This portfolio has only about 4 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.

Income focused portfolio with high yield tilts and short but promising recent performance history

Report created on May 5, 2026

Risk profile Info

2/7
Conservative
Less risk More risk

Diversification profile Info

4/5
Broadly Diversified
Less diversification More diversification

Positions

This portfolio is built around listed funds and a few individual stocks, with no single position above 18%. The largest holding is an income-focused Nasdaq 100 ETF, followed by an S&P 500 high-income ETF and an MLP and energy infrastructure ETF. Together, the top three positions account for roughly 39% of assets, while the rest is spread across closed-end funds, preferreds, and equity-income ETFs. This structure creates a clear tilt toward income-oriented strategies rather than plain index trackers. With only about four months of data, it’s hard to label long-term behavior, but the current mix suggests a focus on cash flow and distributions, using diversified funds rather than concentrated single-stock bets.

Growth Info

Over the roughly four-month sample, a hypothetical $1,000 grew to about $1,107, which translates into a 32.11% annualized return. That’s ahead of both the US market and global market benchmarks over the same window, with shallower drawdowns: the portfolio’s maximum drop was about -5.6%, versus -8.9% and -9.7% for the benchmarks. CAGR (compound annual growth rate) is like your average “speed” over the trip; here it looks excellent, but on a very short road. The fact that 90% of returns came from only eight days also shows how lumpy short-term performance can be. With just four months of history, these numbers are more a snapshot than a reliable long-term pattern.

Projection Info

The Monte Carlo projection uses the short recent history to simulate many possible 15‑year paths for a $1,000 investment. It’s like running 1,000 alternate timelines where returns vary randomly based on past volatility and average gains. The median outcome lands around $2,324, with a wide “likely” band from roughly $1,693 to $3,308, and very broad extremes. The overall simulated annual return is 6.53%, and about 70% of simulations end positive. Because this engine feeds on historical data, using only four months means the model is working with a thin sample. That makes these ranges more illustrative than predictive, especially for a portfolio full of specialized income strategies.

Asset classes Info

  • Stocks
    61%
  • No data
    20%
  • Bonds
    9%
  • Not classified
    5%
  • Other
    5%

On an asset-class level, about 61% of the portfolio is classified as stocks, 9% as bonds, and the rest spread across “other,” “not classified,” and “no data.” That leaves a modest but meaningful fixed-income slice and a majority in equity-like risk, even though many holdings are income-focused. Compared with broad equity benchmarks, this is more mixed, but still clearly growth-and-income rather than bond-heavy. The sizable “no data” and “not classified” buckets likely reflect the complexity of some structures, and the inability of the data provider to label them cleanly. Since this information is missing, it’s safer to treat the asset-class breakdown as directionally helpful but not fully comprehensive.

Sectors Info

  • Financials
    21%
  • Technology
    16%
  • Industrials
    6%
  • Energy
    5%
  • Telecommunications
    5%
  • Consumer Discretionary
    4%
  • Health Care
    3%
  • Consumer Staples
    2%
  • Utilities
    1%
  • Basic Materials
    1%

This breakdown covers the equity portion of your portfolio only.

Sector data shows the biggest exposure in financials at 21%, followed by technology at 16%, then smaller slices in industrials, energy, telecoms, and consumer areas. That financials tilt makes sense for a portfolio heavy in income funds, preferreds, and lending-related vehicles, as these often sit inside the broader financial sector. Compared with broad equity benchmarks, this looks more financials-heavy and somewhat more income-oriented, while still keeping notable exposure to growth-linked areas through technology and consumer names. Income-oriented financials can be sensitive to interest rates and credit conditions, while tech exposure ties part of the portfolio to innovation and growth cycles. This mix provides multiple economic drivers rather than relying on a single industry.

Regions Info

  • North America
    72%
  • Europe Developed
    3%

This breakdown covers the equity portion of your portfolio only.

Geographically, about 72% of exposure is in North America, with only roughly 3% tagged to developed Europe and the rest uncategorized. That means the portfolio is mainly tied to one region’s companies, currencies, and economic cycle, closer to a US-centric stance than a fully global market-weighted mix. Many global indices spread more across Europe and Asia, so this leans more heavily on North American businesses. A regional tilt like this can be beneficial when that area is performing strongly, but it also means portfolio outcomes will be closely linked to North American market behavior. With a lot of positions in US-listed income funds, this home-region concentration is consistent with the overall design.

