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 fully invested in US-listed equities, mixing broad-market index funds, growth funds, sector ETFs, dividend strategies, and a single large individual stock. The biggest building block is a core S&P 500 ETF at 20%, surrounded by sizeable allocations to a NASDAQ 100 fund, large-cap growth, and focused sector ETFs in health care, energy, and aerospace and defense. A 10% direct position in NVIDIA creates a notable single-company exposure on top of its presence inside several ETFs. Overall, the structure leans clearly toward growth and US large caps, with some offset from dividend and value funds, which provide a modest income and style counterbalance within the stock-only setup.
Historically, this portfolio turned $1,000 into about $3,492 over the period, a compound annual growth rate (CAGR) of 25.59%. CAGR is like the average yearly “speed” over the whole trip, smoothing out the bumps. That’s meaningfully higher than both the US market (15.08%) and global market (13.13%). The max drawdown of -23.91% was similar to the benchmarks, meaning the downside during the worst period wasn’t much harsher despite higher returns. A small set of 37 days produced 90% of gains, highlighting how a few strong sessions can drive long‑term results. This pattern fits a growth‑tilted portfolio that has benefited from strong performance in leading US names.
The Monte Carlo projection uses past return and volatility patterns to simulate many possible future paths for the portfolio. Think of it as running 1,000 alternate timelines and seeing where $1,000 often ends up after 15 years. The median outcome is about $2,665, with a “middle” range from roughly $1,759 to $4,239 and a wider 5–95% band from $922 to $8,106. The average annualized return across simulations is 8.05%, and about 73% of simulations finish above $1,000. These numbers are not promises; they simply show that the same volatility that powered strong historical gains also creates a broad spread of potential future outcomes.
All of the portfolio sits in stocks, with no allocation to bonds, cash-like assets, or alternatives. That makes the structure straightforward but also firmly equity‑only. Asset classes are like food groups in a diet: using more than one can help smooth out different environments. Here, the entire risk and return experience is tied to stock markets. This aligns with the “Growth” classification and explains the relatively high historic return profile. The flip side is that in periods when equities struggle broadly, there is no built‑in buffer from defensive asset classes, so portfolio ups and downs are driven almost entirely by stock behavior.
Sector exposure is clearly tilted rather than evenly spread. Technology stands out at 32%, with health care around 16% and industrials near 15%, reflecting the aerospace and defense tilt. Energy at 9% is also meaningfully above many broad benchmarks. Holdings in telecom, consumer discretionary, financials, and consumer staples round out the mix, with basic materials and utilities very small. Compared with a typical US market index, tech and a couple of cyclical sectors are heavier here, while more defensive or interest‑rate‑sensitive areas are smaller. This can boost returns when these favored sectors lead, but it also means portfolio results are more tied to their specific cycles and headline risks.
Geographically, the portfolio is almost entirely focused on North America at 99%. That makes it very aligned with the US market, which has been a strong performer in recent years and is heavily represented in global indices. From a diversification lens, though, this means exposures to other major economies and currencies are minimal. If the US market continues to do well, this concentration keeps the portfolio closely linked to that strength. If US equities lag other regions for a stretch, there is little offset from international markets. The geographic score matches the reported low diversification rating and explains some of the portfolio’s strong recent US‑driven returns.
Market capitalization exposure is concentrated in the largest companies: about 38% in mega‑caps and 39% in large caps, with mid caps at 17% and a modest slice in small and micro caps. Mega‑ and large‑cap stocks tend to be mature, widely followed businesses, which can provide liquidity and broad index alignment. The smaller exposure to mid and small caps adds some potential for more idiosyncratic growth and volatility, but it doesn’t dominate the profile. Overall, this mix looks similar to a typical large‑cap‑focused US growth portfolio, where the biggest companies and their performance patterns play the leading role in day‑to‑day and long‑term outcomes.
Looking through the ETFs, NVIDIA stands out as a major underlying position at roughly 14.06% total exposure, combining the 10% direct holding and about 4% through funds. Other mega‑cap names like Apple, Microsoft, Amazon, Alphabet, Eli Lilly, and Meta show up across multiple ETFs, each adding a few percent. This overlap creates hidden concentration: different funds may appear diversified, but they often own the same giants. Because only ETF top‑10 holdings are included, the true overlap is likely somewhat higher. The main takeaway is that a handful of large US growth companies drive a meaningful portion of the portfolio, both directly and indirectly through index and sector funds.
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 is broadly market‑like across the six dimensions shown. Value, momentum, quality, yield, and low volatility all sit in the neutral band, meaning there’s no strong tilt toward or away from these characteristics versus a typical broad market. Size is modestly low, which is consistent with the dominance of mega‑ and large‑cap holdings over smaller companies. Factors can be thought of as the “personality traits” of a portfolio; here, the traits are fairly balanced. That suggests the portfolio’s behavior is driven more by its sector and stock concentration choices than by explicit factor tilts such as deep value, high dividend, or low‑volatility strategies.
Risk contribution shows how much each holding adds to the overall ups and downs, which can differ a lot from its weight. NVIDIA is 10% of the portfolio but contributes about 22.16% of total risk, more than double its size, reflecting its high volatility and growth nature. By contrast, the 20% S&P 500 ETF contributes around 17.98% of risk, slightly less than its weight. Together with the NASDAQ 100 ETF, the top three holdings account for 57.34% of portfolio risk. This means day‑to‑day movements are heavily influenced by a small group of positions, especially NVIDIA and the growth‑oriented index funds surrounding it.
The Invesco NASDAQ 100 ETF and the Schwab U.S. Large-Cap Growth ETF move almost identically, indicating very high correlation. Correlation measures how often assets move together; when two funds are tightly linked, holding both doesn’t add much diversification. In practice, this means that the growth portion of the portfolio behaves like a single, concentrated engine tied to many of the same big US growth names. During strong rallies in those companies, this can amplify gains. During pullbacks in the growth universe, both positions are likely to decline at the same time, which reduces the portfolio’s ability to offset losses through differing behavior among holdings.
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 optimization chart compares the current mix with an efficient frontier built from these same holdings. The current portfolio Sharpe ratio is 0.94, below the maximum achievable Sharpe of 1.51 and also below the minimum variance portfolio’s 0.82 at much lower risk. A Sharpe ratio measures return per unit of volatility, using a risk‑free rate as a baseline. Being about 5.88 percentage points below the frontier at its current risk level suggests the existing weights are not making the most of the available combination. In other words, rearranging the same ingredients could historically have delivered either higher return for similar risk or similar return with less overall volatility.
The overall dividend yield of the portfolio is about 1.21%, coming from a mix of higher‑ and lower‑yield holdings. Dividend‑focused funds like the Schwab U.S. Dividend Equity ETF and Vanguard High Dividend Yield ETF provide yields in the 2–3%+ range, while growth and sector funds sit closer to 0.4–1.1%. Dividends can matter because they contribute to total return and can offer a small cash flow component alongside price changes. In this setup, income plays a supporting rather than dominant role. The low‑to‑moderate yield fits with the portfolio’s growth orientation, where more of the expected return is tied to price appreciation than to regular cash distributions.
The portfolio’s total expense ratio (TER) is a low 0.11%, with most ETFs charging between 0.03% and 0.15% annually and only one fund at 0.40%. TER is the ongoing management fee baked into each fund’s price; you don’t pay it separately, but it slightly reduces returns every year. Keeping costs low is one of the few things investors can control, and this portfolio does that well. Over long periods, even a few tenths of a percent can add up when compounded, so this low‑fee structure supports more of the gross return flowing through to the investor rather than being lost to fund expenses.
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