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.
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.
The structure is very straightforward: about 86% sits in broad stock index mutual funds and roughly 14% is in a single speculative biotech stock. That makes this a 100% equity portfolio, with one big satellite position wrapped around low-cost core holdings. This kind of setup matters because the funds provide wide diversification while the single stock introduces very specific company risk. In practical terms, most of the account behaves like the overall market, but the fate of that one stock can meaningfully swing total returns. Anyone using a similar layout should be very deliberate about whether that concentrated bet size truly matches their comfort level.
From 2018 to early 2026, the hypothetical $1,000 grows to about $2,117, implying a compound annual growth rate (CAGR) of 11.88%. CAGR is like your average speed on a long road trip, smoothing out bumps along the way. The US market proxy did a bit better (13.40% CAGR to $2,603), while the global market did slightly worse (10.73% to $2,172). The portfolio’s max drawdown, at -38.36%, was deeper than both benchmarks, meaning the worst drop from peak to trough was harsher. With just 13 days making up 90% of returns, timing turned out crucial. This history is decent but also shows higher downside than broad indexes.
The forward projection uses a Monte Carlo simulation, which essentially replays many possible futures by remixing past returns in 1,000 random paths. It’s like running weather models to see a range of possible storms. After 10 years, the 5th percentile outcome is extremely poor (-98.7%), the median is surprisingly negative (-16.4%), while the 67th percentile shows strong gains (about +170%). Around 475 of 1,000 runs end positive. The average simulated annualized return of 18.83% looks high but reflects the historical volatility feeding the model. These ranges highlight that outcomes span from huge losses to big wins, and that simulations, based on past patterns, can’t reliably predict the future or fully capture regime changes.
All assets are in stocks, with no buffer from bonds, cash, or alternatives. That pure-equity stance is what drives the “growth” risk classification and the relatively high risk score of 5/7. Being 100% in stocks matters because drawdowns can be sharp and prolonged, especially during recessions or market panics, without the stabilizing effect other asset classes might provide. Versus a more balanced setup, this approach chases higher long-term return potential at the cost of bigger swings. Anyone using a similar all-stock allocation typically needs a long time horizon and the emotional ability to ride through deep, multi-year downturns without feeling forced to sell.
Sector exposure is spread but tilts toward Technology (26%) and Healthcare (22%), followed by Financials, Consumer Cyclical, Communication Services, and Industrials. This is more growth and innovation heavy than a perfectly even sector mix and reflects the influence of major index funds plus the biotech position. Sector balance matters because different parts of the economy lead or lag in different cycles. Tech and healthcare can deliver strong growth but can be especially sensitive to interest rates, regulation, and innovation risk. The presence of all 11 major sectors, even at smaller weights, supports diversification, and overall the mix lines up reasonably well with broad market norms while still carrying a growth-leaning character.
Geographically, about 83% is in North America, with modest exposure to developed Europe and Japan, plus smaller slices to other regions. That’s more domestic-leaning than many global benchmarks, which usually have somewhat lower US weight. Geographic mix matters because different regions face different economic cycles, interest rate paths, and political risks. A strong tilt to one region means fortunes are tightly tied to that area’s performance. On the plus side, the US has been a standout over the past decade, so this alignment has historically been beneficial. The existing international slice still adds some global diversification without overwhelming the home-market focus.
By market cap, there is a strong tilt to the largest companies: about 41% mega-cap and 30% big-cap, with 14% mid and 15% small. Market cap describes a company’s size by total stock value, and it shapes how a portfolio behaves. Large companies often provide stability and are widely researched, while smaller ones can be more volatile but sometimes offer higher growth potential. This blend leans toward the safety of giants while still keeping a meaningful allocation to smaller names through the total market and international funds. That combination can help smooth extremes somewhat while still leaving room for more dynamic, smaller-company performance.
