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.

Concentrated thematic growth portfolio with strong recent gains and elevated risk across technology and energy themes

Report created on May 10, 2026

Risk profile Info

5/7
Growth
Less risk More risk

Diversification profile Info

3/5
Moderately Diversified
Less diversification More diversification

Positions

This portfolio is built almost entirely from equity funds, with a strong tilt toward thematic ETFs in generative AI, semiconductors, energy transition, uranium, smart grid infrastructure, and defense, plus a broad US index fund and a small gold position. The largest holding is the AI ETF at about a third of the portfolio, followed by the S&P 500 index fund at just over a fifth. This structure means the portfolio is driven mainly by a handful of growth-oriented themes rather than broad, evenly spread exposure. Because the youngest holdings only give about one year of data, any conclusions about long-term behaviour are tentative and mostly describe how this specific mix behaved in a short, strong market period.

Growth Info

Over the limited one-year window, $1,000 in this portfolio grew to about $1,779, implying a compound annual growth rate (CAGR) of roughly 83%. CAGR is like the average speed on a road trip, smoothing out bumps to show how fast the portfolio grew per year. This clearly beat both the US and global market benchmarks, which returned about 27% over the same period. Max drawdown, the biggest peak‑to‑trough drop, was around -12%, only modestly deeper than the benchmarks. However, such exceptional returns over a short period are often tied to specific themes being in favour. With just a year of data, it is risky to treat this pace as a “normal” expectation for the future.

Projection Info

The Monte Carlo projection uses that short historical record to simulate many possible 15‑year paths for a $1,000 investment. Monte Carlo is essentially a “what if” engine: it shuffles and replays past volatility and returns thousands of times to see a range of outcomes. Here, the median result is about $2,787, with a wide “likely” band from roughly $1,775 to $4,272 and a very broad possible range. The average simulated annual return is about 8.1%. Because all of this is based on roughly one year of unusually strong performance, the numbers may be overstating typical returns and understating risks. These projections are best seen as rough scenarios, not as probabilities you can rely on.

Asset classes Info

  • Stocks
    99%
  • No data
    1%

Asset‑class exposure is extremely simple: about 99% in stocks and 1% in “no data,” with no meaningful allocation to bonds or cash in the analysis. Stocks historically offer higher potential growth than bonds but also come with larger and faster price swings. A nearly all‑equity portfolio like this tends to be more sensitive to market cycles and headlines, which can be rewarding in strong markets but uncomfortable in sharp downturns. Compared with broad multi‑asset benchmarks that include bonds and sometimes real assets, this mix leans clearly toward growth and volatility. The small non‑equity component is too minor to materially change the risk/return profile at the portfolio level.

Sectors Info

  • Technology
    45%
  • Industrials
    17%
  • Telecommunications
    9%
  • Energy
    6%
  • Basic Materials
    6%
  • Utilities
    5%
  • Consumer Discretionary
    3%
  • Financials
    3%
  • Consumer Discretionary
    2%
  • Health Care
    2%
  • Consumer Staples
    1%

Sector exposure is heavily tilted toward technology, at around 45%, with meaningful stakes in industrials and telecom, and smaller slices in energy, basic materials, utilities, and consumer‑related areas. This reflects the focus on AI, semiconductors, smart grids, defense, and energy transition. Compared with diversified global benchmarks, which spread more evenly across financials, healthcare, and consumer sectors, this portfolio is more concentrated in cyclical, innovation‑driven areas. Tech‑heavy and theme‑focused sector mixes often experience bigger swings when interest rates change or when expectations about future growth shift. The advantage is strong participation when these themes are in favour; the trade‑off is that sector‑specific slowdowns could hit the portfolio harder than a broadly balanced mix.

