High growth US equity portfolio with strong tech tilt and concentrated three fund structure
Report created on May 14, 2026Risk profile
5/7
Diversification profile
3/5
Positions
-
VO Vanguard S&P 500 ETF
VOO - US9229083632 40.00% -
QQ Invesco NASDAQ 100 ETF
QQQM 40.00% -
SM Vaneck Vectors Semiconductor ETF
SMH 20.00%
This portfolio is built from three equity ETFs with a simple 40 / 40 / 20 split, all tracking US-focused stock indices. Two broad US index funds sit alongside a dedicated semiconductor ETF, creating a concentrated growth structure focused entirely on shares. With only three holdings, the setup is easy to understand and monitor. However, all observations here rest on roughly 2.9 years of history, which is a short period and has been unusually strong for US growth and technology names. That means any apparent pattern in returns or volatility may be more about this specific market phase than a stable, long-term characteristic of the portfolio.
Growth
Over the 2.9‑year window, $1,000 grew to about $2,313, a compound annual growth rate (CAGR) near 79.9%. CAGR is the “average speed” of growth per year, smoothing out ups and downs. This comfortably beat both a broad US market proxy and a global market proxy over the same period. The flip side is a notable maximum drawdown of about -22.8%, meaning there was a period where the portfolio was more than one‑fifth below a prior peak. With only a few years of data, mostly in a strong tech cycle, this outperformance and drawdown profile should be seen as a snapshot, not a reliable guide to decades of future behavior.
Projection
The Monte Carlo simulation projects many possible 15‑year paths by remixing past daily moves, then shows a range of potential outcomes. Here, the median path turns $1,000 into roughly $2,594, but the 5th to 95th percentile range is wide, from around $1,087 to $6,597. Monte Carlo is useful to visualize uncertainty, but it assumes the recent 2.9‑year pattern is representative, which is a big stretch for such a short and unusually strong tech‑driven period. So these numbers are better read as “this is how wild the ride could be” rather than a forecast of what is likely to happen.
Asset classes
- No data 60%
- Stocks 40%
The asset class breakdown shows about 40% clearly identified as stocks and 60% tagged as “No data,” which simply means the classification wasn’t available in the dataset. Because of that, it is not possible to draw a precise picture of how much is in equities versus any other asset class from this view alone. The key point is that all three ETFs are equity products, so overall behavior is driven by stock market risk rather than bonds or cash. With limited history and incomplete labels, it’s safer to treat this as a broadly equity‑heavy profile without leaning too much on the exact percentages shown.
Sectors
- Technology 13%
- Financials 5%
- Telecommunications 4%
- Consumer Discretionary 4%
- Health Care 4%
- Industrials 3%
- Consumer Staples 2%
- Energy 2%
- Utilities 1%
- Real Estate 1%
- Basic Materials 1%
Sector data highlights noticeable tilts toward technology and growth‑oriented areas, with technology the single largest identified slice, followed by smaller allocations across financials, telecom, consumer sectors, health care, and others. This pattern is consistent with broad US large‑cap and growth indices, but the added semiconductor ETF likely increases the effective tech exposure beyond what this breakdown alone shows. Sector weights matter because different parts of the economy react differently to interest rates, inflation, and economic cycles. A portfolio leaning into tech and related growth areas tends to move more sharply in both directions, especially during periods of changing rate expectations, which is important context given the short data window.
Regions
- North America 40%
The geographic breakdown shows the portfolio classified entirely as North America, reflecting the US‑focused nature of all three ETFs. This creates a clear home base in one economy and currency, which often simplifies tracking and news flow but also concentrates exposure in a single region. Compared with global benchmarks that spread across many countries, this is a deliberate geographic focus rather than a world mix. Over the last few years, US markets, especially growth and tech names, have done very well, which lifts historical figures here. With just under three years of data, it’s hard to say how this regional concentration would behave across a full market cycle.
Market capitalization
- Mega-cap 18%
- Large-cap 14%
- Mid-cap 7%
Market cap data shows an emphasis on the largest companies, with significant allocations to mega‑cap and large‑cap stocks and a smaller piece in mid‑caps. Market capitalization describes company size; mega‑caps are the biggest global players by value. Large established firms often have more stable business models and more analyst coverage, while still being sensitive to market swings. This pattern aligns with broad US index exposures, which are naturally dominated by big names. The risk/return trade‑off here is that large caps can still be volatile, especially if they sit in fast‑moving sectors, but tend to behave differently from small, more speculative companies. Again, the short window means recent mega‑cap strength heavily shapes these observations.
