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 portfolio is almost entirely in equities, with 99% in stocks, 1% in “other” (mainly gold), and 1% in crypto. Within stocks, there’s a heavy tilt to US large-cap funds, led by a big core in a broad US index ETF and sizable positions in momentum and growth ETFs. A handful of small satellite positions target themes like semiconductors, defense, and clean infrastructure. This is essentially a growth-oriented, equity-heavy setup with a small sleeve for gold and bitcoin as diversifiers. The big takeaway is that it behaves much more like a stock portfolio than a classic “balanced” mix, so someone using it should be comfortable with stock-style ups and downs.
From early 2024 to April 2026, a hypothetical $1,000 grew to about $1,511, giving a compound annual growth rate (CAGR) of 20.45%. CAGR is like the constant yearly “speed” that would get you from the starting value to the ending value. Over this period, that beat both the US market and global market by roughly 3 percentage points a year, which is impressive. The max drawdown, or worst peak-to-trough drop, was about -19.7%, similar to the benchmarks. That means the extra return didn’t come with noticeably worse downside so far. Still, this is a relatively short, strong period for stocks, so it doesn’t guarantee similar outperformance in tougher markets.
The Monte Carlo projection runs 1,000 simulations of future returns using past volatility and correlations as a guide, then shows a range of possible 15‑year outcomes. Think of it as rolling the dice many times on what markets could do, while keeping the portfolio mix fixed. The median path grows $1,000 to about $2,745, with a broad “likely” band from roughly $1,800 to $4,100. There’s also a meaningful chance of basically flat or negative results, which the low end of the range highlights. The 8.13% annualized simulated return is reasonable for an equity-heavy mix, but it’s still just a model based on history, not a prediction or guarantee.
Asset-class-wise, this is almost a pure equity portfolio. Compared with a traditional “balanced” mix that might hold 40%–60% in bonds, there’s essentially no fixed income ballast here. Equities tend to drive long-term growth but also deliver sharper drawdowns, because there’s nothing defensive in size to cushion big stock-market falls. The small allocations to gold and bitcoin offer some diversification, but they’re too small and volatile on their own to act like classic stabilizers. The positive side is clear growth focus; the trade-off is that short- and medium-term portfolio swings will closely track equity market cycles, not a smoother balanced profile.
Sector exposure is strongly tilted toward technology at 41%, with the remainder spread across industrials, financials, telecom, health care, consumer areas, energy, materials, utilities, and real estate. This tech emphasis is higher than broad global or US benchmarks, which typically put tech closer to a quarter to a third of the equity universe. That tilt has helped performance in a period when tech and related growth names have led the market. The flip side is sensitivity to things like interest-rate moves or sentiment shifts that often hit tech and growth hardest. In those environments, this sector mix may see bigger swings than a more even spread.
Geographically, the portfolio is overwhelmingly concentrated in North America at 94%, with only modest exposure to developed Europe, Japan, and other Asian markets. In global stock benchmarks, the US and broader North America usually sit closer to 60%–65% of market value, so this is a clear home-country tilt. That’s worked very well over the last decade-plus, as US stocks have outpaced many other regions. The trade-off is that economic and policy shocks in the US will dominate the portfolio’s behavior, since there’s limited offset from other regions. For someone wanting true global diversification, this is a point to be aware of rather than a hidden surprise.
The market-cap breakdown shows a strong focus on the largest companies: about 45% in mega-caps and 36% in large caps, with much smaller slices in mid, small, and micro caps. This closely mirrors broad US and global equity benchmarks, which are naturally top-heavy. The benefit is exposure to more established businesses with deep liquidity and stronger balance sheets on average, which can be more resilient during stress than tiny names. The cost is less participation in potential small-cap catch-up phases, when smaller companies sometimes outperform. Overall, this size mix is pretty standard and helps keep risk anchored in widely followed, well-known firms.
Looking through the ETFs, the portfolio’s biggest underlying exposures cluster in a familiar group of mega tech and growth names: NVIDIA, Apple, Microsoft, Broadcom, Alphabet, Amazon, Meta, Tesla, and Micron. NVIDIA alone adds up to over 8% and Apple about 5.6%, all via funds. Microsoft is notable, because it appears both via ETFs and as a direct 1% stock holding, pushing total exposure to just over 5%. This kind of overlap is common with broad US and growth ETFs, but it does create hidden concentration: if mega-cap tech stumbles, multiple holdings get hit at once. And because we only see ETF top-10s, true overlap is likely higher under the surface.
