High income US stock portfolio with strong value tilt and efficient risk return profile
Report created on Apr 12, 2026Risk profile
- Secure Speculative
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.
Diversification profile
- Focused Diversified
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.
Positions
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SP SHP ETF Trust - NEOS S&P 500 High Income ETF
SPYI - US78433H3030 87.90% -
SC Schwab U.S. Dividend Equity ETF
SCHD - US8085247976 7.20% -
QQ NEOS Nasdaq 100 High Income ETF
QQQI - US78433H6751 4.90%
The portfolio is very focused: almost 88% sits in a single S&P 500 high‑income ETF, with smaller allocations to a U.S. dividend ETF and a Nasdaq 100 high‑income ETF. That means most of the behavior is driven by one core holding, supported by two income‑oriented satellites. Structurally, this is a simple, easy‑to‑manage setup, which can be appealing if someone prefers not to juggle many positions. The flip side is that diversification across strategies is limited, so the experience will closely track how that main ETF performs. A general takeaway is that simple can work very well, as long as the concentration is intentional and understood.
Growth
Over the period shown, $1,000 grew to about $1,358, a compound annual growth rate (CAGR) of 15.05%. CAGR is like average speed on a road trip: it smooths out ups and downs into one yearly growth number. This trailed both the U.S. and global market benchmarks, which returned 17.55% and 18.60% respectively, but with a slightly smaller maximum drawdown than the U.S. market. The worst drop for this portfolio was about -16.4%, recovering in roughly three months. That mix of solid growth with controlled downside is consistent with a balanced, income‑tilted equity approach, even though it has lagged broad indices in this specific time window.
Projection
The Monte Carlo projection uses many random simulations based on historical return and volatility patterns to estimate a range of future outcomes. It’s like running 1,000 alternate histories to see how often things work out well. Here, the median 15‑year outcome for $1,000 is about $2,790, with most paths landing between roughly $1,820 and $4,416. About three‑quarters of simulations end positive, and the average simulated annual return is 8.21%. This is quite respectable for an all‑equity, income‑heavy profile. Still, these projections lean on past data; markets evolve, and actual future results can fall outside even the 5–95% range, so they’re more a planning tool than a promise.
Asset classes
- Stocks 99%
- Other 1%
Asset‑class exposure is extremely straightforward: about 99% in stocks and a small “other” slice. There’s essentially no ballast from bonds or cash‑like assets. Equities historically offer higher growth, but they also drive larger swings in account value, especially over shorter periods. For someone seeking long‑term growth and willing to ride through volatility, an equity‑heavy mix can make sense. For someone who cares more about stability or has near‑term spending needs, a more mixed stock‑bond blend is usually more comfortable. The key implication is that all the risk and reward here comes from the stock market, with little cushion during equity downturns.
Sectors
- Technology 33%
- Financials 11%
- Telecommunications 11%
- Health Care 10%
- Consumer Discretionary 10%
- Industrials 8%
- Consumer Staples 6%
- Energy 5%
- Utilities 2%
- Real Estate 2%
- Basic Materials 2%
Sector‑wise, the portfolio leans heavily into technology at 33%, with meaningful exposure to financials, telecom, health care, consumer, and industrial names, plus smaller slices in energy, utilities, real estate, and materials. This tech weight is somewhat higher than a typical broad U.S. equity benchmark, reflecting the influence of mega‑cap growth companies and the Nasdaq‑linked sleeve. Tech‑heavy mixes often do very well in growthy, low‑rate environments but can be more sensitive when interest rates rise or when markets rotate into more defensive areas. On the positive side, the remaining sectors are reasonably spread out, which helps avoid being completely dependent on a single industry cycle.
Regions
- North America 99%
Geographically, exposure is almost entirely to North America, at about 99%. That keeps things simple from a currency and tax perspective for a U.S.‑based investor, and has historically benefited from the strong run of U.S. stocks. However, it also means the portfolio is heavily tied to one economy, one political system, and one currency. Global benchmarks usually allocate a much larger share to non‑U.S. markets. While concentration can work for long stretches, it does leave less room to benefit if other regions outperform or if U.S. equities face a multi‑year period of relative weakness. It’s a clear, intentional home‑bias trade‑off.
Market capitalization
- Mega-cap 43%
- Large-cap 38%
- Mid-cap 18%
- Small-cap 1%
Market‑cap exposure is dominated by mega‑caps (43%) and large‑caps (38%), with modest mid‑cap and tiny small‑cap exposure. Large and mega‑cap companies tend to be more established, with diversified revenues and deeper liquidity, which often makes them less volatile than smaller firms. That aligns well with an income‑focused, low‑volatility tilt. The trade‑off is less participation in potential small‑cap growth spurts, which at times can deliver strong returns but with bumpier rides. Overall, this size mix is quite close to mainstream U.S. equity benchmarks, which is a positive sign for broad diversification by company size, even if the factor tilts push behavior in a more defensive direction.
