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.
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Highly focused semiconductor and silver portfolio with extreme yield and aggressive growth profile

Report created on Apr 7, 2026

Risk profile Info

6/7
Aggressive
Less risk More risk

Diversification profile Info

2/5
Low Diversity
Less diversification More diversification
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Positions

This portfolio is extremely concentrated, with roughly four holdings making up about 80% of the total weight. It’s all in stocks, with big tilts toward semiconductors, a single precious metal position, and broad US equity funds as supporting players. That structure makes the overall mix aggressive and very theme-driven rather than broadly diversified. Because this is assumed buy-and-hold with no rebalancing, strong performers can grow into even bigger chunks over time, amplifying both gains and potential losses. With only about a year of data, it’s hard to say how this setup behaves across full market cycles, so any conclusions about long-term resilience should be taken as tentative rather than definitive.

Growth Info

Over the last year, $1,000 hypothetically grew to about $1,937, giving a huge 94% compound annual growth rate (CAGR). CAGR is like your average speed on a road trip, smoothing out bumps along the way. This crushed both the US and global market benchmarks, which were in the mid‑20% range, but it came with a nearly ‑20% max drawdown, roughly twice benchmark downside. Only about 10 days made up 90% of returns, highlighting how dependent results were on a handful of big moves. With just one year of history, this outperformance could easily be a lucky streak tied to current themes rather than a repeatable pattern.

Projection Info

The Monte Carlo projection uses the short historical record to simulate thousands of possible 15‑year paths and estimate likely outcomes. Think of it as running “what if” market dice rolls over and over, based on past volatility and returns. The median outcome grows $1,000 to about $2,719, with a wide possible range from roughly flat to more than eight‑times the starting value. The average annualized result across simulations is about 8.1%, but this rests on less than a year of data, which is a fragile foundation. Early performance—especially a very strong first year—can skew these simulations, so they should be seen as rough scenario ranges, not a forecast to rely on.

Asset classes Info

  • Stocks
    100%

Every dollar here is in stocks or stock-like funds, with no bonds, cash, or other defensive assets in the mix. Asset classes are broad buckets like stocks, bonds, and real estate that tend to react differently to economic news. A pure‑equity setup usually means higher long‑term growth potential but also deeper drawdowns in bear markets because there’s no built‑in shock absorber. Compared with more balanced portfolios that blend stocks with steadier assets, this structure is intentionally aggressive and will likely feel more like a rollercoaster when markets turn. With only about a year of history, it hasn’t yet been “stress‑tested” through a major recession or extended downturn, so real‑world downside could be harsher than anything seen so far.

Sectors Info

  • Technology
    57%
  • Financials
    22%
  • Telecommunications
    9%
  • Health Care
    3%
  • Industrials
    2%
  • Consumer Discretionary
    2%
  • Consumer Staples
    2%
  • Consumer Discretionary
    1%
  • Energy
    1%
  • Utilities
    1%
  • Basic Materials
    1%

Sector-wise, the portfolio is dominated by technology-related exposure, with over half in that bucket and the rest spread thinly across areas like financials, telecom, health care, and others. Sector allocation just means how much is tied to different parts of the economy. Being this tech- and semiconductor-heavy can work brilliantly when innovation and risk appetite are in favor, which recent performance shows, but it often means sharper hits when interest rates rise, regulation bites, or the cycle shifts away from growth. This concentration is a clear double‑edged sword: it’s a focused bet that can outperform broad benchmarks in good times, yet it also makes downturns in that theme much more painful than in a diversified sector mix.

Regions Info

  • North America
    92%
  • Europe Developed
    4%
  • Asia Developed
    3%
  • Asia Emerging
    1%

Geographically, about 92% of exposure is in North America, with only small slices in developed Europe, developed Asia, and emerging Asia. Geography affects currency risk, political risk, and how tied you are to one economy. This setup closely tracks a US‑centric view of the world, which is common for American investors and has been rewarded in the last decade as US markets have led global returns. Still, it means the portfolio’s fate is heavily linked to US economic policy, regulation, and the dollar. Relative to global benchmarks that spread more across regions, this is clearly home‑biased. With limited historical data, it’s hard to judge how this regional tilt would behave if US leadership temporarily stalled while other areas outperformed.