Regions Info

  • North America
    70%
  • Europe Developed
    9%
  • Asia Developed
    8%
  • Asia Emerging
    6%
  • Australasia
    3%
  • Japan
    2%

Geographically, the portfolio leans strongly toward North America at about 70%, with smaller allocations to developed Europe, developed and emerging Asia, Australasia, and Japan. This creates a clear home‑region tilt relative to global indexes, which typically have a lower North American share and more weight in the rest of the world. Geographic spread matters because different regions can go through economic and market cycles at different times. Here, diversification across other regions is present but secondary; most of the portfolio’s fortunes are tied to North American markets and currency. Over short periods this has helped, but with only a year of history it is hard to judge how this regional tilt might behave across full economic cycles.

Market capitalization Info

  • Mega-cap
    42%
  • Large-cap
    32%
  • Mid-cap
    16%
  • Small-cap
    6%
  • Micro-cap
    1%

The market‑cap breakdown shows a strong emphasis on very large companies: about 42% in mega‑caps and 32% in large‑caps, with the remainder in mid‑, small‑, and micro‑caps. Market capitalization describes company size, and bigger firms usually have more diversified businesses and more stable earnings than very small firms. This profile is somewhat similar to broad equity benchmarks that are dominated by large names, but the added presence of themed ETFs also introduces smaller, more specialized companies. The result is a blend of stability from the mega‑caps and more pronounced swings from the smaller holdings. In stressed markets, smaller caps can move more sharply, which can amplify volatility relative to a purely large‑cap index.

True holdings Info

  • NVIDIA Corporation
    4.31%
    Part of fund(s):
    • First Trust NASDAQ® Clean Edge® Smart Grid Infrastructure Index Fund
    • Roundhill Generative AI & Technology ETF
    • VanEck Semiconductor ETF
  • Alphabet Inc Class A
    2.34%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
  • Advanced Micro Devices Inc
    2.25%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
    • VanEck Semiconductor ETF
  • Broadcom Inc
    2.16%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
    • VanEck Semiconductor ETF
  • Micron Technology Inc
    2.15%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
    • VanEck Semiconductor ETF
  • SK Hynix Inc
    1.63%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
  • Amazon.com Inc
    1.41%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
  • Samsung Electronics Co Ltd
    1.27%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
  • Microsoft Corporation
    1.19%
    Part of fund(s):
    • Roundhill Generative AI & Technology ETF
  • Taiwan Semiconductor Manufacturing
    1.14%
    Part of fund(s):
    • VanEck Semiconductor ETF
  • Top 10 total 19.84%

Looking through the ETFs’ disclosed top‑10 holdings, several big technology and semiconductor companies appear repeatedly, including NVIDIA, Alphabet, AMD, Broadcom, and others. For example, NVIDIA alone makes up over 4% of the portfolio via multiple funds. This kind of overlap means that the portfolio is more concentrated in a handful of large growth names than the fund list might suggest at first glance. Because only ETF top‑10 holdings are used, true overlap is likely higher than reported. Hidden concentration can be a double‑edged sword: it boosts participation when those companies do well but also ties overall portfolio performance more tightly to a few influential stocks, especially in short, theme‑driven rallies.

Factors Info

Value
Preference for undervalued stocks
No data
Data availability: 0%
Size
Exposure to smaller companies
Very low
Data availability: 78%
Momentum
Exposure to recently outperforming stocks
No data
Data availability: 0%
Quality
Preference for financially healthy companies
No data
Data availability: 0%
Yield
Preference for dividend-paying stocks
Neutral
Data availability: 100%
Low Volatility
Preference for stable, lower-risk stocks
Low
Data availability: 36%

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 data is limited, but there are two notable tilts: a very low size factor score (12%) and low exposure to low volatility (26%), with yield around neutral. Factors are like investing “ingredients” that describe why holdings behave the way they do. A very low size exposure usually means a bias toward larger companies relative to a market‑neutral stance. Low low‑volatility exposure suggests the portfolio leans away from steadier stocks and more towards names that can swing more day to day. Combined with strong thematic positions, this can amplify both upside and downside moves. With only a year of factor data, it is difficult to say how persistent these tilts will be over longer horizons.

