High octane crypto equity mix with concentrated tech exposure and pronounced drawdown potential
Report created on Apr 20, 2026Risk profile
- Secure Speculative
The risk profile, derived from past market volatility, reflects the level of risk the portfolio is exposed to. This assessment helps align your investments with your financial goals and comfort with market fluctuations.
Diversification profile
- Focused Diversified
The diversification assessment evaluates the spread of investments across asset classes, regions, and sectors. This ensures a balanced mix, reducing risk and maximizing returns by not concentrating in any single area.
Positions
-
BT Bitcoin
BTC 40.61% -
AA Apple Inc
AAPL - US0378331005 14.21% -
MS Microsoft Corporation
MSFT - US5949181045 13.20% -
ET Grayscale Ethereum Mini Trust (ETH)
ETH 12.18% -
SP SPDR S&P 500 ETF Trust
SPY - US78462F1030 11.17% -
TS Tesla Inc
TSLA - US88160R1014 8.63%
This portfolio is built around a concentrated blend of crypto and a few large US stocks. Over half of the value sits in Bitcoin and Ethereum, with the rest in three mega-cap tech names plus a broad US market ETF. That creates a compact, high-conviction structure rather than a wide spread of holdings. A setup like this can move sharply because each position is large, and there are no bonds or cash offsets in the mix. The officially “aggressive” risk label and high risk score line up with what the holdings suggest: this is a portfolio that’s oriented toward strong upside swings but also sizable downturns when markets, especially crypto, are under pressure.
Growth
Over the roughly 1.7-year period available, $1,000 grew to about $1,084, giving a Compound Annual Growth Rate (CAGR) of 4.82%. CAGR is the average yearly growth rate, like checking your average speed over a whole road trip. During the same time, both the US market and a global benchmark grew much faster, in the mid-teens. The portfolio also saw a maximum drawdown of about -35%, meaning the deepest peak-to-trough loss was over a third of its value and has not yet fully recovered. With such a short history and a crypto-heavy mix, these numbers show what can happen over one recent cycle, not a long-term pattern.
Projection
The Monte Carlo projection uses the limited past data to randomly remix returns 1,000 times and see a range of possible 15-year outcomes. It’s a bit like simulating thousands of alternate timelines based on what’s happened so far. The median path roughly doubles the initial $1,000, but the “likely” band is extremely wide, from less than the starting amount to more than quadruple it. Even the 5–95% range stretches from losing most of the capital to very large gains. Because the underlying history is barely 1.7 years and heavily influenced by crypto volatility, these projections are particularly fragile and should be read as an illustration of uncertainty rather than a reliable roadmap.
Asset classes
- Crypto 53%
- Stocks 47%
By asset class, about 53% sits in crypto and 47% in equities, with no bonds or cash-like assets included. That’s a far cry from broad benchmarks, where crypto is either a tiny slice or not present at all, and bonds commonly play a role in smoothing returns. Having more than half in crypto means portfolio behavior is likely to be dominated by episodes in that market, which has historically seen big booms and deep drawdowns. The equity slice does add some balance, but it’s still entirely in growth-oriented stocks and an equity ETF, so it does not provide the kind of downside cushioning that more defensive asset classes might offer in risk-off environments.
Sectors
- Technology 31%
- Consumer Discretionary 10%
- Financials 1%
- Telecommunications 1%
- Health Care 1%
- Industrials 1%
- Consumer Staples 1%
This breakdown covers the equity portion of your portfolio only.
Within the equity portion, sector data shows a strong lean toward technology, with additional exposure in consumer discretionary and small slices in several other sectors via the ETF. Compared with a broad market, this portfolio is more tech-focused and less spread across defensive areas like utilities or traditional staples. Tech and consumer discretionary companies tend to be more sensitive to economic cycles and interest rate changes, often moving more dramatically in both up and down markets. This focused sector profile can amplify gains when growth companies are favored, but it also means that sector-specific setbacks—such as regulatory shifts or tech valuation resets—can have an outsized impact on the portfolio’s total return.
Regions
- North America 47%
This breakdown covers the equity portion of your portfolio only.
Geographically, the equity allocation is entirely in North America, with 47% of the portfolio measured as US-focused. Global indices usually blend US, Europe, Asia, and emerging markets, so this is a clear US tilt on the stock side. Crypto holdings, while global in trading, are not classified by region here, so the diversification benefit they may or may not add across economies is hard to quantify in standard geographic terms. Having all the equity exposure in one region means outcomes are closely tied to the US economic cycle, policy decisions, and currency movements. That alignment has helped in the recent decade but also means there’s limited offset if other regions perform differently.
Market capitalization
- Mega-cap 41%
- Large-cap 4%
- Mid-cap 2%
This breakdown covers the equity portion of your portfolio only.
Market capitalization data shows a clear bias toward mega-cap companies, with smaller slices in large- and mid-cap names via the ETF. Mega-caps are the biggest companies in the market, often with strong balance sheets and global reach, which can support resilience compared with smaller firms. At the same time, this cap profile means the equity part of the portfolio tends to move similarly to the largest index names, rather than reflecting smaller, more niche companies. Because crypto is outside this classification, the overall portfolio still carries very high volatility, but within equities, the dominance of mega-caps aligns closely with mainstream indices and can help moderate risk relative to holding only smaller, more speculative stocks.