Market capitalization Info

  • Large-cap
    41%
  • Mega-cap
    36%
  • Mid-cap
    19%
  • Small-cap
    2%
  • Micro-cap
    1%

The portfolio leans toward mega‑ and large‑cap stocks, which make up over three quarters of the allocation, with the rest in mid‑, small‑, and tiny micro‑cap names. Market capitalization is just company size by stock market value. Bigger firms tend to be more stable and widely followed, while smaller ones can be more volatile but sometimes offer higher growth potential. This mix tilts toward the “safer” end of equities in terms of size, but the sectors and themes (like semiconductors and a small individual chip stock) still push overall risk quite high. In choppy markets, mid‑ and small‑caps in niche areas can swing dramatically, and with only a year of history we haven’t seen how these size exposures might react in a prolonged downturn.

True holdings Info

  • Sprott Physical Silver
    19.00%
  • Netflix Inc
    5.30%
  • Navitas Semiconductor Corp
    5.30%
  • NVIDIA Corporation
    2.53%
    Part of fund(s):
    • Invesco NASDAQ 100 ETF
    • Schwab U.S. Large-Cap Growth ETF
    • YieldMax Semiconductor Portfolio Option Income ETF
  • Broadcom Inc
    1.68%
    Part of fund(s):
    • Invesco NASDAQ 100 ETF
    • Schwab U.S. Large-Cap Growth ETF
    • YieldMax Semiconductor Portfolio Option Income ETF
  • Lam Research Corp
    1.11%
    Part of fund(s):
    • YieldMax Semiconductor Portfolio Option Income ETF
  • ASML Holding N.V.
    0.97%
    Part of fund(s):
    • Vanguard Total International Stock Index Fund ETF Shares
    • YieldMax Semiconductor Portfolio Option Income ETF
  • Marvell Technology Group Ltd
    0.97%
    Part of fund(s):
    • YieldMax Semiconductor Portfolio Option Income ETF
  • Apple Inc
    0.89%
    Part of fund(s):
    • Invesco NASDAQ 100 ETF
    • Schwab U.S. Large-Cap Growth ETF
  • Arm Holdings plc American Depositary Shares
    0.89%
    Part of fund(s):
    • YieldMax Semiconductor Portfolio Option Income ETF
  • Top 10 total 38.64%

Looking through the funds, a lot of exposure clusters around a handful of semiconductor names like NVIDIA, Broadcom, and Lam Research, plus direct positions in Navitas and high overlap between the semiconductor mutual fund and the semiconductor option-income ETF. “Look-through” just means we’re peeking under the hood of the funds’ top holdings to see what you really own. Because we only see ETF top‑10 holdings, actual overlap is almost certainly higher than reported. Hidden overlap matters: if the same chip names appear in multiple funds and a single stock, one bad earnings season in that niche could hit several positions at once, making the portfolio swing harder than the headline position count suggests.

Factors Info

Value
Preference for undervalued stocks
Neutral
Data availability: 40%
Size
Exposure to smaller companies
Very low
Data availability: 59%
Momentum
Exposure to recently outperforming stocks
High
Data availability: 40%
Quality
Preference for financially healthy companies
Neutral
Data availability: 11%
Yield
Preference for dividend-paying stocks
Low
Data availability: 70%
Low Volatility
Preference for stable, lower-risk stocks
Neutral
Data availability: 40%

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 how much the portfolio leans into traits like value, size, or momentum that research has linked to returns. Here, size exposure is “very low,” meaning a strong tilt toward larger companies instead of smaller ones, and momentum is “high,” suggesting a bias toward stocks that have already been recent winners. High momentum can turbocharge gains when trends persist, but it can hurt more in sharp reversals if hot names fall out of favor. The very low size factor fit with the heavy large‑ and mega‑cap exposure, which tends to be a bit steadier than small caps, though sector choice overwhelms that here. Given the very short track record, these factor tilts might not be fully stable and could shift as markets change.

