Growth oriented US stock portfolio with strong momentum tilt and concentrated technology exposure
Report created on Aug 4, 2026Risk profile
5/7
Diversification profile
2/5
Positions
-
SP SPDR S&P 500 ETF Trust
SPY - US78462F1030 50.00% -
SP Invesco S&P 500® Momentum ETF
SPMO - US46138E3392 25.00% -
QN State Street SPDR Portfolio Nasdaq 100 ETF
QNDX - US78468R3903 25.00%
This portfolio is a simple three‑ETF mix, fully invested in US stocks. Half sits in a broad S&P 500 fund, while the other half is split equally between a momentum‑focused S&P 500 ETF and a Nasdaq‑100 ETF. Structurally, that means a core “market” base with a sizeable overlay of growth and momentum. This kind of setup matters because the broad ETF tends to behave like the overall US stock market, while the other two lean into faster‑moving, more volatile names. With only one month of history, it’s too early to say how the mix behaves over full cycles, but the design clearly prioritizes growth potential over balance across different asset types.
Growth
Over the short one‑month window available, a $1,000 investment dipped to about $986, giving a negative annualized CAGR of -12.33%. CAGR, or Compound Annual Growth Rate, is like averaging the speed of a road trip; here it just stretches a brief dip into a “per year” figure. The maximum drawdown of -7.66% was deeper than both the US and global benchmarks, which fell around -3.4%. The portfolio also underperformed both benchmarks on return. With such a short sample, these numbers mostly show how the portfolio behaved in this particular month, not a reliable long‑term pattern.
Projection
The Monte Carlo projection uses past price moves to simulate thousands of possible 15‑year paths, like running many “what if” market movies. Here, the median scenario turns $1,000 into about $2,789, with a wide typical range between roughly $1,820 and $4,298. There’s also a sizeable spread from about $994 to $7,552 in the more extreme 5%–95% range. The average simulated annual return of 8.12% looks broadly in line with long‑term stock expectations. However, because the underlying data covers only about a month, these simulations lean heavily on that short, noisy history, so they’re best read as rough illustrations of potential volatility rather than precise forecasts.
Asset classes
- Stocks 100%
All of the portfolio sits in stocks, with no bonds, cash, or alternative assets in the mix. Asset classes are broad buckets like equities, bonds, or real estate that tend to react differently to economic news. Being 100% in equities usually means larger swings in value, both up and down, compared with a mix that includes bonds or cash. That concentration can amplify growth in strong markets but also increases sensitivity to sharp pullbacks. Over only a month of data, the recent drawdown already shows how an all‑stock setup can move more than blended portfolios, even if it may benefit more when markets are rising.
Sectors
- Technology 45%
- Telecommunications 11%
- Industrials 8%
- Financials 8%
- Consumer Discretionary 8%
- Health Care 8%
- Consumer Staples 5%
- Energy 3%
- Utilities 2%
- Basic Materials 1%
- Real Estate 1%
Sector‑wise, the portfolio leans heavily into technology at around 45%, with smaller slices in areas like telecom, industrials, financials, consumer sectors, health care, and only tiny allocations to energy, utilities, materials, and real estate. Compared to a typical broad global mix, this is more tech‑centric and less evenly spread. Sector exposure matters because different parts of the economy respond differently to interest rates, regulation, and growth trends. A tech‑heavy portfolio can benefit strongly during innovation booms or falling rates but may also experience sharper drawdowns when sentiment turns against high‑growth companies, as the recent short‑term volatility hints.
Regions
- North America 99%
Geographically, about 99% of the exposure is to North America, effectively making this a US‑centric portfolio. Geography matters because markets in different regions can be driven by distinct economic cycles, currencies, and policy decisions. A more globally spread portfolio may sometimes see one region offset weakness in another. Here, outcomes are tightly tied to the US economy, US corporate earnings, and the US dollar. This alignment can be positive if US stocks continue to perform well, but it also means the portfolio will closely track the fortunes of a single country, rather than drawing much diversification from other regions’ different growth paths.
Market capitalization
- Mega-cap 46%
- Large-cap 38%
- Mid-cap 15%
- Small-cap 1%
By market capitalization, the portfolio is dominated by mega‑cap and large‑cap stocks, with 84% in those categories and only a small slice in mid‑ and tiny exposure to small caps. Market cap simply measures company size on the stock market. Larger companies tend to be more established and widely followed, while smaller ones can be more volatile and idiosyncratic. A large‑cap tilt often means performance is more closely linked to a handful of big household names. That’s consistent with the presence of well‑known giants in the look‑through data. With one month of returns, it’s early, but this structure typically leads to behavior similar to big‑company indices.