True holdings
-
Part of fund(s):
- SPDR S&P 500 ETF Trust
-
Part of fund(s):
- SPDR S&P 500 ETF Trust
-
Part of fund(s):
- SPDR S&P 500 ETF Trust
-
NV NVIDIA Corporation 0.85%
Part of fund(s):- SPDR S&P 500 ETF Trust
-
AM Amazon.com Inc 0.44%
Part of fund(s):- SPDR S&P 500 ETF Trust
-
GO Alphabet Inc Class A 0.35%
Part of fund(s):- SPDR S&P 500 ETF Trust
-
AV Broadcom Inc 0.32%
Part of fund(s):- SPDR S&P 500 ETF Trust
-
GO Alphabet Inc Class C 0.28%
Part of fund(s):- SPDR S&P 500 ETF Trust
-
ME Meta Platforms Inc. 0.26%
Part of fund(s):- SPDR S&P 500 ETF Trust
-
BR Berkshire Hathaway Inc 0.17%
Part of fund(s):- SPDR S&P 500 ETF Trust
- Top 10 total 40.16%
This breakdown covers the equity portion of your portfolio only.
The look-through analysis shows that Apple, Microsoft, and Tesla appear both as direct holdings and indirectly through the S&P 500 ETF. For example, total Apple exposure is nearly 15%, slightly higher than the direct holding alone, because the ETF also owns Apple. The same pattern applies to Microsoft and Tesla. This kind of overlap creates “hidden” concentration, where a company’s real weight is larger than it looks at first glance. Since ETF data only uses top-10 holdings, true overlap may be somewhat understated. Still, it’s clear that a small set of big tech names represent a sizeable share of total equity exposure, reinforcing the portfolio’s focus on a few familiar giants.
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 reveals a couple of notable tilts. Size exposure is very low, meaning the equity side leans strongly toward larger companies rather than smaller ones; this matches the mega-cap concentration, and often results in behavior similar to broad headline indices rather than small-cap swings. Quality exposure is high, suggesting the stocks tend to have stronger profitability, stability, or balance-sheet metrics compared with the average market. That can sometimes help during periods of stress in equity markets. Other factors like value, momentum, yield, and low volatility are closer to mild tilts and not extreme. It’s important to remember these factor scores only apply to the equity sleeve, while more than half the portfolio sits in crypto, which doesn’t fit neatly into traditional factor frameworks.
Risk contribution
-
Bitcoin
Weight: 40.61% 52.0% -
Grayscale Ethereum Mini Trust (ETH)
Weight: 12.18% 22.9% -
Tesla Inc
Weight: 8.63% 10.4% -
Apple Inc
Weight: 14.21% 5.6% -
Microsoft Corporation
Weight: 13.20% 5.3% - Top 5 risk contribution 96.1%
Risk contribution highlights how much each position drives the portfolio’s overall ups and downs, which can differ a lot from its weight. Bitcoin, at about 41% weight, contributes roughly 52% of total risk, showing it’s more volatile than its size alone suggests. Ethereum, with only 12% weight, contributes almost 23% of risk, making it disproportionately influential. The top three positions by risk—Bitcoin, Ethereum, and Tesla—collectively account for over 85% of portfolio volatility. Meanwhile, Apple and Microsoft have sizable weights but much lower risk shares, behaving more like stabilizers. This pattern underscores that the portfolio’s day-to-day behavior is overwhelmingly determined by the crypto slice and one high-volatility stock.
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 shows the current portfolio sitting below the efficient frontier, meaning that with the same set of holdings, different weights could have delivered higher expected return for the same risk, or similar return with less risk. The Sharpe ratio, which measures return per unit of volatility above the risk-free rate, is 0.3 for the current mix versus 0.81 for the optimal portfolio and 0.74 for the minimum-variance version. Being 11.75 percentage points below the frontier at its risk level indicates that the present configuration is relatively inefficient. This doesn’t say anything about future performance, but it does show that, historically, the same ingredients might have been combined in a more balanced way.
Dividends
- Apple Inc 0.40%
- Microsoft Corporation 0.80%
- SPDR S&P 500 ETF Trust 0.80%
- Weighted yield (per year) 0.25%
Dividend yield across the portfolio is low at about 0.25%, with modest contributions from Apple, Microsoft, and the S&P 500 ETF. A dividend is a cash payment from a company’s profits, and yield measures those payments relative to price. Here, the equity picks and the crypto exposure clearly lean toward growth potential rather than income generation. Most of the expected return, if it comes, is likely to be from price changes rather than regular cash payouts. For investors who care mainly about total return, low yield isn’t necessarily a problem, but it does mean that the portfolio relies largely on market appreciation, which can be more volatile and less predictable over short spans like the 1.7 years observed.
Ongoing product costs
- SPDR S&P 500 ETF Trust 0.10%
- Weighted costs total (per year) 0.01%
On the cost side, the only ongoing fund fee is the 0.10% Total Expense Ratio (TER) of the S&P 500 ETF, leading to a very low blended TER of around 0.01% for the whole portfolio. TER is like a small annual service charge taken out inside the fund; lower fees leave more of any returns in the investor’s hands over time. This cost level is impressively low and aligns with best practices for long-term investing, where reducing friction can make a noticeable difference over decades. With costs largely under control, the main drivers of the portfolio’s outcome are asset selection and volatility rather than drag from management fees.
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