High octane growth focused portfolio with concentrated risk and strong recent short term gains
Report created on Apr 1, 2026Risk profile
7/7
Diversification profile
4/5
Positions
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VO Vanguard S&P 500 ETF
VOO - US9229083632 35.93% -
SP Fidelity® Government Money Market Fund
SPAXX - US31617H1023 12.83% -
VX Vanguard Total International Stock Index Fund ETF Shares
VXUS - US9219097683 12.34% -
ET Grayscale Ethereum Mini Trust (ETH)
ETH 10.99% -
IN Intel Corporation
INTC - US4581401001 5.80% -
HO Robinhood Markets Inc
HOOD - US7707001027 4.27% -
AM Amazon.com Inc
AMZN - US0231351067 4.21% -
GO Alphabet Inc Class A
GOOGL - US02079K3059 3.93% -
IB Immunitybio Inc
IBRX - US45256X1037 3.02% -
MS Microsoft Corporation
MSFT - US5949181045 2.67% -
SL iShares Silver Trust
SLV - US46428Q1094 2.58% -
SI Sidus Space Inc
SIDU - US8261651025 1.07% -
NV NVIDIA Corporation
NVDA - US67066G1040 0.36%
This portfolio mixes broad low cost index funds with a handful of punchy individual stocks and a crypto position. Around a third sits in a diversified US equity ETF, with another chunk in international stocks and a money market fund, while the rest leans into single names plus Ethereum and silver. That blend creates a core‑and‑satellite structure: a steady core wrapped around speculative positions. Because the history we have is only about seven months, it’s hard to know if this balance will feel comfortable in a real bear market. In setups like this, the key takeaway is that the satellites can dominate outcomes even when they look small in percentage terms.
Growth
Over this short 7‑month window, the portfolio turned $1,000 into about $1,074, beating both US and global market benchmarks by a wide margin. The reported Compound Annual Growth Rate (CAGR) is extremely high because it’s annualizing a brief, favorable period; it does not mean that pace is sustainable. Max drawdown of about -7% has been modest given the speculative rating, but again that’s during a specific slice of market history. Almost all returns came from a single day, which shows how lumpy performance can be. The main takeaway: recent results are strong but heavily path dependent, and they shouldn’t be treated as evidence of a long term pattern.
Projection
The Monte Carlo projection simulates 1,000 possible 15‑year paths, using the short history to generate many “what if” futures. It shows a median outcome of about $2,669 from a $1,000 start, with a wide range between roughly $958 and $8,195. Monte Carlo is helpful for visualizing uncertainty, but with only seven months of data, the inputs are noisy and likely overstate both return and risk. The simulation is essentially amplifying recent high volatility into the future. So these numbers are better viewed as a rough illustration of how unpredictable a speculative portfolio can be, not as a forecast you can plan around.
Asset classes
- Stocks 74%
- No data 13%
- Crypto 11%
- Other 3%
Asset class exposure is dominated by stocks at around 74%, with 11% in crypto, a small slice in “other,” and 13% classified as “no data.” That mix is clearly growth oriented, with only a modest buffer from cash‑like or defensive assets. For a speculative investor, this equity‑heavy profile aligns with a focus on long term appreciation over stability. The crypto allocation adds an extra layer of potential upside and downside, amplifying swings. Because some holdings lack clear asset class tags, the exact risk blend is a bit fuzzy, but the overall picture is still aggressive rather than balanced or income focused.
Sectors
- Technology 23%
- Financials 11%
- Consumer Discretionary 9%
- Telecommunications 8%
- Health Care 7%
- Industrials 6%
- Consumer Staples 3%
- Energy 2%
- Basic Materials 2%
- Utilities 1%
- Real Estate 1%
This breakdown covers the equity portion of your portfolio only.
Sector exposure shows a strong tilt toward technology and related areas, with tech alone at 23% and solid chunks in financials, consumer discretionary, and telecom. This kind of profile often does very well when innovation themes and risk appetite are strong, but it can be hit hard if interest rates stay high, regulation bites, or growth sentiment turns. On the plus side, there is at least some representation across all major sectors, which supports the “broadly diversified” label. Still, the portfolio behaves more like a growth engine than a defensive all‑weather mix, so swings may be larger than a more evenly spread sector allocation.
Regions
- North America 62%
- Europe Developed 5%
- Japan 2%
- Asia Developed 2%
- Asia Emerging 2%
- Australasia 1%
This breakdown covers the equity portion of your portfolio only.
Geographically, about 62% of exposure is in North America, with smaller slices in developed Europe, Japan, other developed Asia, and emerging Asia. That North America tilt lines up with many global benchmarks, where US‑linked markets also dominate. This alignment is actually a positive: it keeps the portfolio connected to some of the world’s largest, most liquid markets. The overseas exposure adds helpful diversification, especially if non‑US regions go through different economic cycles. Given the short performance history, it’s too early to say whether this geographic mix will consistently reduce risk, but structurally it’s in line with widely used global market standards.
Market capitalization
- Mega-cap 39%
- Large-cap 20%
- Mid-cap 11%
- Micro-cap 1%
- Small-cap 1%
This breakdown covers the equity portion of your portfolio only.
Market cap exposure is anchored in mega‑cap and large‑cap companies, which together make up roughly 59% of the equity slice. These bigger firms tend to be more established and liquid, often smoothing out some volatility compared with a pure small‑cap portfolio. At the same time, there are small and micro‑cap positions, which can move sharply in both directions and contribute to the speculative profile. Historically, a blend of sizes can support diversification across business stages, but with limited data we can’t judge how this mix responds across full market cycles. The key point: the giants provide stability while the tiny names inject substantial extra risk.
