This portfolio has only about 2 months of historical data, based on the youngest asset in the portfolio. Some metrics, projections, and AI insights may be less reliable and should be interpreted with caution.
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Balanced global equity portfolio with strong quality tilt and concentrated risk in a few growth names

Report created on Jun 9, 2026

Risk profile Info

4/7
Balanced
Less risk More risk

Diversification profile Info

4/5
Broadly Diversified
Less diversification More diversification

Positions

This portfolio is built mainly around diversified equity funds, with a handful of individual stocks and a modest allocation to bonds, cash-like Treasuries, and gold. The largest holding is a broad US equity ETF, followed by a global ex‑US equity fund and a short‑term Treasury ETF. A few single stocks and a semiconductor ETF take up noticeable space, giving the mix a growth and technology flavor. This structure matters because core index funds offer broad market exposure, while single names and niche funds can drive results in a more focused way. Given the very short two‑month history, it’s too early to say how this exact mix behaves over a full cycle; current observations are more like a snapshot than a long‑term pattern.

Growth Info

One or more local-currency benchmark funds are unavailable for this report.

Over the roughly two‑month window, a hypothetical $1,000 grew to about $1,296, far outpacing the global market benchmark. The portfolio’s calculated CAGR of 357% and limited max drawdown of about -3% look extremely strong on paper, but such figures over a tiny period are statistically fragile. CAGR, or compound annual growth rate, is like averaging speed over a road trip; here the “trip” is barely started, so the speedometer is noisy. A short burst of strong performance in a few holdings can dramatically inflate annualized numbers. This outperformance is interesting, but it should be seen as early noise, not evidence of a persistent long‑term edge.

Projection Info

The Monte Carlo projection uses the recent returns and volatility to simulate thousands of possible 15‑year paths, estimating a range of ending values for a $1,000 starting point. It shows a median outcome around $2,745, with most simulations landing between roughly $1,900 and $3,800. Monte Carlo is like running many alternate futures based on past behavior, but here the “past” is only two months, which is a very thin foundation. That makes these forecasts particularly fragile: if the brief strong run cools off, the long‑term averages could shift a lot. The numbers are best read as an illustration of uncertainty, not as a reliable roadmap.

Asset classes Info

  • Stocks
    81%
  • Cash
    11%
  • Bonds
    6%
  • Other
    1%

Asset‑class exposure is heavily tilted to stocks at 81%, with about 11% in cash or cash‑like instruments, 6% in bonds, and 1% in other assets like gold. This creates a primarily growth‑oriented profile with a modest stabilizing layer from bonds and near‑cash holdings. Compared with typical global blends, the equity share is firmly on the higher‑risk side, while the cash and bonds provide some cushion during short‑term swings. The presence of gold as a small slice can add a different pattern of returns, especially around macro shocks, but at 1% it won’t dominate behavior. Over two months, these roles are hard to see clearly; longer data would better show how these pieces actually interact.

Sectors Info

  • Technology
    35%
  • Cash
    11%
  • Industrials
    8%
  • Financials
    8%
  • Consumer Staples
    7%
  • Telecommunications
    5%
  • Health Care
    5%
  • Consumer Discretionary
    5%
  • Energy
    4%
  • Utilities
    3%
  • Basic Materials
    2%
  • Real Estate
    1%

This breakdown covers the equity portion of your portfolio only.

Sector‑wise, technology stands out at around 35%, clearly above what many broad global benchmarks hold. The rest is spread across industrials, financials, consumer staples, telecom, health care, consumer discretionary, energy, utilities, basic materials, real estate, and cash. A tech‑heavy tilt often means more sensitivity to innovation cycles and interest rate changes, and can deliver both strong gains and sharper pullbacks. The balanced presence of more defensive areas like consumer staples and utilities helps provide some counterweight, which is a positive sign for diversification. With only a couple of months of history, though, it’s too early to say how this sector mix will actually behave across different economic environments or stress periods.

Regions Info

  • North America
    68%
  • Cash
    11%
  • Europe Developed
    5%
  • Japan
    4%
  • No data
    3%
  • Asia Developed
    3%
  • Asia Emerging
    2%
  • Australasia
    1%

This breakdown covers the equity portion of your portfolio only.

