This portfolio is built almost entirely from diversified stock funds, with a very small slice in short‑term US Treasuries. The biggest pieces are broad international stocks and US large‑cap growth, followed by US mid‑cap growth and value, then US and international large‑cap value funds, plus a small‑cap growth fund. This structure creates a clear growth tilt while still spreading holdings across different fund families and styles. Using pooled vehicles like ETFs and mutual funds means each line item actually holds many underlying companies. That helps reduce single‑stock risk, though the overall mix still behaves mainly like a stock portfolio with only minimal bond cushioning.
From 2016 to 2026, $1,000 in this portfolio grew to about $3,458, a compound annual growth rate (CAGR) of 13.3%. CAGR is like your average speed on a long road trip, smoothing out bumps along the way. The portfolio’s return trailed the US market benchmark, which returned 15.39% a year, but slightly beat the global market at 12.67%. The max drawdown, or worst peak‑to‑trough drop, was about ‑35%, very similar to broad markets during the 2020 shock. That drop recovered in roughly five months, showing resilience but also confirming that this behaves like a risk‑on equity portfolio rather than a defensive one.
The Monte Carlo projection uses the historical return and volatility of this mix to simulate many possible 15‑year paths for $1,000. Think of it as running 1,000 alternate universes based on past patterns, then seeing where you most often end up. The median outcome is around $2,856, with a “likely” middle band from about $1,798 to $4,298. Extreme but still plausible outcomes range roughly from flat to more than seven times the starting value. The overall average simulated return is 8.16% a year. As always, these are modelled numbers, not promises; markets rarely repeat the past exactly, and unusual future events could push real outcomes outside the illustrated ranges.
Asset allocation is overwhelmingly in stocks at 99%, with just 1% in bonds via a short‑term Treasury ETF. Asset classes are the broad buckets like stocks and bonds that drive much of a portfolio’s behaviour. Stock‑heavy mixes usually offer higher long‑term growth potential but larger and more frequent swings in value, especially during market stress. The tiny bond slice here offers only a small buffer against stock downturns, but short‑term Treasuries can still help with liquidity and slightly reduce volatility. Compared with many blended portfolios that hold larger bond stakes, this one clearly prioritises equity growth over income stability at the total portfolio level.
This breakdown covers the equity portion of your portfolio only.
Sector exposure is fairly broad, with technology at about 25% and financials and industrials together accounting for another 32%. Health care, consumer discretionary, telecom, and other sectors round out the mix with smaller but meaningful weights. Sector diversification matters because different parts of the economy respond differently to interest rates, inflation, and growth cycles. For example, tech‑heavy allocations can be more sensitive to rate moves, while financials and industrials often track economic activity more closely. Here, technology is an important driver but not overwhelmingly dominant, which helps spread risk across multiple economic themes rather than hinging on a single sector narrative.
This breakdown covers the equity portion of your portfolio only.
Geographically, around two‑thirds of the equity exposure is in North America, with the rest spread across developed Europe, Japan, developed Asia, emerging Asia, and smaller allocations to Australasia, Latin America, and Africa/Middle East. Geography affects exposure to different currencies, political systems, and economic cycles. A roughly 67% North America weight is a noticeable home‑region tilt relative to global indices, but still leaves meaningful room for non‑US growth drivers. The presence of both developed and emerging markets adds another layer of diversification, as these regions can move differently over time. This allocation is well‑balanced and aligns closely with global standards for broad international diversification.
This breakdown covers the equity portion of your portfolio only.
The portfolio is diversified across company sizes, with about 32% in mega‑caps, 25% in large‑caps, 21% in mid‑caps, and 18% in small‑caps, plus a small micro‑cap slice. Market capitalisation, or “market cap,” simply measures a company’s size by its share price times shares outstanding. Large and mega‑cap companies tend to be more stable and widely followed, while smaller companies can be more volatile but offer different growth dynamics. This spread across the size spectrum means the portfolio doesn’t rely solely on the biggest names in the market. Instead, it blends the steadier behaviour of large firms with the potentially punchier moves of mid‑ and small‑caps.
