This portfolio has only about 1.7 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.
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Several funds, one bet. Look through them and it is the same handful of tech companies wearing different tickers.
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A tech obsessed factor cocktail swinging for the fences with diversification as an afterthought

Report created on Aug 12, 2026

Risk profile Info

5/7
Growth
Less risk More risk

Diversification profile Info

2/5
Low Diversity
Less diversification More diversification
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Positions

This portfolio looks like someone tried to cram three different strategies into one blender and hit “liquefy.” There’s a broad S&P 500 core, then a chunky tilt to small-cap value, then dividend stocks, then a full 15% bet on semiconductors, plus momentum and a tiny AI lottery ticket. That’s not balance; that’s a committee fight. Structurally, it’s 35% “own the market” and 65% “I know better than the market,” which is confident bordering on cocky. With only about 1.7 years of data, it’s impossible to say this mashup “works” long term; so far you’ve mainly proved that concentrated growth bets look great when the wind’s at their back.

Growth Info

On paper, the short history makes this thing look like a genius move: $1,000 puffed up to $1,544, smashing both US and global markets with a 29.6% CAGR. That’s a road-trip-speed type number — fast, but only measured over a couple of exits on the highway. Max drawdown of -21.4% versus roughly -19% for the benchmarks tells the real story: when things wobble, this falls harder. Also, 90% of returns came from just 12 days. That’s a red flag that this ride is very dependent on a few turbo-charged bursts. Past data over 1.7 years is basically yesterday’s weather — too short to declare a climate pattern.

Projection Info

The Monte Carlo simulation is basically a fancy dice roll that replays versions of the last 1.7 years thousands of times to guess the next 15. It spits out a median of $2,738 from $1,000 with an average annual return of about 8%, which sounds almost civilized compared to recent fireworks. But remember, this is all built from a tiny and very hot data window. If the last year and a half was a party for semis and momentum, the model assumes the party never really stops, just occasionally slows down. That’s more optimistic storytelling than hard science — useful to frame “could” ranges, not to bank on.

Asset classes Info

  • Stocks
    100%

Asset class “diversification” here is basically a yes/no question, and the answer is yes to stocks and no to everything else. You’ve gone 100% equities, no bonds, no cash buffer, no diversifying assets — just pure market exposure with a spicy tilt. That’s like building a house entirely out of glass because the view is better. In good periods, it makes performance charts look heroic; in ugly periods, everything bleeds at once. With only 1.7 years of data, the pain hasn’t fully shown up yet, but structurally this setup is hardwired to feel every market mood swing in full HD.

Sectors Info

  • Technology
    44%
  • Financials
    11%
  • Industrials
    9%
  • Health Care
    8%
  • Consumer Discretionary
    7%
  • Telecommunications
    6%
  • Consumer Staples
    6%
  • Energy
    6%
  • Basic Materials
    2%
  • Utilities
    1%
  • Real Estate
    1%

Sector-wise, this is a tech worship portfolio in a thin disguise: 44% in technology, plus more tangential exposure via momentum and AI themes. Semiconductors alone are a 15% explicit bet, and that doesn’t count all the chips hiding in the S&P 500 and momentum ETF. Other sectors are basically background extras: financials, industrials, health care all get token roles so the portfolio can pretend it’s diversified. When a single sector is this dominant, performance becomes hostage to one narrative — right now chips and big tech saving the world. If that script flips, this allocation doesn’t have many understudies ready to step in.

Regions Info

  • North America
    95%
  • Asia Developed
    3%
  • Europe Developed
    1%
  • Asia Emerging
    1%

Geographically, this thing screams “America or else,” with 95% in North America and crumbs tossed to the rest of the planet. Europe and emerging Asia are basically a rounding error. That’s fine as long as US mega-tech and related names keep dominating headlines and earnings, which they have during this very short data window. But it’s not exactly a global portfolio; it’s more like a US tech-and-friends portfolio that incidentally owns a few foreigners through them. If the US cools off relative to other regions, this setup is positioned to learn what “home bias” means the hard way.

Market capitalization Info

  • Large-cap
    37%
  • Mega-cap
    31%
  • Mid-cap
    14%
  • Small-cap
    9%
  • Micro-cap
    8%

The market cap mix looks diversified on paper — mega, large, mid, small, even a noticeable 8% in micro-caps — but it’s more chaos than design. The core S&P 500 gives you mega and large stability, then you bolt on small-cap value and sprinkle in micro-cap drama. That combo means the portfolio has both big-ship inertia and speedboat volatility at the same time. With only 1.7 years of data, small and micro haven’t really had long enough to show how badly they can lag in the wrong cycle. For now, they mostly add extra shake without clear evidence of long-term payoff.