Looking through the funds, the top underlying exposures are dominated by mega-cap growth names like NVIDIA, Apple, Microsoft, Amazon, Alphabet, Meta, Tesla, plus the direct Sellas position. Only about 43% of the portfolio is captured by this look-through, and ETF coverage is based on top-10 holdings only, so overlap is likely understated. Still, it’s clear the same big growth companies appear in multiple funds, creating hidden concentration. That means performance will be heavily tied to how a relatively small group of large stocks behave. When so much rests on a handful of names, it can turbocharge gains in good times but also magnify pain if that group falls out of favor.
Factor exposure shows strong tilts to Size (85%), Momentum (46.3%), and some Value (20%), with limited exposure to Quality and Low Volatility. Factors are like underlying “traits” of the portfolio—such as cheap vs. expensive, big vs. small, steady vs. jumpy—that research has linked to returns over decades. A strong Size and Momentum tilt suggests an emphasis on smaller and recently strong performers, which can shine in trending bull markets but may suffer in sharp reversals. Low Quality and Low Volatility exposure implies less focus on “steady-eddy” companies. Signal coverage, at 26% on average, is incomplete, so readings aren’t perfect, but they still hint at a return-chasing, higher-octane growth profile rather than a defensive tilt.
Risk contribution shows how much each holding drives the portfolio’s overall ups and downs, which can differ a lot from simple weight. Here, Sellas has a 13.99% weight but contributes a huge 53.54% of total risk—a risk-to-weight ratio of 3.83. In contrast, the large index funds contribute much less risk than their weights would suggest. That means more than half of the portfolio’s volatility is effectively coming from a single speculative stock. Top three holdings account for almost all risk (96.91%), but one dominates. When one position’s risk footprint is that oversized, it’s crucial to be consciously comfortable with potentially extreme swings tied to that company’s fate.
Correlation looks at how holdings move relative to each other. The two main US equity funds are highly correlated, meaning they generally rise and fall together. That’s expected because both track broad US stock markets with overlapping constituents. High correlation isn’t inherently bad; it simply means that owning both doesn’t dramatically increase diversification. In downturns, these funds will likely move in the same direction, limiting the portfolio’s ability to offset losses within the equity bucket. The good news is that the international fund and the biotech stock introduce some differentiation, but overall, the structure still behaves a lot like a concentrated bet on global and especially US equities.
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 risk vs. return chart, the current mix has expected return of 17.26% with 25.47% volatility and a Sharpe ratio of 0.6. The Sharpe ratio measures return per unit of risk—the higher, the better. The portfolio sits on the efficient frontier, meaning that, given the chosen holdings, it’s already using them in a mathematically efficient way. However, it’s not at the optimal point: the highest Sharpe portfolio uses a bit less risk (20.72%) for a still strong 16.07% return and a Sharpe of 0.73. That suggests reweighting away from the riskiest elements, not adding new products, could slightly improve the risk-adjusted profile while preserving a growth orientation.
The total portfolio yield sits around 1.29%, with the international fund offering the highest yield among the components. Dividend yield is the annual cash payout as a percentage of investment value, and it can be an important part of total return, especially for income-focused investors. Here, the yield is modest, consistent with a growth-oriented, equity-only setup skewed toward large US companies. Most of the expected reward is from price appreciation rather than cash flow. For an investor mainly targeting long-term growth and willing to reinvest dividends, this is perfectly reasonable and aligns well with common equity index strategies rather than a high-income approach.
Costs are impressively low, with the flagship S&P 500 index fund at just 0.02% and an overall TER around 0.01%. TER, or total expense ratio, is the annual fee charged by funds, and even tiny differences compound meaningfully over decades. Keeping fees this low is a major structural advantage, letting more of the portfolio’s return stay in the account rather than flowing to managers. This allocation is well-balanced from a cost perspective and aligns closely with best practices used by many long-term investors. With expenses already near rock-bottom, there is little to gain from further fee optimization; attention can focus instead on risk, diversification, and allocation choices.
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