Geographically, about 68% of the portfolio is in North America, with additional exposure to developed Europe, Japan, other developed Asia, emerging Asia, and a small slice of Australasia. That creates a clear home bias toward the US and neighboring markets, but still with meaningful global diversification. Compared with a pure global market benchmark, the US share is somewhat higher, while regions like emerging markets are relatively smaller. This can matter when different economies move out of sync, as a heavier US tilt may capture US‑led rallies more but also tie a lot of outcomes to a single currency and policy regime. Over just two months, regional return gaps are mostly noise, not durable trends.

Market capitalization Info

  • Mega-cap
    37%
  • Large-cap
    29%
  • Mid-cap
    13%
  • Small-cap
    2%
  • No data
    1%

This breakdown covers the equity portion of your portfolio only.

By market capitalization, the portfolio leans strongly toward mega‑ and large‑cap companies, which together make up roughly two‑thirds of equity exposure, with mid‑caps and a small slice of small‑caps filling in the rest. Bigger companies tend to have more diversified businesses and more analyst coverage, which can sometimes mean smoother, less volatile price moves than tiny firms. That said, large‑cap‑heavy portfolios may miss some of the more explosive upside (and downside) small‑cap names offer. This structure aligns fairly well with global equity benchmarks, which are also dominated by the largest companies. In such a short lookback, though, any apparent “stability” of large caps could be largely coincidental.

True holdings Info

  • Micron Technology Inc
    7.84%
    Part of fund(s):
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • Roundhill Memory ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
    • VanEck Semiconductor ETF
    Direct holding 7.21%
  • NVIDIA Corporation
    3.04%
    Part of fund(s):
    • JPMorgan Equity Premium Income ETF
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
    • VanEck Semiconductor ETF
    • Vanguard S&P 500 ETF
  • Advanced Micro Devices Inc
    2.53%
    Part of fund(s):
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • VanEck Semiconductor ETF
    Direct holding 1.96%
  • Costco Wholesale Corp
    2.38%
    Part of fund(s):
    • Consumer Staples Select Sector SPDR® Fund
    • Vanguard Dividend Appreciation Index Fund ETF Shares
    Direct holding 2.16%
  • Apple Inc
    1.87%
    Part of fund(s):
    • JPMorgan Equity Premium Income ETF
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
    • Vanguard Dividend Appreciation Index Fund ETF Shares
    • Vanguard S&P 500 ETF
  • Broadcom Inc
    1.63%
    Part of fund(s):
    • First Trust NASDAQ Cybersecurity ETF
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
    • VanEck Semiconductor ETF
    • Vanguard Dividend Appreciation Index Fund ETF Shares
    • Vanguard S&P 500 ETF
  • Amphenol Corporation
    1.55%
  • Microsoft Corporation
    1.42%
    Part of fund(s):
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
    • Vanguard Dividend Appreciation Index Fund ETF Shares
    • Vanguard S&P 500 ETF
  • Comfort Systems USA Inc
    1.32%
  • Amazon.com Inc
    1.09%
    Part of fund(s):
    • JPMorgan Equity Premium Income ETF
    • JPMorgan Nasdaq Equity Premium Income ETF
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
    • Vanguard S&P 500 ETF
  • Top 10 total 24.67%

This breakdown covers the equity portion of your portfolio only.

Looking through the ETFs and funds, a few individual companies stand out as bigger combined exposures. Micron is the largest, with over 7.8% total weight once direct and fund exposure are added, followed by AMD, Costco, and big global names like NVIDIA, Apple, Microsoft, Amazon, and Broadcom. Some of these show overlap across multiple vehicles, especially Micron, AMD, and Costco, which appear both directly and via ETFs. Overlap matters because it can create hidden concentration: different funds may look diversified but still hinge on the same underlying stocks. The look‑through coverage is only about 40% of the portfolio, so actual overlap is likely higher than measured here, and the short return history doesn’t yet show how this concentration plays out.

