This portfolio is very simple: five individual US stocks at equal 20% weights, with no funds or bonds. That means every holding has a big say in overall results, and there’s no automatic smoothing from broad index funds. Simplicity can make it easier to understand what’s driving performance, but it also means less diversification than a portfolio spread across dozens or hundreds of companies. With equal weights, changes in any single stock show up clearly in the total value. The structure lines up with a focused, stock‑picking style rather than a broad market approach, and the low diversification score reflects this concentrated setup.
From 2016 to April 2026, a hypothetical $1,000 in this portfolio grew to about $10,260. That translates to a compound annual growth rate (CAGR) of 26.33%, which is very high compared with both the US market (15.25%) and global market (12.66%). CAGR is like your average speed over a long road trip, smoothing out bumps along the way. The max drawdown of -22.05% was noticeably smaller than the roughly -34% drawdowns of the benchmarks, meaning the worst peak‑to‑trough fall was milder. Returns were also concentrated: just 64 days made up 90% of gains, showing how a handful of strong days can dominate long‑term results.
The Monte Carlo projection looks ahead 15 years by simulating many possible paths using historical returns and volatility as a guide. Think of it as rolling the dice 1,000 times on how markets could behave, not predicting a single future. The median outcome turns $1,000 into about $2,712, with a “middle” range from roughly $1,805 to $4,297. There’s a wide possible band from around $978 to $7,761, highlighting how uncertain long‑term outcomes can be. The average simulated annual return of 8.11% is much lower than the historical 26%+, underlining that past outperformance is not assumed to continue indefinitely.
All of this portfolio is in stocks, with 0% in bonds, cash, or alternatives. Stocks are ownership stakes in companies and tend to have higher long‑term return potential but also larger ups and downs. A 100% stock allocation usually means more sensitivity to market cycles and economic news, since there’s no bond or cash portion to buffer volatility. Compared with broad balanced portfolios that mix several asset classes, this one is firmly at the growth‑oriented end of the spectrum. The growth‑risk classification and 5/7 risk score align with this all‑equity setup, where the trade‑off is more potential growth in exchange for bigger swings.
Sector exposure is evenly split: 20% each in industrials, health care, technology, telecommunications, and consumer staples. This creates a tidy sector balance within the stock portion, which is a positive sign, because portfolio risk isn’t being driven by one industry alone. Compared with common benchmarks that are often heavily tilted to technology or financials, this spread looks more even across different parts of the economy. Sector balance helps when one industry hits a rough patch, as others may behave differently. Here, diversification comes more from crossing business types than from owning a large number of companies.
Geographically, the portfolio is 100% in North America, and more specifically US‑listed companies. That means all company earnings, regulation, currency exposure, and political risk are tied to a single country. Compared with global benchmarks such as MSCI ACWI, which spread across many regions, this is a clear home‑country concentration. A single‑country focus can benefit from strong local market performance, as US stocks have shown over the last decade, but it also means less protection if that market lags others. The global market includes economies that may perform differently at various times; here, that cross‑country diversification is intentionally not present.
Every holding is a mega‑cap stock, meaning very large companies by market value. Mega‑caps often have more diversified businesses, stronger balance sheets, and better access to capital than smaller firms. They can sometimes be more stable and liquid, making them easier to trade. At the same time, limiting exposure to only the largest companies means missing smaller and mid‑sized firms, which historically have shown different return and risk patterns. Many broad indices naturally blend large, mid, and small companies. This portfolio instead leans fully into the mega‑cap segment, creating a clear size profile that matches its “very low” size factor exposure.
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 highlights how the portfolio leans toward certain characteristics that research has linked to returns. The most notable tilts are very high quality (81%) and high momentum (74%), alongside high low‑volatility exposure (66%) and very low size (3%). Quality refers to companies with strong profitability, stable earnings, and solid balance sheets; such stocks often hold up better in downturns. Momentum captures stocks that have been trending strongly, which can boost returns when trends continue but may hurt during sharp reversals. The very low size score reflects the pure mega‑cap focus. Overall, this combination lines up with historically resilient, established companies that have recently performed well.
Risk contribution shows how much each stock adds to the portfolio’s overall ups and downs, which can differ from its simple weight. Here, the three largest risk contributors—Caterpillar, Microsoft, and Eli Lilly—each weigh 20% but together account for about two‑thirds of total risk. Their risk/weight ratios slightly above 1 indicate they are marginally more volatile or less correlated diversifiers than the others. Walmart’s ratio of 0.73 suggests it dampens risk relative to its size. This pattern illustrates how equal dollar weights don’t translate into equal risk: a few holdings naturally dominate the volatility picture even in an evenly split portfolio.
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 analysis compares the current mix with the best possible combinations of the same five stocks. The portfolio’s Sharpe ratio of 1.26—where Sharpe measures return earned per unit of risk above the risk‑free rate—is already high. The max‑Sharpe version reaches 1.47 with slightly more return and risk, while the minimum‑variance mix delivers lower risk and still a solid Sharpe of 1.39. The note that this portfolio sits on or very near the frontier means the way the five stocks are currently weighted is already an efficient trade‑off for its risk level, based purely on historical relationships among these holdings.
Dividend yield for the portfolio is relatively modest at about 0.92% overall, with individual stock yields ranging from 0.50% to 1.90%. Dividends are the cash payments companies make to shareholders, and they can be an important part of total return over time, especially when reinvested. Here, most of the historical growth has come from price appreciation rather than income. This pattern is common in portfolios tilted toward quality and growth‑oriented mega‑caps, where companies may reinvest more of their earnings back into the business instead of paying them out. The low yield fits with a focus on capital growth over current cash flow.
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