Market capitalization Info

  • Small-cap
    20%
  • Mega-cap
    19%
  • Large-cap
    13%
  • Mid-cap
    9%
  • Micro-cap
    1%

This breakdown covers the equity portion of your portfolio only.

By market capitalization, the portfolio holds a broad mix: around 19% in mega-caps, 13% in large-caps, 9% in mid-caps, 20% in small-caps, and a small 1% in micro-caps. That gives exposure from global giants to more niche companies, with a relatively meaningful slice in smaller firms compared with some large-cap-focused benchmarks. Smaller companies tend to be more volatile but can behave differently from the biggest index names, helping diversification. The mega-cap share also anchors part of the portfolio in highly liquid, widely followed companies, often accessed through major index-based funds. Overall, this spread suggests a blend of stability from large firms and extra risk-and-return potential from smaller ones, rather than an all large-cap approach.

True holdings Info

  • Trinity Capital Inc
    7.07%
  • BlackRock Capital Allocation Trust
    7.03%
  • SPDR S&P 500 ETF Trust
    7.01%
    Part of fund(s):
    • TappAlpha SPY Growth & Daily Income ETF
  • Pimco Dynamic Income Opportunities Fund
    4.95%
  • NVIDIA Corporation
    2.40%
    Part of fund(s):
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
  • Apple Inc
    1.99%
    Part of fund(s):
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
  • Microsoft Corporation
    1.53%
    Part of fund(s):
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
  • Amazon.com Inc
    1.39%
    Part of fund(s):
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
  • Alphabet Inc Class A
    1.14%
    Part of fund(s):
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
  • Broadcom Inc
    1.01%
    Part of fund(s):
    • NEOS Nasdaq 100 High Income ETF
    • SHP ETF Trust - NEOS S&P 500 High Income ETF
  • Top 10 total 35.52%

This breakdown covers the equity portion of your portfolio only.

Looking through the funds, coverage of underlying holdings is about 46% of the portfolio, and only ETF top-10 positions are captured, so overlap is definitely understated. Within that visible slice, there is a clear cluster in large US growth names: NVIDIA, Apple, Microsoft, Amazon, Alphabet, and Broadcom all appear via ETFs. SPDR S&P 500 ETF Trust shows up as a 7% look-through exposure, but that is itself a diversified basket. Trinity Capital and BlackRock Capital Allocation Trust stand out as direct holdings with no additional ETF overlap, so their risk is more “pure.” While there is some concentration in big tech and index exposure, the partial data suggests overlap exists but is not extreme in the covered portion.

Factors Info

Value
Preference for undervalued stocks
High
Data availability: 31%
Size
Exposure to smaller companies
Low
Data availability: 65%
Momentum
Exposure to recently outperforming stocks
Neutral
Data availability: 26%
Quality
Preference for financially healthy companies
Very high
Data availability: 7%
Yield
Preference for dividend-paying stocks
High
Data availability: 100%
Low Volatility
Preference for stable, lower-risk stocks
High
Data availability: 28%

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 a very high tilt to quality at 87%, and high tilts to yield and low volatility at 79% each, with a high value tilt at 62%. Factor exposure is basically how much the portfolio leans into certain characteristics that research has linked to returns over time. Here, the profile suggests a focus on financially stronger companies or funds, with above-average income and somewhat smoother price movements, rather than aggressive growth or speculative themes. The lower size score (31%) means the factor model sees an overall lean away from the smallest stocks, despite some small-cap exposure in the market-cap breakdown. Because the history is short, these factor readings are best viewed as a snapshot of the current mix, not guaranteed behavior.

Risk contribution Info

  • NEOS Nasdaq 100 High Income ETF
    Weight: 17.74%
    24.4%
  • SHP ETF Trust - NEOS S&P 500 High Income ETF
    Weight: 10.96%
    12.1%
  • Trinity Capital Inc
    Weight: 7.07%
    9.7%
  • TappAlpha SPY Growth & Daily Income ETF
    Weight: 7.04%
    8.9%
  • BlackRock Capital Allocation Trust
    Weight: 7.03%
    7.4%
  • Top 5 risk contribution 62.4%

Risk contribution looks at how much each holding adds to overall volatility, which can differ a lot from simple weight. The largest high-income Nasdaq ETF is about 17.7% of the portfolio but contributes roughly 24.4% of total risk, making it the main driver of ups and downs. The S&P 500 high-income ETF and Trinity Capital also contribute more risk than their weights, while the BlackRock Capital Allocation Trust is closer to “risk in line with weight.” The top three holdings together account for about 39% of assets but over 46% of risk. That pattern is common in concentrated income strategies: a few core positions dominate day-to-day movement even when others are meaningfully sized on paper.