Factors Info

Value
Preference for undervalued stocks
Neutral
Data availability: 22%
Size
Exposure to smaller companies
Very low
Data availability: 83%
Momentum
Exposure to recently outperforming stocks
No data
Data availability: 0%
Quality
Preference for financially healthy companies
Very high
Data availability: 15%
Yield
Preference for dividend-paying stocks
Neutral
Data availability: 97%
Low Volatility
Preference for stable, lower-risk stocks
High
Data availability: 81%

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 a very high tilt toward quality and a very low tilt toward size, with value and yield around neutral and no usable data for momentum. Factors are like underlying “ingredients” that help explain why investments behave the way they do over time. A high quality score often reflects companies with solid balance sheets, consistent earnings, or stable profitability, which historically has sometimes helped in choppy markets. A very low size exposure means the portfolio leans away from smaller companies and toward larger ones. Combined, this paints a picture of relatively sturdy large‑cap holdings. With only two months of returns, though, the practical impact of these tilts on actual performance and downside resilience is still highly uncertain.

Risk contribution Info

  • Micron Technology Inc
    Weight: 7.21%
    32.8%
  • Vanguard S&P 500 ETF
    Weight: 22.20%
    14.5%
  • VanEck Semiconductor ETF
    Weight: 6.62%
    14.3%
  • Vanguard Total International Stock Index Fund ETF Shares
    Weight: 11.41%
    14.0%
  • Advanced Micro Devices Inc
    Weight: 1.96%
    7.0%
  • Top 5 risk contribution 82.5%

Risk contribution shows how much each position drives the portfolio’s overall ups and downs, which can differ a lot from simple weights. Micron is a clear standout: at about 7.2% of the portfolio, it contributes roughly a third of total risk, meaning its moves are amplified in the portfolio’s volatility. The semiconductor ETF and the main US index ETF together add another large slice of risk, so the top three holdings account for over 60% of total portfolio risk. A few smaller, more volatile names like AMD also punch above their weight. This pattern suggests that, despite many positions, day‑to‑day fluctuations are heavily shaped by a handful of growth‑oriented holdings, especially in the short period observed so far.

Redundant positions Info

  • SHP ETF Trust - NEOS S&P 500 High Income ETF
    Vanguard S&P 500 ETF
    High correlation
  • Vanguard Total International Stock Index Fund ETF Shares
    Vanguard FTSE Europe Index Fund ETF Shares
    High correlation

The correlation view shows some pairs moving almost identically, such as the S&P 500 ETF and the NEOS S&P 500 high‑income ETF, and the Europe ETF with the broader international stock ETF. Correlation measures how often assets move together; highly correlated holdings tend to rise and fall in sync, which can reduce the diversification benefit of holding both. In this case, overlapping exposures mean that changes in US large‑cap stocks or developed European markets may be echoed across several funds at once. Over only two months, correlations can be unstable and heavily influenced by a single short‑term market theme, so these relationships might look different over a more typical multi‑year span.

Risk vs. return

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.

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The efficient frontier chart compares the current mix with alternative weightings of the same holdings. The Sharpe ratio, a measure of return per unit of risk after accounting for a risk‑free rate, is very high across the board because of the unusually strong short‑term returns. The current portfolio sits well below the efficient frontier at its risk level, meaning that, based on this short window, other weightings could have produced better risk‑adjusted results with the same ingredients. The minimum‑variance and max‑Sharpe portfolios show lower risk for still‑strong returns in this sample. Given the tiny two‑month dataset, these optimization numbers mainly illustrate the concept rather than giving a robust guide to how different mixes might behave over the long haul.