Risk contribution Info

  • Roundhill Generative AI & Technology ETF
    Weight: 34.09%
    42.8%
  • VanEck Semiconductor ETF
    Weight: 11.24%
    13.2%
  • Sprott Energy Transition Materials ETF
    Weight: 7.51%
    10.6%
  • VanEck Uranium+Nuclear Energy ETF
    Weight: 6.96%
    10.2%
  • Fidelity 500 Index Fund
    Weight: 21.27%
    10.0%
  • Top 5 risk contribution 86.8%

Risk contribution shows how much each holding drives the portfolio’s ups and downs, which can differ from its simple weight. Here, the AI ETF is 34% of the portfolio but accounts for almost 43% of the total risk, and the top three holdings together generate about two‑thirds of the overall volatility. In contrast, the broad S&P 500 index fund carries over 21% weight but only about 10% of risk, acting as a relative stabilizer. This pattern is typical when concentrated theme funds sit next to a diversified core fund. It means that day‑to‑day and month‑to‑month results are particularly sensitive to a few thematic positions, especially during quick market swings or sentiment shifts.

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 analysis shows the current portfolio sitting below the frontier at its risk level, with a Sharpe ratio of 2.63. The Sharpe ratio measures return per unit of risk, using the risk‑free rate as a baseline. The “optimal” portfolio built from the same holdings has a higher Sharpe (3.13) by taking on more risk but also a much higher expected return, while the minimum‑variance mix offers lower risk and a lower Sharpe. Being about 6 percentage points below the frontier suggests that, historically, a different combination of these same funds might have delivered a smoother trade‑off between risk and return. Because this optimisation is based on about a year of data, its guidance is informative but not definitive.

Dividends Info

  • Roundhill Generative AI & Technology ETF 2.00%
  • Fidelity 500 Index Fund 1.10%
  • First Trust NASDAQ® Clean Edge® Smart Grid Infrastructure Index Fund 0.80%
  • VanEck Uranium+Nuclear Energy ETF 2.20%
  • Sprott Energy Transition Materials ETF 1.20%
  • VanEck Semiconductor ETF 0.20%
  • iShares Defense Industrials Active ETF 0.20%
  • Weighted yield (per year) 1.28%

The portfolio’s total dividend yield is around 1.28%, with individual funds mostly paying between 0.2% and 2.2%. Dividend yield measures yearly cash payouts as a percentage of price. Here, income is a secondary feature: the main return driver has been price appreciation, especially in the AI, semiconductor, and energy‑related themes. Over long periods, reinvested dividends can contribute meaningfully to total return, but in a high‑growth, thematic mix like this, they are more of a modest bonus. The relatively low overall yield is consistent with portfolios tilted toward growth and innovation rather than mature, high‑payout businesses. With only a year of yield history, payouts could still evolve as the underlying companies change policies.

Ongoing product costs Info

  • Roundhill Generative AI & Technology ETF 0.75%
  • Fidelity 500 Index Fund 0.02%
  • First Trust NASDAQ® Clean Edge® Smart Grid Infrastructure Index Fund 0.57%
  • iShares® Gold Trust Micro 0.09%
  • VanEck Uranium+Nuclear Energy ETF 0.61%
  • Sprott Energy Transition Materials ETF 0.65%
  • VanEck Semiconductor ETF 0.35%
  • Weighted costs total (per year) 0.45%

The weighted average ongoing fee (TER) is about 0.45% per year. TER is like a subscription fee charged by funds to cover management and operations, taken out of returns before you see them. Costs here sit between ultra‑low‑cost index investing and more expensive active or niche strategies. The broad market index fund is very cheap at 0.02%, which helps offset higher‑fee thematic ETFs in AI, uranium, and energy transition, many of which charge between 0.35% and 0.75%. For a concentrated thematic portfolio, this overall fee level is fairly reasonable and not extreme. Over many years, though, even moderate differences in TER can compound, so understanding what you are paying for themes versus broad exposure is useful.

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