet adds nearly 29% of total risk, making it a major risk engine. Bitcoin and silver, although smaller, also punch above their weight in risk terms. The top three holdings together drive over 80% of total portfolio risk, which is typical for a concentrated core plus spicy satellites. Adjusting these weights is the main lever to dial overall risk up or down.

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 current portfolio sits below the efficient frontier, meaning that with the same set of holdings, a different weighting could deliver better expected return for the same or lower risk. The efficient frontier is like the best‑possible menu of risk/return combinations given your ingredients. Here, both the minimum‑variance mix and the highest‑Sharpe mix look more attractive than the current point, at least on paper. That suggests there’s room to tweak position sizes, especially in the higher‑risk components like AI and crypto, to raise the Sharpe ratio. Importantly, this is about reweighting what’s already owned, not adding new products.

Ongoing product costs Info

  • Vanguard FTSE All-World UCITS ETF USD Accumulation 0.19%
  • Weighted costs total (per year) 0.09%

The stated total expense ratio around 0.09% is impressively low, especially given the global diversification and access to specialized themes. TER is the annual fee charged by funds, and keeping it low leaves more of the return in your pocket each year. Even a difference of 0.5% per year compounds significantly over decades. Using broad, low‑cost ETFs for the core is right in line with best practices and supports solid long‑term outcomes. The more niche holdings, like active AI strategies or crypto products, can carry higher implicit costs or spreads, but they’re a smaller slice, so the overall cost profile remains very efficient.

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