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.
This portfolio is built mainly from broad stock index funds with a light touch of active stock picking. Over 65% sits in a total US stock ETF, with another slice in a similar broad US fund, plus small allocations to international stock ETFs. Berkshire Hathaway is a notable single-stock position at nearly 7%, and there is a focused semiconductor ETF at about 6%. A balanced fund adds a small bond component. Structurally, this is a mostly equity, US-led mix with one concentrated growth sleeve in semiconductors. That combination tends to anchor returns to overall stock markets while allowing some extra punch from specific themes and a single large company stake.
From 2016 to 2026, $1,000 in this portfolio grew to about $4,317, a compound annual growth rate (CAGR) of 15.82%. CAGR is like your average speed on a long road trip, smoothing out bumps along the way. Over the same period, the US market grew at 14.68% and the global market at 12.11%, so this portfolio beat both by a meaningful margin. The worst decline, or max drawdown, was about -34% during early 2020, similar to the benchmarks. That shows the portfolio behaved like a growth-oriented equity mix: strong long-run growth but with sharp drops when markets fall. Past performance, though, does not guarantee similar results in the future.
The Monte Carlo projection looks at many possible futures by remixing past returns in thousands of random simulations. It’s like running 1,000 alternate histories for the same portfolio to see a range of outcomes. Over 15 years, a $1,000 starting point has a median result around $2,667, with a “middle” band of roughly $1,778 to $4,061. The simulated average annual return across all paths is about 7.85%. There’s about a 74% chance of ending above the starting amount. These numbers frame expectations: big upside is possible, but weak or flat outcomes also appear in the distribution. All simulations rely on historical behavior, which may not repeat if market conditions change meaningfully.
Almost the entire portfolio, about 98%, is in stocks, with only around 2% in bonds via the balanced fund. Asset classes are broad buckets like stocks, bonds, and cash, and they tend to respond differently to growth, inflation, and interest rates. A stock-heavy mix usually has higher return potential but also bigger swings than portfolios that hold more bonds. Compared with typical global “balanced” mixes that often hold 30–40% in bonds, this portfolio is clearly tilted toward growth. The small bond portion offers only limited cushioning during equity selloffs, so overall behavior is dominated by stock market moves rather than income or capital preservation characteristics.
This breakdown covers the equity portion of your portfolio only.
Sector exposure leans heavily toward technology at about 31%, with financials next at 19%, then industrials, health care, and consumer areas making up much of the rest. A dedicated semiconductor ETF adds extra tech concentration on top of the broad market funds. Sector weights roughly echo a modern global equity index but with a clear tech tilt. That means performance is especially sensitive to cycles in innovation, chip demand, and interest rates. Tech-related holdings often benefit in periods of strong growth and low rates, but they can be more volatile when rates rise or when expectations around earnings and innovation reset sharply. Non-tech sectors still provide some balance but don’t dominate the picture.
This breakdown covers the equity portion of your portfolio only.
Geographically, about 88% of the portfolio sits in North America, with only modest allocations to Europe, Japan, and other regions. Global equity benchmarks typically have closer to 60% in North America, so this is a clear US-centric stance. Geography matters because economies, currencies, and policy decisions differ across regions. A strong US tilt ties results closely to the American economic and market cycle, which has been rewarding in recent decades. However, outcomes also become more sensitive to US-specific events like domestic policy changes or sector booms and busts. The smaller overseas slice does provide some international flavor, but it plays a supporting rather than leading role.
This breakdown covers the equity portion of your portfolio only.
By market capitalization, this portfolio is anchored in mega and large caps, which together make up roughly three-quarters of exposure. Mid caps are meaningful at 17%, while small and micro caps together total about 7%. Market cap is essentially company size; larger firms often have more diversified businesses and steadier earnings, while smaller ones can be more volatile but sometimes faster growing. This mix is closer to a broad-market, size-weighted index than a small-cap-tilted strategy. That helps keep risk in line with mainstream equity markets and avoids over-reliance on very small, thinly traded companies, while still allowing some impact from the smaller-cap portion.