True holdings
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-
Part of fund(s):
- Vanguard S&P 500 ETF
-
Part of fund(s):
- Vanguard S&P 500 ETF
-
Part of fund(s):
- Vanguard S&P 500 ETF
-
-
-
Part of fund(s):
- Vanguard S&P 500 ETF
-
AA Apple Inc 2.39%
Part of fund(s):- Vanguard S&P 500 ETF
-
-
AV Broadcom Inc 0.92%
Part of fund(s):- Vanguard S&P 500 ETF
- Top 10 total 35.40%
This breakdown covers the equity portion of your portfolio only.
Looking through the funds, several big tech and growth names appear both directly and via ETFs, notably Amazon, Alphabet, Microsoft, and NVIDIA. This “overlap” means those companies have more influence than the headline weights suggest, creating hidden concentration risk. For example, Amazon’s total exposure is noticeably higher when you add its ETF share to the direct stock position. Coverage of underlying holdings is limited to top‑10 ETF positions, so overlap is likely understated. In practice, that means the portfolio’s fate is more tied to a small group of large companies than it appears, a tradeoff between potential upside and vulnerability if those names fall out of favor.
Factors
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 a very low tilt to the size factor, meaning the portfolio is skewed toward larger companies rather than smaller ones. Factor investing looks at traits like value, size, momentum, and quality that research links to long term returns. A strong tilt away from size suggests fewer small caps relative to a market‑neutral mix, which can reduce idiosyncratic risk but may miss some small‑cap bursts. Quality exposure is high, which often means more profitable or financially healthy firms, and that’s a nice offset to the speculative elements. With only months of history, though, the actual behavior of these tilts over time remains uncertain.
Risk contribution
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Immunitybio Inc
Weight: 3.02% 49.5% -
Intel Corporation
Weight: 5.80% 29.3% -
iShares Silver Trust
Weight: 2.58% 16.9% -
Vanguard S&P 500 ETF
Weight: 35.93% 16.4% -
Vanguard Total International Stock Index Fund ETF Shares
Weight: 12.34% 11.4% - Top 5 risk contribution 123.6%
Risk contribution data is striking: Immunitybio is only about 3% of the portfolio by weight but contributes roughly half of the total volatility. Intel also carries almost a third of risk, and the silver ETF adds a sizable chunk, so the top three risk contributors drive about 96% of overall ups and downs. Meanwhile, the broad S&P 500 ETF is over a third of the weight yet contributes relatively little to risk. This shows how a few volatile names can dominate the experience. Rebalancing or trimming such positions is one common way investors try to align risk with their intended allocations, especially in speculative setups.
Redundant positions
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High correlationImmunitybio InciShares Silver TrustMicrosoft CorporationAlphabet Inc Class AIntel CorporationGrayscale Ethereum Mini Trust (ETH)Fidelity® Government Money Market Fund
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High correlationVanguard Total International Stock Index Fund ETF SharesVanguard S&P 500 ETF
The correlation data shows many assets moving almost identically over this short period, including some surprising pairs like Immunitybio with Microsoft, or silver with a money market fund. Correlation measures how often things move together; when correlations are high, diversification benefits can shrink during stress. With only seven months of history, these relationships may be more noise than signal and could easily change in a different market environment. Still, the pattern suggests that in a sharp downturn, several holdings could fall at the same time, limiting protection. It’s a reminder that diversification isn’t just about counting holdings; it’s about how they actually behave.
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 efficient frontier chart, the current portfolio sits well below the curve, with a Sharpe ratio of 2.37 versus a much higher ratio for the mathematically “optimal” mix using the same ingredients. The Sharpe ratio compares return to volatility, like measuring how much reward you get per unit of risk. Being below the frontier means that, based on recent data, different weights in these same holdings could have delivered better risk‑adjusted performance. That said, the inputs rely on a very short, unusually strong period, so the extreme numbers are not dependable. Still, it suggests that the risk taken is driven by a few hot positions rather than a finely tuned balance.
Dividends
- Alphabet Inc Class A 0.30%
- Microsoft Corporation 0.90%
- Vanguard S&P 500 ETF 1.20%
- Vanguard Total International Stock Index Fund ETF Shares 3.00%
- Fidelity® Government Money Market Fund 1.80%
- Weighted yield (per year) 1.07%
Income from this portfolio is modest, with an overall yield around 1.07%. Most of the yield comes from the international index fund and the money market fund, while several big holdings either don’t pay dividends or pay very little. Dividends matter if someone wants regular cash flow or a cushion during flat markets, but they’re less central in a growth‑heavy, speculative approach. Here, most of the expected return is from price movement, not income. That’s fine for long horizons and higher risk tolerance, but it does mean that in sideways markets, this setup won’t generate much cash on its own.
Ongoing product costs
- iShares Silver Trust 0.50%
- Vanguard S&P 500 ETF 0.03%
- Vanguard Total International Stock Index Fund ETF Shares 0.05%
- Weighted costs total (per year) 0.03%
Costs are a bright spot. The broad index ETFs are extremely cheap, with expense ratios as low as 0.03% and a total blended TER of about 0.03% across the fund portion. Lower ongoing fees mean more of any future return stays in your pocket, and this structure is very well aligned with best practices in cost control. The slightly higher fee on the silver ETF is normal for that niche and small relative to the overall mix. Over long horizons, even small fee differences compound, so having such low‑cost core holdings is a solid foundation, especially when paired with more speculative satellites.
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