Risk contribution Info

  • Fidelity Select Semiconductors Portfolio
    Weight: 22.00%
    24.8%
  • Navitas Semiconductor Corp
    Weight: 5.30%
    20.5%
  • Sprott Physical Silver
    Weight: 19.00%
    20.0%
  • YieldMax Semiconductor Portfolio Option Income ETF
    Weight: 19.00%
    17.6%
  • Schwab S&P 500 Index Fund
    Weight: 19.00%
    9.1%
  • Top 5 risk contribution 92.1%

Risk contribution looks at how much each position drives overall volatility, not just how big it is in dollars. A standout here is Navitas Semiconductor: at about 5.3% weight, it contributes over 20% of total portfolio risk, nearly four times its size share. That’s like a small, very loud instrument dominating an orchestra. The semiconductor mutual fund and silver position each contribute roughly in line with their weights, while the broad S&P 500 fund pulls less than its share of risk, acting as a stabilizer. The top three holdings account for about 65% of total risk, which is high concentration. Tuning position sizes over time is one way to bring risk more in line with how much conviction there is in each idea.

Redundant positions Info

  • YieldMax Semiconductor Portfolio Option Income ETF
    Fidelity Select Semiconductors Portfolio
    High correlation
  • Invesco NASDAQ 100 ETF
    Schwab U.S. Large-Cap Growth ETF
    Schwab S&P 500 Index Fund
    High correlation

Correlation describes how often two assets move together: a value of 1 means they move almost identically, 0 means they’re independent, and negative means they often go in opposite directions. Several pairs here are highly correlated, especially the two semiconductor‑focused funds and the trio of broad US equity ETFs and funds. When assets are this tightly linked, diversification benefits shrink, particularly in sell‑offs when everything drops together. On the plus side, this strong alignment with core US equity markets can make behavior somewhat more predictable versus random niche bets. But because the underlying theme and geography are already concentrated, high correlations reinforce that clustering instead of smoothing out the ride. This is another reason swings may feel more intense than the number of line items suggests.

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.

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The efficient frontier chart compares different mixes of the same holdings to find the best trade‑off between risk and return. The current portfolio has a Sharpe ratio of 2.32, while the “optimal” mix hits 2.6 with higher expected return and somewhat higher risk, and the minimum‑risk version lands at lower volatility but also lower return. The Sharpe ratio measures return per unit of risk, like miles per gallon for investing. Today’s allocation sits about 3.2 percentage points below the efficient frontier at its risk level, meaning the same ingredients could, in theory, be combined more efficiently. Given this is built on less than a year of data, these optimizations are more like rough guidance than a precise roadmap.

Dividends Info

  • Fidelity Select Semiconductors Portfolio 7.10%
  • Invesco NASDAQ 100 ETF 0.50%
  • Schwab U.S. Large-Cap Growth ETF 0.40%
  • Schwab S&P 500 Index Fund 1.20%
  • Vanguard Total International Stock Index Fund ETF Shares 3.00%
  • YieldMax Semiconductor Portfolio Option Income ETF 38.70%
  • Weighted yield (per year) 9.20%

The portfolio shows an eye‑popping total yield around 9.2%, driven mainly by the semiconductor option‑income ETF with a stated yield north of 38%. Dividend yield is the annual cash payout as a percentage of price; it can be attractive for income but also sometimes signals higher risk. Option‑income strategies often convert potential future upside into current cash flows, which can mean missing out if the sector soars. The rest of the holdings generally have modest or low yields, consistent with growth and tech‑oriented names. With only a year of data, it’s crucial not to assume this unusually high headline yield is sustainable over the long run; distributions from option strategies can fluctuate a lot with volatility and market direction.

Ongoing product costs Info

  • Fidelity Select Semiconductors Portfolio 0.62%
  • Invesco NASDAQ 100 ETF 0.15%
  • Schwab U.S. Large-Cap Growth ETF 0.04%
  • Schwab S&P 500 Index Fund 0.02%
  • Vanguard Total International Stock Index Fund ETF Shares 0.05%
  • Weighted costs total (per year) 0.15%

Average ongoing fund costs (TER, or total expense ratio) land around 0.15%, which is impressively low given the mix of specialized and broad funds. TER is the annual fee, expressed as a percentage of assets, that quietly comes out of performance each year. Keeping this number low is one of the few things investors can control, and it compounds nicely over decades. The semiconductor mutual fund is notably more expensive than the index trackers, but that’s typical for sector funds. Overall, the cost structure here is a real strength: for such an aggressive and specialized approach, having low fees means more of any future returns—good or bad—stay in the investor’s pocket rather than going to fund providers.

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