Looking through the funds, a few individual companies show up repeatedly, creating hidden concentration. Berkshire Hathaway totals about 7.85% when combining the direct holding with its presence inside ETFs. Mega-cap tech names like NVIDIA, Apple, Microsoft, Amazon, Alphabet, Meta, and Tesla also appear via the broad US and semiconductor funds. Look-through analysis is based only on ETF top-10 holdings, so overlap is likely understated for the full portfolio. Still, it already reveals a core cluster of large, growth-oriented US names. This type of overlap means these giants can drive results more than their visible fund weights suggest, especially during periods when big tech and related firms sharply rise or fall together.
Factor exposures are broadly neutral across value, size, momentum, quality, yield, and low volatility, all hovering near 50%. Factors are characteristics like “cheap vs. expensive” (value) or “stable vs. jumpy” (low volatility) that research links to long-term return patterns. A neutral reading means the portfolio behaves a lot like the market overall on these dimensions, rather than leaning heavily into any one style. That can be helpful if the goal is to capture general market behavior instead of betting on specific factor premiums. It also means performance relative to broad benchmarks is more likely to come from asset allocation and concentration choices, not from systematic factor tilts.
Risk contribution shows how much each holding adds to the portfolio’s overall ups and downs, which can differ from its weight. The total US stock ETF is about 65% of capital but contributes roughly 67% of risk, very close to proportional. The semiconductor ETF stands out: at 5.6% of the portfolio, it contributes around 8.6% of risk, reflecting its higher volatility. Berkshire and the international ETF each contribute slightly less risk than their weights. Overall, the top three holdings account for over 83% of total risk, so day-to-day swings are mainly driven by a small set of positions, especially broad US equities and the focused semiconductor slice.
The correlation data shows that several holdings move very similarly. The Schwab US broad market ETF and the Vanguard total US ETF are almost perfectly aligned, and the balanced fund also tracks closely with the US market piece despite having some bonds. Likewise, the Schwab and Vanguard international funds move in near lockstep. Correlation measures how assets move together, from -1 (opposite) to +1 (in sync). Highly correlated holdings don’t add much diversification in sharp selloffs because they tend to fall together. Here, multiple US broad-market funds behave almost like a single position, so actual diversification comes more from the international slice, Berkshire, and the semiconductor ETF than from the number of fund tickers alone.
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–return chart, the current portfolio sits below the efficient frontier by about 3 percentage points at its risk level. The efficient frontier represents the best expected return achievable for each risk level using just these existing holdings in different weights. The current Sharpe ratio, a measure of return per unit of risk, is 0.63 versus 1.05 for the optimal mix and 0.67 for the minimum-variance version. That means other weightings of the same funds and stock could historically have offered either higher expected return for similar risk or similar return for lower risk. The existing allocation is functional but not making full use of the diversification benefits available within its own components.
The portfolio’s overall dividend yield is about 1.42%, so most of the historic return has come from price growth rather than income. Individual holdings vary: the balanced fund has a high yield near 5.4%, international ETFs are in the 2.8–3.1% range, while the semiconductor ETF yields very little. Dividends are cash payments from companies and funds, and over long periods they can be an important part of total return, especially when reinvested. In a growth-tilted equity mix like this, dividends play a supporting role rather than driving results. The yield level is consistent with a portfolio focused on broad markets and growth sectors, instead of targeting high income specifically.
Costs are a standout strength here. The weighted average total expense ratio (TER) is about 0.05%, thanks to the heavy use of low-cost index funds from major providers. TER is the annual fee charged by a fund, expressed as a percentage of assets; it quietly chips away at returns every year. Keeping this number very low helps more of the portfolio’s gross performance reach the end investor. Over long horizons, even small fee differences compound into meaningful dollar amounts. This cost level is significantly below many actively managed or niche strategies, which is a strong foundation for long-term compounding and aligns well with broad-market indexing best practices.
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