True holdings Info

  • NVIDIA Corporation
    7.16%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
    • Vanguard S&P 500 ETF
  • Micron Technology Inc
    3.31%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
    • Vanguard S&P 500 ETF
    • VistaShares Artificial Intelligence Supercycle ETF
  • Broadcom Inc
    3.06%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
    • Vanguard S&P 500 ETF
  • Apple Inc.
    2.31%
    Part of fund(s):
    • Vanguard S&P 500 ETF
  • Alphabet Inc Class A
    1.81%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • Vanguard S&P 500 ETF
  • Advanced Micro Devices Inc
    1.67%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
    • VistaShares Artificial Intelligence Supercycle ETF
  • Taiwan Semiconductor Manufacturing
    1.56%
    Part of fund(s):
    • VanEck Semiconductor ETF
    • VistaShares Artificial Intelligence Supercycle ETF
  • Microsoft Corporation
    1.51%
    Part of fund(s):
    • Vanguard S&P 500 ETF
  • Alphabet Inc Class C
    1.45%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • Vanguard S&P 500 ETF
  • Amazon.com Inc
    1.27%
    Part of fund(s):
    • Vanguard S&P 500 ETF
  • Top 10 total 25.09%

The look-through holdings are basically the “usual suspects” lineup: Nvidia, Broadcom, Apple, Microsoft, Amazon, Alphabet, TSMC, AMD — the entire Magnificent Tech Circus. Nvidia alone shows up as over 7% exposure through overlapping ETFs, and that’s with only top-10 ETF holdings captured, so real overlap is probably higher. This is the classic problem: different tickers, same underlying story. You think you’ve got six funds and a clever structure; you really have one big tech and semiconductor bet, sliced six ways. When the same names power multiple products, diversification becomes more marketing than math.

Factors Info

Value
Preference for undervalued stocks
Very high
Data availability: 30%
Size
Exposure to smaller companies
Very low
Data availability: 100%
Momentum
Exposure to recently outperforming stocks
High
Data availability: 15%
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
Neutral
Data availability: 95%

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.

The factor profile is where this portfolio quietly admits it has an identity crisis. Value exposure is at 85% — a very high tilt — while size is at a very low 10%, meaning it’s largely skewed to bigger companies despite that small-cap label showing in the holdings list. At the same time, momentum sits high at 75%, so you’ve got a weird mashup of “cheap” and “recent winners.” Factor exposure is basically the recipe list under the hood, and this recipe screams: chase strong trends, but pretend it’s disciplined value. Over 1.7 years of strong markets, that combo looks brilliant; in reversals, it can get whiplashy.

Risk contribution Info

  • Vanguard S&P 500 ETF
    Weight: 35.00%
    27.6%
  • VanEck Semiconductor ETF
    Weight: 15.00%
    27.2%
  • Invesco S&P 500® Momentum ETF
    Weight: 15.00%
    17.2%
  • Avantis® U.S. Small Cap Value ETF
    Weight: 15.00%
    12.4%
  • VistaShares Artificial Intelligence Supercycle ETF
    Weight: 5.00%
    9.4%
  • Top 5 risk contribution 93.8%

Risk contribution reveals which holdings are actually shaking the portfolio, and it’s not subtle here. The semiconductor ETF is 15% of the weight but contributes over 27% of the risk — almost double its fair share. The tiny 5% AI supercycle position hogs over 9% of the risk, also nearly 2x its weight. Meanwhile, the S&P 500, at 35% weight, contributes less risk than that ratio. Translation: the flashy, thematic pieces are driving the mood swings, not the big core. When the riskiest toys in the box are doing this much heavy lifting, portfolio stability depends heavily on them not face-planting.

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.

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The efficient frontier chart is quietly roasting this portfolio. At its current risk level, it sits about 7.7 percentage points below the best achievable return using the same ingredients. Sharpe ratio — the “how much return per unit of pain” stat — is 1.13, while the optimal mix from these same funds clocks in at 1.65. That’s a big gap for a portfolio supposedly trying to be smart and aggressive. Even the minimum-variance mix manages a Sharpe over 1.0 with much lower risk. In plain English, this is like driving a sports car in second gear: loud, bumpy, and still not using what you paid for efficiently.

Dividends Info

  • Avantis® U.S. Small Cap Value ETF 1.20%
  • Schwab U.S. Dividend Equity ETF 3.10%
  • VanEck Semiconductor ETF 0.20%
  • Invesco S&P 500® Momentum ETF 0.70%
  • Vanguard S&P 500 ETF 1.00%
  • Weighted yield (per year) 1.13%

For something that devotes 15% to a dividend ETF, the total yield limps in around 1.13%, which is… underwhelming. The dividend fund pulls its weight at just over 3%, but it’s surrounded by growthy, low-yield friends like semis, momentum, and AI that drag the portfolio’s income back down. This isn’t an income portfolio; it’s a growth engine with a decorative dividend badge slapped on the side. If the idea was to “get paid while you wait,” the actual cash flow here is more like “get tipped occasionally while you mostly rely on price swings to do the heavy lifting.”

Ongoing product costs Info

  • Avantis® U.S. Small Cap Value ETF 0.25%
  • Schwab U.S. Dividend Equity ETF 0.06%
  • VanEck Semiconductor ETF 0.35%
  • Invesco S&P 500® Momentum ETF 0.13%
  • Vanguard S&P 500 ETF 0.03%
  • Weighted costs total (per year) 0.13%

Costs are the one area where this portfolio doesn’t completely clown itself. A total expense ratio around 0.13% is actually impressively low for something this complex and theme-heavy. You somehow ended up with spicy tilts in semis, momentum, small-cap value, and AI while still paying index-like fees on average. That’s either good discipline or a very lucky ETF screener search. The dry punchline: you’ve built a pretty expensive-feeling roller coaster at budget pricing. If the results go sideways, it probably won’t be because of the fees — the problem will be the design, not the ticket cost.

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