Redundant positions Info

  • SHP ETF Trust - NEOS S&P 500 High Income ETF
    TappAlpha SPY Growth & Daily Income ETF
    NEOS Nasdaq 100 High Income ETF
    High correlation

The correlation data highlights a few pairs that have moved almost in lockstep over this short period: the two NEOS high-income ETFs, and the S&P 500 high-income ETF with the TappAlpha SPY-based income ETF. Correlation is just a measure of how similarly two holdings move; near-1.0 means they tend to go up and down together. When funds are based on similar underlying indices and use comparable income strategies, high correlation is expected. In practice, this means those positions behave more like a cluster than completely separate bets. During a market pullback, they may all move in the same direction at roughly the same time, which can reduce the diversification benefit they provide relative to each other.

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 compares the current portfolio with the “efficient frontier” built from the same holdings. The efficient frontier represents the best expected return for each risk level using only different weightings. The current portfolio’s Sharpe ratio (2.48) is below both the maximum Sharpe portfolio (6.17) and the minimum variance option (3.44), and it sits about 32 percentage points below the frontier at its current risk. Sharpe ratio measures return per unit of volatility, like miles per gallon for risk. This gap suggests that, based on the recent short history, an alternative mix of the same holdings could have delivered better risk-adjusted performance. With only four months of data, though, these optimization numbers should be treated cautiously.

Dividends Info

  • Aberdeen Standard Global Infrastructure Income Fund 10.70%
  • BlackRock Capital Allocation Trust 21.00%
  • PIMCO Dynamic Income Fund 15.10%
  • Pimco Dynamic Income Opportunities Fund 11.50%
  • Virtus InfraCap U.S. Preferred Stock 9.50%
  • PIMCO Corporate & Income Opportunity 11.60%
  • NEOS Nasdaq 100 High Income ETF 13.90%
  • SHP ETF Trust - NEOS S&P 500 High Income ETF 11.90%
  • Cushing MLP Total Return Closed Fund 15.10%
  • Trinity Capital Inc 13.10%
  • TappAlpha SPY Growth & Daily Income ETF 14.00%
  • WisdomTree Equity Premium Income Fund 12.10%
  • Calamos US Equity Autocallable Income ETF 11.00%
  • Neos Mlp & Energy Infrastructure High Income ETF 5.70%
  • Weighted yield (per year) 12.56%

Income is a defining feature here: many holdings show double-digit distribution yields, and the overall portfolio yield is estimated around 12.56%. That’s unusually high compared with broad equity indices and most bond benchmarks. Dividends and fund distributions can be an important part of total return, especially when they’re reinvested, but very high yields sometimes reflect higher underlying risk, leverage, or return-of-capital mechanics. Closed-end funds and option-writing ETFs, which feature heavily here, often use strategies that boost cash payouts in exchange for different risk trade-offs. Because the yield figures are point-in-time and the history is short, it’s worth seeing them as current indications rather than guaranteed long-run income levels.

Ongoing product costs Info

  • PIMCO Dynamic Income Fund 2.18%
  • Virtus InfraCap U.S. Preferred Stock 2.52%
  • PIMCO Corporate & Income Opportunity 1.19%
  • NEOS Nasdaq 100 High Income ETF 0.68%
  • SHP ETF Trust - NEOS S&P 500 High Income ETF 0.68%
  • Cushing MLP Total Return Closed Fund 2.84%
  • Weighted costs total (per year) 0.65%

The portfolio’s overall estimated cost (Total TER) is about 0.65% per year, despite several individual funds charging much more. Some closed-end and income funds have expense ratios above 2%, while the NEOS ETFs sit around 0.68%. TER (total expense ratio) is the annual fee the fund takes before performance reaches the investor, and over many years, even small differences can compound. Given the heavy use of specialized, actively managed, or structured income vehicles, a blended TER of 0.65% is actually quite moderate. This cost profile supports the income-focused strategy without being extreme, and it’s a positive sign that the higher-fee funds are balanced by lower-cost holdings in the overall mix.

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