Highly concentrated bitcoin focused portfolio with speculative performance and very short track record
Report created on Jun 14, 2026Risk profile
7/7
Diversification profile
3/5
Positions
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FB Fidelity Wise Origin Bitcoin Trust
FBTC - US3159481098 36.00% -
IB iShares Bitcoin Trust
IBIT - US46438F1012 34.00% -
MS MicroStrategy Incorporated
MSTR - US5949724083 28.00% -
ST MicroStrategy Incorporated Variable Rate Series A Perpetual Stretch Preferred Stock
STRC - US5949728530 2.00%
This portfolio is highly concentrated, with roughly 70% in bitcoin-focused crypto trusts and 30% in a single operating company plus its preferred stock. The structure is effectively a bet on one underlying theme, expressed partly through direct crypto exposure and partly through a company whose fortunes are tightly linked to that same asset. With only about 10 months of data, it is hard to judge whether this pattern is temporary or persistent. Concentrated portfolios like this can move very sharply both up and down, because there are few independent drivers. The main takeaway is that portfolio behavior will largely follow the path of bitcoin and MicroStrategy rather than a broad mix of unrelated investments.
Growth
One or more local-currency benchmark funds are unavailable for this report.
Over the roughly 10‑month period available, a hypothetical $1,000 in this portfolio fell to about $490, a compound annual growth rate (CAGR) of about ‑56%. CAGR is like average speed on a road trip, showing how fast value changed per year on average. The maximum drawdown of about ‑55% means the deepest peak‑to‑trough loss has not yet been recovered. Over the same window, the global market benchmark grew strongly, so the portfolio lagged by a wide margin. Because this is a very short and particularly weak slice of history, it shows downside potential more than long‑term typical behavior, which cannot be inferred confidently from such limited data.
Projection
The forward projection uses a Monte Carlo simulation, which takes the short return history, scrambles and replays it thousands of times to map a range of possible 15‑year outcomes. Here, the median result grows $1,000 to about $1,521, but the “likely” middle band spans roughly $500 to $4,228, and the wider band runs from about $108 to over $20,000. That huge spread reflects the very high volatility built into the inputs. Because the simulation is fed with only around 10 months of data, the reliability of these numbers is limited. They illustrate that outcomes could be extremely good or extremely poor, rather than predicting any specific path.
Asset classes
- Crypto 70%
- Stocks 30%
By asset class, the portfolio is 70% crypto and 30% stocks. Compared with broad global equity or balanced portfolios, this is an unusually large allocation to a single alternative asset class. Crypto has historically shown much bigger and faster price swings than many traditional assets, which tends to dominate overall behavior when it’s this large. The single‑company stock exposure does little to offset that, since it is economically tied to the same theme. With such a short data window, it is hard to quantify long‑term diversification benefits, but structurally this mix is built around one primary risk factor rather than several independent ones.
Sectors
- Crypto 70%
- Technology 30%
This breakdown covers the equity portion of your portfolio only.
Sector-wise, the portfolio is effectively split between “crypto” and technology, with 70% classified as crypto and the remaining 30% in a technology‑related company and its preferred stock. This is very different from diversified portfolios that spread across many industries such as healthcare, consumer, or industrials. Sector concentration matters because shocks that hit one theme can impact all holdings at once. Tech‑linked and crypto‑linked assets can be particularly sensitive to sentiment, regulation, and liquidity conditions. With only 10 months of history, it is too early to generalize long‑term sector behavior here, but the structure clearly leaves little insulation from technology and digital‑asset cycles.
Regions
- North America 30%
This breakdown covers the equity portion of your portfolio only.
On a geographic basis, only the 30% stock allocation shows as North America, while the crypto trusts are not classified in the same way. Compared with global benchmarks, which spread exposure across many regions, this portfolio has limited identifiable geographic diversification. The main economic exposure is tied to one listed company and the broader global crypto market rather than to a broad mix of countries. Geographic spread can help when different regions move on different cycles, but here most of the risk is driven by a single theme that tends to trade more on global risk appetite than on local economic data. The brief history doesn’t yet reveal how it behaves across full economic cycles.
Market capitalization
- Large-cap 28%
- No data 2%
This breakdown covers the equity portion of your portfolio only.
By market capitalization, about 28% of the portfolio is in a large‑cap stock, with another 2% in preferred shares where size data is marked “no data.” The remaining 70% in crypto does not slot into traditional size buckets. In a typical equity portfolio, a mix of large, mid, and small companies can diversify business risk and liquidity conditions. Here, the one large‑cap exposure plus crypto means there is effectively no spread across different company sizes. Over long periods, smaller companies can behave differently from large ones, but that potential diversification is not represented. The short return record makes it difficult to test how size might matter here, but structurally the mix is very narrow.