True holdings
-
NV NVIDIA Corporation 10.06%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vaneck Vectors Semiconductor ETF
- Vanguard S&P 500 ETF
-
AA Apple Inc 5.47%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vanguard S&P 500 ETF
-
MS Microsoft Corporation 4.10%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vanguard S&P 500 ETF
-
AV Broadcom Inc 4.01%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vaneck Vectors Semiconductor ETF
- Vanguard S&P 500 ETF
-
AM Amazon.com Inc 3.46%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vanguard S&P 500 ETF
-
GO Alphabet Inc Class A 2.77%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vanguard S&P 500 ETF
-
GO Alphabet Inc Class C 2.42%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vanguard S&P 500 ETF
-
ME Meta Platforms Inc. 2.16%
Part of fund(s):- Invesco NASDAQ 100 ETF
- Vanguard S&P 500 ETF
-
TS Taiwan Semiconductor Manufacturing 2.12%
Part of fund(s):- Vaneck Vectors Semiconductor ETF
-
TS Tesla Inc 2.09%
Part of fund(s):- Invesco NASDAQ 100 ETF
- LS 1x Tesla Tracker ETP Securities GBP
- Vanguard S&P 500 ETF
- Top 10 total 38.65%
Looking through the ETFs’ top holdings, a handful of major US tech and growth names stand out: NVIDIA, Apple, Microsoft, Broadcom, Amazon, Alphabet, Meta, Tesla, and Taiwan Semiconductor among them. Several of these appear across multiple ETFs, creating overlap that boosts their combined influence. For example, NVIDIA alone adds up to just over 10% of the portfolio within the covered portion, and other mega‑caps also cluster at meaningful weights. Because this analysis only uses top‑10 ETF holdings, the true overlap is likely understated. The key takeaway is that, beneath the three‑fund surface, a relatively small group of large tech‑linked companies drives a big share of the portfolio’s behavior.
Risk contribution
-
Invesco NASDAQ 100 ETF
Weight: 40.00% 40.1% -
Vanguard S&P 500 ETF
Weight: 40.00% 30.0% -
Vaneck Vectors Semiconductor ETF
Weight: 20.00% 30.0%
Risk contribution shows how much each holding adds to overall ups and downs, which can differ from simple weights. Here, the NASDAQ 100 ETF contributes about 40% of portfolio risk, closely matching its 40% weight. The S&P 500 ETF contributes roughly 30% of risk despite a 40% weight, while the 20% semiconductor ETF also contributes around 30% of total risk. That means the semiconductor slice is punching above its weight in driving volatility. This kind of concentration is common when one holding focuses on a more volatile niche. With just a few years of data, the exact numbers may shift over time, but the pattern of higher risk intensity in the semiconductor ETF is clear.
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 risk–return chart compares the current mix with an efficient frontier built from the same three ETFs. The efficient frontier shows the best expected return for each risk level using different weightings. Here, the current portfolio sits about 2.4 percentage points below the frontier at its risk level, with a Sharpe ratio of 2.0 versus 2.43 for the max‑Sharpe configuration. The Sharpe ratio measures return per unit of risk, after accounting for a given risk‑free rate. This suggests there are alternative weightings of the same funds that, based on the short 2.9‑year sample, would have delivered better risk‑adjusted outcomes, though there is no guarantee this relationship will hold in future markets.
Ongoing product costs
- Vanguard S&P 500 ETF 0.03%
- Weighted costs total (per year) 0.01%
The disclosed ongoing cost level looks impressively low, with a total expense ratio (TER) near 0.01% and a core ETF at 0.03%. TER is the annual fee taken by a fund as a percentage of your investment, similar to a small service charge. Low costs mean less drag on returns, especially when compounded over many years. In a highly equity‑driven portfolio, where volatility and market direction already play large roles, keeping fees minimal helps more of any future gains stay in the portfolio. With such low expenses, costs are a definite strength here and support the growth‑oriented profile rather than working against it.
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