True holdings
-
NV NVIDIA Corporation 7.64%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
AA Apple Inc. 5.49%
Part of fund(s):- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
MU Micron Technology Inc 4.71%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
MS Microsoft Corporation 3.70%
Part of fund(s):- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
GO Alphabet Inc Class A 3.45%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
AV Broadcom Inc 3.16%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- SPDR S&P 500 ETF Trust
-
GO Alphabet Inc Class C 2.87%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
AM Amazon.com Inc 2.81%
Part of fund(s):- SPDR S&P 500 ETF Trust
- State Street SPDR Portfolio Nasdaq 100 ETF
-
AM Advanced Micro Devices Inc 2.05%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- State Street SPDR Portfolio Nasdaq 100 ETF
-
JN Johnson & Johnson 1.15%
Part of fund(s):- Invesco S&P 500® Momentum ETF
- Top 10 total 37.02%
Looking through the ETFs’ top holdings, a handful of big tech and growth names stand out: NVIDIA, Apple, Micron, Microsoft, Alphabet, Broadcom, Amazon, and AMD collectively form a meaningful slice. Some of these appear in more than one ETF, creating overlap and hidden concentration even though the portfolio only holds three funds. Look‑through analysis matters because owning multiple ETFs doesn’t guarantee broad diversification if they all crowd into the same leaders. Coverage here is only based on top‑10 holdings, so true overlap is likely higher. The clustering in a small group of growth‑oriented companies helps explain why the portfolio’s short‑term moves have been relatively sharp.
Factors
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.
On factor exposure, the portfolio shows very low size and high momentum, with low yield and neutral low volatility. Factors are like underlying “personality traits” of stocks, such as preferring recent winners (momentum) or smaller companies (size). A 0% size reading indicates almost no tilt toward smaller firms; this portfolio is squarely in large names. High momentum, at 75%, means a strong lean into stocks that have performed well recently. That can boost returns when trends persist but can sting when trends reverse suddenly. With only a month of performance data, these factor tilts help explain why returns moved more than the market in this brief period.
Risk contribution
-
Invesco S&P 500® Momentum ETF
Weight: 25.00% 45.3% -
State Street SPDR Portfolio Nasdaq 100 ETF
Weight: 25.00% 27.8% -
SPDR S&P 500 ETF Trust
Weight: 50.00% 26.9%
Risk contribution shows how much each holding drives the portfolio’s ups and downs, which can differ from simple weight. Here, the momentum ETF is 25% of assets but contributes about 45% of total risk, a risk‑to‑weight ratio of 1.81. The Nasdaq 100 ETF also contributes slightly more risk than its weight, while the broad S&P 500 ETF contributes just 27% of risk despite being 50% of the portfolio. This pattern suggests the momentum sleeve is the main volatility driver. Even though the portfolio is evenly split between “core” and “satellite” funds by weight, most of the recent bumpiness came from that momentum component.
Dividends
- Invesco S&P 500® Momentum ETF 0.70%
- SPDR S&P 500 ETF Trust 1.00%
- Weighted yield (per year) 0.68%
Dividend yield is modest at about 0.68% overall, with the broad S&P 500 ETF yielding around 1.0% and the momentum ETF at 0.70%. Yield is the income you get from dividends relative to price, a bit like interest from a savings account but not guaranteed. This level of income suggests the portfolio is anchored in growth‑oriented companies that tend to reinvest profits rather than paying out large dividends. Over just a month, dividends barely show up in performance, but over many years they can add a noticeable chunk to total returns. Here, though, capital gains and losses are clearly the main driver of outcomes.
Ongoing product costs
- Invesco S&P 500® Momentum ETF 0.13%
- SPDR S&P 500 ETF Trust 0.10%
- Weighted costs total (per year) 0.08%
The portfolio’s costs are impressively low. The total expense ratio (TER) across the holdings is about 0.08% per year, with the priciest ETF at 0.13%. TER is the annual fee charged by funds to cover management and operations, taken directly out of returns. Keeping fees this low supports better long‑term performance because less return is lost each year to costs. Over decades, even small fee differences compound. With only one month of data, cost impact isn’t very visible yet, but structurally this portfolio is set up efficiently on the fee side, which is a clear positive alignment with common low‑cost investing best practices.
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