True holdings
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NV NVIDIA Corporation 7.08%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
AA Apple Inc 6.28%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
MS Microsoft Corporation 4.56%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
AM Amazon.com Inc 3.43%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
GO Alphabet Inc Class A 2.87%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
AV Broadcom Inc 2.46%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
GO Alphabet Inc Class C 2.31%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
ME Meta Platforms Inc. 2.14%
Part of fund(s):- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
TS Tesla Inc 1.86%
Part of fund(s):- LS 1x Tesla Tracker ETP Securities GBP
- NEOS Nasdaq 100 High Income ETF
- SHP ETF Trust - NEOS S&P 500 High Income ETF
-
BR Berkshire Hathaway Inc 1.38%
Part of fund(s):- SHP ETF Trust - NEOS S&P 500 High Income ETF
- Top 10 total 34.36%
Looking through the ETFs, the biggest underlying names are familiar mega‑cap U.S. giants like NVIDIA, Apple, Microsoft, Amazon, Alphabet, Broadcom, Meta, Tesla, and Berkshire Hathaway. Several of these appear across multiple funds, creating hidden overlap; for example, Apple or Microsoft can be owned indirectly through both the S&P 500 high‑income and Nasdaq 100 high‑income ETFs. This kind of repetition increases concentration in those companies more than the simple ETF weightings might suggest. Since only top‑10 holdings are captured here, the real overlap is likely somewhat higher. The main implication is that portfolio outcomes will be strongly tied to how these few mega‑caps perform over time.
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.
Factor exposure shows very high tilts to value, yield, and low volatility, with a very low size factor score. Factors are like underlying “personality traits” of stocks — value favors cheaper‑priced names, yield focuses on income, low volatility seeks smoother price paths, and size often relates to smaller companies. Here, the strong value and yield tilts fit the high‑income design: targeting stocks that pay more and are priced more defensively. The very high low‑volatility tilt suggests an emphasis on steadier names, which can help during market stress but may lag in roaring bull markets. The very low size score reflects the preference for larger, more established companies over smaller, higher‑beta names.
Risk contribution
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SHP ETF Trust - NEOS S&P 500 High Income ETF
Weight: 87.90% 88.9% -
NEOS Nasdaq 100 High Income ETF
Weight: 4.90% 6.1% -
Schwab U.S. Dividend Equity ETF
Weight: 7.20% 5.1%
Risk contribution shows how much each holding drives the portfolio’s ups and downs, which can differ from its weight. The main S&P 500 high‑income ETF is about 88% of the portfolio but contributes almost 89% of total risk — very aligned. The Nasdaq 100 high‑income ETF, while under 5% of the weight, contributes a bit over 6% of risk, showing it’s a bit punchier than its size suggests. The Schwab dividend ETF contributes less risk than its weight, acting as a stabilizer. With the top three holdings responsible for virtually all risk, any change to that core ETF’s behavior will dominate, so position sizing decisions have a big impact on the total risk profile.
Redundant positions
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High correlationSHP ETF Trust - NEOS S&P 500 High Income ETFNEOS Nasdaq 100 High Income ETF
Correlation measures how closely different holdings move together — 1.0 means they move almost in lockstep. Here, the Nasdaq 100 high‑income ETF and the S&P 500 high‑income ETF are flagged as moving almost identically. That’s not surprising, since both are U.S., large‑cap, growth‑tilted and income‑oriented. The practical implication is that adding more of one doesn’t dramatically change diversification; they will likely rise and fall at similar times. This is not inherently a problem, but it does limit the ability of one holding to offset the other in a downturn. True diversification usually comes from assets that behave differently under stress, not just from more tickers.
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.
The risk‑return chart shows your current mix sitting right on or very near the efficient frontier. The efficient frontier is the curve of best possible returns for each risk level, using only the holdings you already own, just reweighted. The current Sharpe ratio — a measure of return per unit of risk — is 0.82, while the optimal and minimum‑variance mixes reach about 1.06 and 1.05. That means there is a slightly better risk‑adjusted trade‑off possible with different weights, but you’re already in a very efficient zone. The allocation is doing a good job of converting volatility into return given the chosen building blocks.
Dividends
- NEOS Nasdaq 100 High Income ETF 14.40%
- Schwab U.S. Dividend Equity ETF 3.40%
- SHP ETF Trust - NEOS S&P 500 High Income ETF 12.10%
- Weighted yield (per year) 11.59%
Income is a major highlight here. The overall indicated yield is about 11.6%, driven by the high‑income ETFs (around 12–14%) plus a more moderate 3.4% from the Schwab dividend ETF. Yield is the annual cash payout as a percentage of the investment, and at this level it can be very attractive for funding spending needs. It’s worth remembering that such high yields often come from option strategies or focusing on higher‑yielding stocks, which can affect price behavior and tax treatment. Distributions may also fluctuate year to year. Still, for an investor prioritizing current cash flow over maximum capital growth, this income profile is a real strength.
Ongoing product costs
- NEOS Nasdaq 100 High Income ETF 0.68%
- Schwab U.S. Dividend Equity ETF 0.06%
- SHP ETF Trust - NEOS S&P 500 High Income ETF 0.68%
- Weighted costs total (per year) 0.64%
The weighted total expense ratio (TER) is about 0.64%. TER is the annual fee charged by funds as a percentage of the amount invested, quietly deducted inside the fund. The Schwab dividend ETF is extremely low‑cost at 0.06%, while the NEOS high‑income funds are relatively expensive at 0.68%, which is typical for more complex, options‑based strategies. Over long periods, even small fee differences compound, so keeping costs reasonable is important. That said, for specialized high‑income approaches, paying somewhat higher fees can be acceptable if the structure genuinely delivers the desired income profile and after‑fee, after‑tax results remain competitive.
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