Dividends Info

  • Amphenol Corporation 0.60%
  • Vanguard Total International Bond Index Fund ETF Shares 4.50%
  • First Trust NASDAQ Cybersecurity ETF 0.50%
  • Costco Wholesale Corp 0.60%
  • iShares MSCI Japan Value 4.70%
  • FIDELITY ADVISOR FLOATING RATE HIGH INCOME FUND FIDELITY FLOATING RATE HIGH INCOME FUND 5.40%
  • FIDELITY MEGA CAP STOCK FUND FIDELITY MEGA CAP STOCK FUND 3.60%
  • Comfort Systems USA Inc 0.10%
  • FIDELITY INTERMEDIATE BOND FUND FIDELITY INTERMEDIATE BOND FUND 3.70%
  • JPMorgan Equity Premium Income ETF 8.30%
  • JPMorgan Nasdaq Equity Premium Income ETF 10.30%
  • Kenvue Inc. 4.70%
  • Micron Technology Inc 0.10%
  • Global X U.S. Infrastructure Development ETF 0.80%
  • iShares MSCI Global Metals & Mining Producers ETF 2.40%
  • NEOS Nasdaq 100 High Income ETF 13.60%
  • Schwab U.S. Dividend Equity ETF 3.30%
  • iShares 0-3 Month Treasury Bond ETF 3.90%
  • VanEck Semiconductor ETF 0.20%
  • SHP ETF Trust - NEOS S&P 500 High Income ETF 11.80%
  • Vanguard FTSE Europe Index Fund ETF Shares 2.80%
  • Vanguard Dividend Appreciation Index Fund ETF Shares 1.50%
  • Vanguard S&P 500 ETF 1.00%
  • Vanguard Total International Stock Index Fund ETF Shares 2.70%
  • Consumer Staples Select Sector SPDR® Fund 2.60%
  • Utilities Select Sector SPDR® Fund 2.70%
  • Weighted yield (per year) 2.33%

The portfolio’s total indicated yield is about 2.33%, combining lower‑yielding growth stocks and funds with several high‑income strategies and bond funds. Some holdings, like the NEOS Nasdaq 100 High Income ETF and other option‑based income ETFs, show double‑digit yields, while many core equities and semiconductors pay very little or nothing. Dividends can be an important component of total return, especially when they’re reinvested, but headline yields can also be volatile and influenced by special distributions or option strategies. Over just a couple of months, the realized income stream may not match these indicated yields, so they should be viewed as rough snapshots rather than fixed promises of future cash flow.

Ongoing product costs Info

  • Vanguard Total International Bond Index Fund ETF Shares 0.07%
  • First Trust NASDAQ Cybersecurity ETF 0.59%
  • Global X Cloud Computing 0.68%
  • iShares MSCI Japan Value 0.15%
  • FIDELITY ADVISOR FLOATING RATE HIGH INCOME FUND FIDELITY FLOATING RATE HIGH INCOME FUND 0.73%
  • FIDELITY MEGA CAP STOCK FUND FIDELITY MEGA CAP STOCK FUND 0.58%
  • FIDELITY INTERMEDIATE BOND FUND FIDELITY INTERMEDIATE BOND FUND 0.45%
  • SPDR® Gold Shares 0.40%
  • JPMorgan Equity Premium Income ETF 0.35%
  • JPMorgan Nasdaq Equity Premium Income ETF 0.35%
  • Global X U.S. Infrastructure Development ETF 0.47%
  • iShares MSCI Global Metals & Mining Producers ETF 0.39%
  • NEOS Nasdaq 100 High Income ETF 0.68%
  • Schwab U.S. Dividend Equity ETF 0.06%
  • iShares 0-3 Month Treasury Bond ETF 0.07%
  • VanEck Semiconductor ETF 0.35%
  • SHP ETF Trust - NEOS S&P 500 High Income ETF 0.68%
  • Vanguard FTSE Europe Index Fund ETF Shares 0.06%
  • Vanguard Dividend Appreciation Index Fund ETF Shares 0.06%
  • Vanguard S&P 500 ETF 0.03%
  • Vanguard Total International Stock Index Fund ETF Shares 0.05%
  • Consumer Staples Select Sector SPDR® Fund 0.09%
  • Utilities Select Sector SPDR® Fund 0.09%
  • Weighted costs total (per year) 0.14%

The weighted average cost, or Total Expense Ratio (TER), is about 0.14%, which is impressively low for a portfolio with this many moving parts. Most core index funds here charge single‑digit basis points, while a handful of specialized or high‑income funds sit closer to 0.5–0.7%. Costs matter because they come off returns every year, and even small differences can compound significantly over long periods. In this case, the overall fee level is closer to what you’d expect from a very lean index‑based setup than from a complex multi‑fund mix. With such a short return history, fees haven’t had much time to show their compounding effect yet, but the low TER sets a strong foundation for long‑term efficiency.

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