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 looks mostly balanced. Factor investing focuses on characteristics like value, size, momentum, quality, yield, and low volatility that research links to long-run returns. Here, most measures sit around the neutral range, suggesting something close to a broad market profile. The one notable tilt is a mild underweight to value, with value at 40%, slightly below a neutral 50% baseline. That lines up with the portfolio’s visible preference for growth and tech. In environments where cheaper, more cyclical companies lead, this kind of value-light profile can lag. The plus side is that the factor mix is not lopsided, so behavior should be broadly benchmark-like, just with a modest growth flavor.
Risk contribution shows how much each holding adds to overall ups and downs, which can differ from its simple weight. The top three positions—the broad S&P 500 ETF, the S&P 500 momentum ETF, and the large-cap growth ETF—make up 66% of the portfolio but over 67% of its total risk. Tech and NASDAQ-linked funds also punch a bit above their weight in risk terms, with the dedicated tech ETF contributing more volatility than its 8% slice suggests. None of this is alarming, but it does reinforce that most of the risk lives in a handful of core US-growth vehicles. Tweaking position sizes is one way to dial that dominance up or down.
Correlation measures how closely different holdings move together. When two funds are highly correlated, they tend to rise and fall at the same time, which can limit diversification. Here, many of the strongest relationships appear between broad US funds and the NASDAQ or large-cap growth ETF, and between overlapping international funds. That’s expected, because they’re all drawing from similar stock universes. The important nuance is that owning several highly correlated funds doesn’t diversify much, even if the tickers look different. The upside is that these overlapping exposures are at least low-cost and efficient. The trade-off is that in a broad US or global downturn, they’ll likely all move down together.
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 mix with the best possible combinations of these same holdings. The Sharpe ratio—return per unit of risk—of the current portfolio is 0.92, while the optimal mix of the same assets reaches a Sharpe of 2.49 at similar risk. That’s a big gap, and the portfolio sits about 24 percentage points below the frontier at its risk level. In plain terms, the current weights are not using the available building blocks as efficiently as they could. The data suggests that simply reweighting existing holdings, without adding new ones, could significantly improve the balance between expected return and volatility.
The overall dividend yield of about 0.96% is on the low side, which makes sense for a growth- and tech-heavy equity portfolio. Individual income-oriented funds—like US and international dividend ETFs and high-dividend international stocks—pull yields up a bit, with several paying above 3%. But because their weights are small, they don’t move the total yield that much. For someone focused primarily on long-term capital growth rather than current income, this is a reasonable setup. If steady cash payouts were a priority, a higher overall yield and more sizable allocations to income-focused holdings would typically be needed, acknowledging that yields can change over time.
Costs are a real bright spot here. The overall TER (total expense ratio) across funds is about 0.09%, which is very low by any standard. The bulk of the money sits in ultra-cheap index ETFs from major providers, while the higher-TER thematic and niche ETFs hold only small weights. Lower fees matter because they are one of the few things an investor can control and they compound over time, just like returns. Having such a low-cost core is a genuine advantage: it means more of the portfolio’s gross performance stays in the investor’s pocket. This cost structure is aligned with best practices and supports strong long-term outcomes.
Select a broker that fits your needs and watch for low fees to maximize your returns.
The information provided on this platform is for informational purposes only and should not be considered as financial or investment advice. Insightfolio does not provide investment advice, personalized recommendations, or guidance regarding the purchase, holding, or sale of financial assets. The tools and content are intended for educational purposes only and are not tailored to individual circumstances, financial needs, or objectives.
Insightfolio assumes no liability for the accuracy, completeness, or reliability of the information presented. Users are solely responsible for verifying the information and making independent decisions based on their own research and careful consideration. Use of the platform should not replace consultation with qualified financial professionals.
Investments involve risks. Users should be aware that the value of investments may fluctuate and that past performance is not an indicator of future results. Investment decisions should be based on personal financial goals, risk tolerance, and independent evaluation of relevant information.
Insightfolio does not endorse or guarantee the suitability of any particular financial product, security, or strategy. Any projections, forecasts, or hypothetical scenarios presented on the platform are for illustrative purposes only and are not guarantees of future outcomes.
By accessing the services, information, or content offered by Insightfolio, users acknowledge and agree to these terms of the disclaimer. If you do not agree to these terms, please do not use our platform.
Instrument logos provided by Elbstream.
Your feedback makes a difference! Share your thoughts in our quick survey. Take the survey