True holdings
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BT Grayscale Bitcoin Mini Trust (BTC) 34.00%
Part of fund(s):- iShares Bitcoin Trust
-
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- Top 10 total 64.00%
This breakdown covers the equity portion of your portfolio only.
The look‑through view shows that MicroStrategy appears directly as 28% of the portfolio, while the crypto trusts roll up to a single underlying asset: bitcoin. A key point is hidden concentration: although there are several line items, economically the exposures are heavily tied to just two main drivers. Overlap may even be understated because only ETFs’ top 10 holdings are captured. When the same underlying asset appears through multiple vehicles, the portfolio can react as if it were a single large position. With only 10 months of data, the exact correlation between these underlying pieces may change over time, but structurally the dependence on bitcoin and MicroStrategy is very strong.
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 analysis suggests a strong tilt toward value (77%), with very low exposure to size, momentum, quality, and low volatility factors. Factors are like underlying “ingredients” that help explain how investments behave. Very low size exposure indicates a tilt away from smaller companies, consistent with the single large‑cap equity holding plus crypto that does not register as small‑cap equity. Very low momentum, quality, and low volatility all point toward a profile that may move sharply and not track the steadier characteristics often seen in diversified portfolios. Because these factor scores are built on limited history and a very specialized set of assets, they should be viewed as rough signals, not precise long‑term traits.
Risk contribution
-
MicroStrategy Incorporated
Weight: 28.00% 38.3% -
Fidelity Wise Origin Bitcoin Trust
Weight: 36.00% 31.5% -
iShares Bitcoin Trust
Weight: 34.00% 29.9% -
MicroStrategy Incorporated Variable Rate Series A Perpetual Stretch Preferred Stock
Weight: 2.00% 0.3%
Risk contribution shows how much each holding drives the portfolio’s ups and downs, which can differ from its weight. MicroStrategy is 28% of the portfolio but contributes about 38% of total risk, meaning its price swings have an outsized impact. Each bitcoin trust is in the mid‑30% weight range and contributes just under one‑third of risk apiece, so together with MicroStrategy they account for nearly all volatility. The tiny preferred stock position adds almost no risk. This pattern is typical in concentrated, high‑volatility portfolios, where a few positions dominate risk. With only about 10 months of data, these exact percentages may shift over time, but the overall story of concentrated risk is clear.
Redundant positions
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High correlationiShares Bitcoin TrustFidelity Wise Origin Bitcoin Trust
The available correlation data highlights that the two bitcoin trusts have moved almost identically. Correlation measures how often assets move together; a value near 1 means they tend to rise and fall in tandem. When holdings are highly correlated, owning more than one does not add much diversification, even if they are different tickers. Instead, it mainly increases exposure to the same underlying driver. Here, the close relationship between the crypto trusts reinforces the idea that the portfolio behaves more like a single, amplified bet than a mosaic of independent pieces. With only 10 months observed, these relationships could evolve, but the current pattern is tight co‑movement.
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 chart compares the current portfolio to the best risk‑return trade‑offs possible using the same holdings in different weightings. The current mix has a very negative Sharpe ratio, a measure of return per unit of risk after accounting for a risk‑free rate, while both the optimal and minimum‑variance portfolios show much higher Sharpe ratios and far lower volatility. The fact that the current point sits well below the frontier indicates that, over this short and unfavorable period, the chosen weights delivered much lower returns than what was historically achievable with the same building blocks. Given the limited 10‑month sample and extremely volatile assets, these optimization results should be treated as illustrative rather than a guide to future behavior.
Dividends
- MicroStrategy Incorporated Variable Rate Series A Perpetual Stretch Preferred Stock 9.50%
- Weighted yield (per year) 0.19%
Dividend yield is minimal overall, at about 0.19%, despite the preferred stock listing a high coupon rate of 9.5%. That small position size means its income contribution barely moves the needle at the portfolio level. Dividends can provide a steadier component of total return, especially when price movements are volatile, but this structure is clearly built around capital appreciation (and depreciation) rather than income. With only a short timeline observed, there is not yet a track record of how payouts behave across market conditions. In practice, most of the portfolio’s value changes will come from price swings in bitcoin and MicroStrategy rather than from regular cash flows.
Ongoing product costs
- Fidelity Wise Origin Bitcoin Trust 0.25%
- iShares Bitcoin Trust 0.12%
- Weighted costs total (per year) 0.13%
The total expense ratio (TER) across the holdings is low at about 0.13%, with the bitcoin trusts individually charging 0.25% and 0.12%. TER measures the annual fee level as a percentage of assets, and lower ongoing costs mean less performance drag over time. For a niche, specialized theme, this fee level is impressively low and compares favorably with many alternative products. Over long horizons, even small fee differences can compound, but here the main driver of outcomes will clearly be market movements rather than costs. Given the short 10‑month history, cost efficiency has not had much time to show up yet, but structurally the fee foundation is strong.
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