This breakdown covers the equity portion of your portfolio only.
Looking through the ETFs’ top holdings, a handful of large global companies appear multiple times, including NVIDIA, Apple, Microsoft, Amazon, and Alphabet. These repeated names indicate “overlap,” where the same stock is owned through several funds. Overlap can create hidden concentration: even if no single fund is massive, shared holdings can make certain companies bigger drivers of returns. Here, the combined exposure to each of these giants is still only a few percent of the portfolio, so concentration risk at the single‑company level is moderate. Coverage is limited to ETF top‑10s, so true overlap is likely higher, but the available data still points to diversified underlying 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 is broadly balanced, with most factors hovering near the neutral band. Factors are characteristics like value, size, or momentum that research has linked to long‑term return patterns. This portfolio shows a mild tilt toward the size factor, meaning somewhat greater exposure to smaller companies than a pure market‑cap‑weighted global index. In practice, that can make returns more sensitive to how mid‑ and small‑cap segments perform relative to large‑caps, especially during economic shifts. The neutral readings on value, momentum, quality, yield, and low volatility suggest no strong bet on any single style, which tends to keep behaviour closer to the broad market’s overall pattern.
Risk contribution shows how much each holding drives the portfolio’s overall ups and downs, which can differ from its weight. For example, the US large‑cap growth ETF is about 21% of the portfolio but contributes around 24% of total risk, reflecting its role as a relatively volatile, growth‑oriented core. The international equity ETF, by contrast, has a similar weight but a slightly lower share of risk, partly thanks to diversification benefits. The top three holdings together contribute nearly 60% of portfolio risk, so their behaviour heavily shapes overall volatility. This is typical for a concentrated core‑satellite structure where a few broad funds anchor most of the risk.
Asset correlation describes how often investments move in the same direction at the same time. Highly correlated assets may all rise and fall together, limiting diversification when markets get rough. Here, the US large‑cap growth ETF and the SPDR Portfolio S&P 500 Growth ETF move almost identically, which makes sense because they both target similar growth‑oriented large companies. In practice, this means the tiny allocation to the SPDR fund is effectively doubling down on the same pattern already present in the larger Schwab growth ETF. While the weight is very small, the correlation data underlines that changes in one of these positions will closely mirror changes in the other.
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 chart compares this portfolio with two reference mixes built only from your existing holdings: the “optimal” portfolio with the highest Sharpe ratio and the minimum variance portfolio with the lowest risk. The Sharpe ratio measures return per unit of risk, after accounting for a risk‑free rate like short‑term Treasuries. Your current portfolio’s Sharpe is 0.55, below the optimal 0.93 and also below the minimum‑variance portfolio’s 0.62. It sits about 3.68 percentage points under the efficient frontier at its current risk level, meaning a different weighting of the same funds could historically have delivered better risk‑adjusted returns without adding new positions.
The total indicated dividend yield is about 4.55%, which is relatively high for a growth‑oriented equity mix. Dividend yield measures yearly cash payouts as a percentage of the portfolio’s value. Most of the low‑cost ETFs show modest yields, consistent with broad equity exposure, while certain active mutual funds display very high reported yields that may be influenced by special distributions or data quirks. In practice, dividends can be an important component of total return, especially when reinvested over time. It’s worth remembering that yields can change year to year and that income is only one part of the overall growth and risk profile.
The weighted average cost (TER) of the portfolio is about 0.23% per year. TER, or total expense ratio, is the annual fee charged by funds to cover management and operations, expressed as a percentage of assets. The core ETFs are impressively cheap, ranging from 0.03% to 0.15%, which supports better long‑term compounding. A few active mutual funds carry higher TERs above 1%, but their relatively modest weights keep the overall fee level low. Over long horizons, a 0.23% cost base is quite competitive and helps more of the portfolio’s gross return stay in the investor’s pocket rather than being lost to ongoing expenses.
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